A EPA
EPA/635/R-23/030
IRIS Assessment Protocol
www.epa.gov/iris
Protocol for the Naphthalene IRIS Assessment
(Preliminary Assessment Materials)
[CASRN 91-20-3]
March 2023
Integrated Risk Information System
Center for Public Health and Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
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Protocol for the Naphthalene IRIS Assessment
DISCLAIMER
This document is a public comment draft. This information is distributed solely for review
purposes under applicable information quality guidelines. It has not been formally disseminated by
the Environmental Protection Agency. It does not represent and should not be construed to
represent any Agency determination or policy. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
This document is a draft for review purposes only and does not constitute Agency policy.
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CONTENTS
CONTENTS iii
AUTHORS | CONTRIBUTORS | REVIEWERS ix
1. INTRODUCTION 10
2. SCOPING AND INITIAL PROBLEM FORMULATION SUMMARY 12
2.1. BACKGROUND 12
2.2. SCOPING SUMMARY 15
2.3. PROBLEM FORMULATION 16
2.4. KEY SCIENCE ISSUES 17
3. OVERALL OBJECTIVES AND SPECIFIC AIMS 19
3.1. SPECIFIC AIMS 19
4. LITERATURE SEARCH, SCREENING, AND INVENTORY 21
4.1. POPULATIONS, EXPOSURES, COMPARATORS, AND OUTCOMES (PECO) CRITERIA FOR THE
SYSTEMATIC EVIDENCE MAP 21
4.2. SUPPLEMENTAL SCREENING CRITERIA 22
4.3. LITERATURE SEARCH STRATEGIES 24
4.3.1. Core Database Searches 24
4.3.2. Targeted Search for PBPK Models 25
4.3.3. Other Resources Consulted 25
4.3.4. Non Peer-Reviewed Data 26
4.4. LITERATURE SCREENING 26
4.4.1. Title and Abstract-Level Screening 27
4.4.2. Full-Text Level Screening 28
4.4.3. Multiple Publications of the Same Data 28
4.4.4. Literature Screening Results 28
4.5. LITERATURE INVENTORY 28
4.5.1. Studies that Meet the Problem Formulation PECO Criteria 29
4.5.2. Organizational Approach for Supplemental Material 29
5. SPECIFY ASSESSMENT APPROACH 30
5.1. REFINEMENTS TO PECO CRITERIA 30
This document is a draft for review purposes only and does not constitute Agency policy.
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5.2. UNITS OF ANALYSIS FOR DEVELOPING EVIDENCE SYNTHESIS AND INTEGRATION
JUDGMENTS FOR HEALTH EFFECT CATEGORIES 32
5.3. CONSIDERATION OF SUPPLEMENTAL MATERIAL 33
5.3.1. Toxicokinetic (ADME) Information 33
5.3.2. Mechanistic Information 34
5.3.3. Case Studies 34
6. STUDY EVALUATION (RISK OF BIAS AND SENSITIVITY) 35
6.1. STUDY EVALUATION OVERVIEW FOR HEALTH EFFECT STUDIES 35
6.2. EPIDEMIOLOGY STUDY EVALUATION 39
6.2.1. Air monitoring or modeling 52
6.2.2. Biomarker assessment 53
6.3. EXPERIMENTAL ANIMAL STUDY EVALUATION 57
6.4. PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODEL EVALUATION 68
6.5. IN VITRO STUDY EVALUATION 70
7. DATA EXTRACTION OF STUDY METHODS AND RESULTS 82
8. EVIDENCE SYNTHESIS AND INTEGRATION 84
8.1. EVIDENCE SYNTHESIS 88
8.2. EVIDENCE INTEGRATION 97
9. DOSE-RESPONSE ASSESSMENT: SELECTING STUDIES AND QUANTITATIVE ANALYSIS 104
9.1. OVERVIEW 104
9.2. SELECTING STUDIES FOR DOSE-RESPONSE ASSESSMENT 105
9.2.1. Hazard and MOA Considerations for Dose Response 105
9.3. CONDUCTING THE DOSE-RESPONSE ASSESSMENT 110
9.3.1. Dose-Response Analysis in the Range of Observation 110
9.3.2. Dose Metrics 113
9.3.3. Dosimetric Modeling Summary 115
9.3.4. Extrapolation: Slope Factors and Unit Risk 115
9.3.5. Extrapolation: Reference Values 116
10. PROTOCOL HISTORY 119
REFERENCES 120
APPENDICES 135
APPENDIX A. SURVEY OF EXISTING REFERENCE VALUES FOR NAPHTHALENE 135
APPENDIX B. ELECTRONIC DATABASE SEARCH STRATEGIES 150
This document is a draft for review purposes only and does not constitute Agency policy.
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B.l. ELECTRONIC SCREENING 165
APPENDIX C. INITIAL LITERATURE INVENTORY FOR NAPHTHALENE (SYSTEMATIC EVIDENCE
MAP) 171
C.l. HUMAN AND ANIMAL HEALTH EFFECT STUDIES 173
C.2. PHARMACOKINETIC (PK)/PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODELS 176
This document is a draft for review purposes only and does not constitute Agency policy.
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TABLES
Table 2-1. EPA program interest in reassessment of naphthalene 16
Table 4-1. Populations, exposures, comparators, outcomes (PECO) criteria for the systematic
evidence map (i.e., problem formulation PECO) 21
Table 4-2. Categories of "Potentially Relevant Supplemental Material" 23
Table 5-1. Refined assessment PECO criteria for naphthalene 31
Table 5-2. Health effect categories and human and animal evidence unit of analysis endpoint
groupings for which evidence integration judgments will be developed for
naphthalene 32
Table 6-1. Information relevant to evaluation domains for epidemiology studies 40
Table 6-2. Questions to guide the development of criteria for each domain in epidemiology
studies 41
Table 6-3. Evaluation of exposure biomarkers in general population studies of naphthalene
(adapted from Phthalates SR protocol) (Radke et al., 2018) 54
Table 6-4. Questions to guide the development of criteria for each domain in experimental
animal toxicology studies 58
Table 6-5. Criteria for evaluating physiologically based pharmacokinetic (PBPK) models 69
Table 6-6. Domains, questions, and general considerations to guide the evaluation of in vitro
studies 72
Table 8-1. Generalized evidence profile table to show the relationship between evidence
synthesis and evidence integration to reach judgment of the evidence for
hazard 86
Table 8-2. Generalized evidence profile table to show the key findings and supporting rationale
from mechanistic analyses 87
Table 8-3. Considerations that inform evaluations and judgments of the strength of the evidence
for hazard 90
Table 8-4. Framework for strength of evidence judgments from studies in humans 94
Table 8-5. Framework for strength of evidence judgments from studies in animals 95
Table 8-6. Considerations that inform evidence integration judgments 97
Table 8-7. Framework for summary evidence integration judgments in the evidence integration
narrative 100
Table 9-1. Attributes used to evaluate studies for derivation of toxicity values (in addition to the
health effect category-specific evidence integration judgment) 107
Table 9-2. Specific example of presenting endpoints considered for dose-response modeling and
derivation of points of departure 109
Table 9-3. Internal dose metrics considered for use in assessing dose-response relationships for
naphthalene 114
Table A-l. Sources searched for naphthalene heath effect reference values 135
Table A-2. Details on derivation of the available health effect reference values for inhalation
exposure to naphthalene (from Figure 2-1 of the main text) 138
Table A-3. Details on derivation of the available health effect reference values for oral exposure
to naphthalene (from Figure 2-2 of the main text) 144
Table A-4. Details on additional inhalation values based on another agency's values or lacking
derivation descriptions 146
Table B-l. Core database search strategy 150
Table B-2. Targeted database search for PBPK models for naphthalene 159
This document is a draft for review purposes only and does not constitute Agency policy.
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Table B-3. Toxic Substances Control Act Test Submissions (TSCATS) search strategy 159
Table B-4. Processes used to augment the search of core databases for naphthalene 160
Table B-5. Electronic screening inclusion terms for naphthalene (listed alphabetically within each
organ/system category) 166
Table C-l. Summary of Novel PBPK and Airway Dosimetry Models for Naphthalene 177
Table C-2. Descriptive summary for the Kapraun et al. (2020) CFD-PBPK model 186
FIGURES
Figure 1-1. IRIS systematic review problem formulation and method documents 11
Figure 2-1. Available health effect reference values for inhalation exposure to naphthalene 14
Figure 2-2. Available health effect reference values for oral exposure to naphthalene 15
Figure 6-1. Overview of Integrated Risk Information System (IRIS) study evaluation approach 36
Figure C-l. Literature flow diagram for naphthalene 172
Figure C-2. Survey of human studies that met PECO criteria by study design and health systems
assessed 174
Figure C-3. Survey of animal studies that met PECO criteria by exposure duration, species, and
health systems assessed 175
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
ABBREVIATIONS
ADME absorption, distribution, metabolism, and excretion
B MD L benchmark dose lower confidence limit
BW3/4 body-weight scaling to the 3/4 power
CAA Clean Air Act
CAS Chemical Abstracts Service
CASRN Chemical Abstracts Service registry number
CERCLA Comprehensive Environmental Response, Compensation, and Liability Act
CI confidence interval
CPHEA Center for Public Health and Environmental Assessment
CO I conflict of interest
EPA Environmental Protection Agency
GLP good laboratory practices
HAP hazardous air pollutant
HAWC Health Assessment Workspace Collaborative
HEC human equivalent concentration
HERO Health and Environmental Research Online
IRIS Integrated Risk Information System
IUR inhalation unit risk
LOAEL lowest-observed-adverse-effect level
LOEL lowest-observed-effect level
MeSH Medical Subject Headings
MOA mode of action
NMD normalized mean difference
NOEL no-observed-effect level
NTP National Toxicology Program
OAR Office of Air and Radiation
OECD Organization for Economic Co-operation and Development
OLEM Office of Land and Emergency Management
ORD Office of Research and Development
OSF oral slope factor
PBPK physiologically based pharmacokinetic
PECO populations, exposures, comparators, and outcomes
PK pharmacokinetic
POD point of departure
RfC reference concentration
RfD oral reference dose
ROBINS-I Risk of Bias in Nonrandomized Studies of Interventions
UF uncertainty factor
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
AUTHORS | CONTRIBUTORS | REVIEWERS
Assessment Team
Ingrid L. Druwe. Ph.D. (co-Assessment Manager) U.S. EPA/ORD/CPHEA/CPAD
Erin Yost. Ph.D. (co-Assessment Manager)
Michelle Angrish. Ph.D.
Bevin Blake. Ph.D.
J. Allen Davis, M.S.P.H
Dustin Kapraun. Ph.D.
Martha Powers. M.P.H., Ph.D.
Paul Schlosser. Ph.D.
Rachel M. Shaffer. M.P.H., Ph.D.
Executive Direction
Wayne Cascio
V. Kay Holt
Samantha Jones
Kristina Thayer
Andrew Kraft
Paul White
Ravi Subramaniam
Garland Waleko
Janice Lee
Glenn Rice
Viktor Morozov
CPHEA Center Director
CPHEA Deputy Center Director
CPHEA Associate Director
CPAD Division Director
CPAD Associate Division Director, IRIS PFAS Team Lead
CPAD Senior Science Advisor
CPAD Senior Science Advisor (Acting)
CPHEA/CPAD/Toxic Effects Assessment (DC) Branch Chief (Acting)
CPHEA/CPAD/Toxic Effects Assessment (RTP) Branch Chief
CPHEA/CPAD/Science Assessment Methods Branch Chief
CPHEA/CPAD/Quantitative Assessment Branch Chief
Contributors and Production Team
Maureen Johnson
Ryan Jones
Dahnish Shams
Vicki Soto
Jessica Soto-Hernandez
Samuel Thacker
Garland Waleko
Channa Keshava
Suryanarayana Vulimiri
Audrey Galizia
Amanda Persad
Rebecca Schaefer
Brittany Schulz
John Bucher
U.S. EPA/ORD/CPHEA
Former Chemical manager, U.S. EPA/ORD/CPHEA
Oak Ridge Associated Universities (ORAU) Contractor
Oak Ridge Associated Universities (ORAU) Contractor
Sole Source Contractor, U.S. EPA
This document is a draft for review purposes only and does not constitute Agency policy.
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1. INTRODUCTION
The Integrated Risk Information System (IRIS) Program is undertaking a reassessment of
the health effects of naphthalene. IRIS assessments provide high quality, publicly available
information on the toxicity of chemicals to which the public might be exposed. These science
assessments are not regulations. Science assessments such as these provide a critical part of the
scientific foundation for subsequent risk assessment and risk management decisions made by EPA
program and regional offices to protect public health. IRIS assessments are also used by states and
local health agencies, tribes, other federal agencies, international health organizations, and other
external stakeholders.
An IRIS assessment plan (IAP) for naphthalene was released for public comment in July
2018, but the IRIS assessment of naphthalene was subsequently suspended prior to a public
meeting on the IAP due to changing priorities within the EPA as formally documented in the IRIS
Program Outlook-April 2019. Naphthalene was renominated as an IRIS assessment in 2021 as
described in A Message from the IRIS Program-June 2021. An updated IAP and errata sheet were
posted to the EPA website in September 2021 and presented at a public science meeting on
November 9, 2021 fhttps://www.epa.gov/iris/iris-public-science-meeting-nov-2021). to seek
input on the problem formulation components of the assessment plan.
The IAP summarizes the IRIS Program's scoping and problem formulation conclusions,
specifies the objectives and specific aims of the assessment, provides draft PECO (populations,
exposures, comparators, and outcomes) criteria, and identifies key areas of scientific complexity.
This protocol document incorporates the updated IAP content, including revisions based on public
input and updated scoping needs, and presents the methods for conducting the systematic review
and dose-response analysis for the assessment. Whereas the IAP describes what the assessment
will cover, chemical-specific protocols describe how the assessment will be conducted (see
Figure 1).
The systematic review methods described in this protocol are based on the Office of
Research and Development's ORD Staff Handbook for Developing Integrated Risk Information System
(IRIS) Assessments (referred to as the "IRIS Handbook") fU.S. EPA. 20221. The IRIS Handbook was
revised in 2022 to incorporate updates to assessment methodology as recommended in a report by
the National Academies of Sciences, Engineering, and Medicine (NASEM) (NASEM. 2021) on the
draft IRIS Handbook (U.S. EPA. 2020b). Prior to the suspension of the IRIS assessment of
naphthalene, some aspects of the assessment were already underway using methods included in
the draft Handbook (i.e., literature search, screening, and study evaluation); and when the
assessment was renominated, the assessment team considered the revisions made to the Handbook
in response to the NASEM report and concluded that the changes would not fundamentally impact
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
the previously initiated literature search, screening, and overall study evaluation ratings. Therefore,
for this assessment, studies will continue to be evaluated using the previously established
methodology described in the draft IRIS Handbook fU.S. EPA. 2020bl. This is consistent with a 2011
NASEM recommendation not to delay releasing assessments until systematic review methods are
finalized fNRC. 20111. The study evaluation methods described in this protocol have been
previously presented to NASEM and were positively received fNASEM. 20181: the refinements
recommended by NASEM (20211. and reflected in the final IRIS Handbook are generally aimed at
clarifying the IRIS study evaluation method but do not request a major overhaul of the study
evaluation methods*. fU.S. EPA. 2022: NASEM. 2021: U.S. EPA. 2020b: NASEM. 20181
The IRIS Program posts assessment protocols on its website. Public input received is
considered during preparation of the draft assessment.
Figure 1-1. IRIS systematic review problem formulation and method
documents.
1 The major study evaluation refinements recommended by NASEM (2021) include (1) clarifications to the
procedure for evaluating studies for sensitivity and (2) standardizing the procedure for evaluating reporting quality
between human and animal studies.
This document is a draft for review purposes only and does not constitute Agency policy.
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2.SCOPING AND INITIAL PROBLEM FORMULATION
SUMMARY
Section 2.1 provides a brief overview of aspects of the human exposure characteristics of
naphthalene that might provide useful context for this protocol. This overview is not intended to
provide a comprehensive description of the available information on these topics and is not
recommended for use in decision-making. The reader is encouraged to refer to the source materials
cited below, more recent publications on these topics, and authoritative reviews or assessments
focused on these topics.
2.1. BACKGROUND
Naphthalene is a polycyclic aromatic hydrocarbon that is a white crystalline solid with an
aromatic odor. It is soluble in organic solvents and stable in closed containers under normal
temperatures and pressures fNTP. 20111. Naphthalene is naturally occurring and is most
abundantly found in coal tar, coal, and petroleum fToxNet Hazardous Substances Data Bank. 2017:
ATSDR. 20051. The release of naphthalene also could occur because of its manufacture or use in the
chemical industry. In the United States, naphthalene is considered a high production volume (HPV)
chemical, though domestic production of naphthalene has decreased significantly from a peak of
900 million pounds in 1968 to an aggregate volume of 100-250 million pounds in 2015 fU.S. EPA.
20161. Naphthalene is also present in jet fuels, such as jet propulsion fuel 8 (JP-8) fATSDR. 20131.
Naphthalene is mainly used in the manufacture of dyes, surfactants, leather tanning agents,
dispersants, pesticides, resins, solvents, and chemical intermediates fATSDR. 20051. Major
consumer products containing naphthalene include moth repellents, in the form of mothballs or
crystals, and toilet deodorant blocks fATSDR. 20051. Naphthalene is used as fragrance in non-food-
use pesticide products, while naphthalene derivatives are also used as inert ingredients in non-food
use pesticide products regulated by EPA fU.S. EPA. 2015a. 2012c). Lastly, naphthalene is also a
constituent of tobacco smoke fATSDR. 20051.
The general public can be exposed to naphthalene via inhalation, ingestion, and dermal
routes. Inhalation is generally considered to be the predominant route of exposure (ToxNet
Hazardous Substances Data Bank. 20171. Naphthalene is emitted into the atmosphere by industrial
facilities, open burning and mobile sources. Naphthalene is a component of fuel oil and gasoline and
is produced as a combustion by-product in vehicle exhaust Exposure to naphthalene may also
come from contact with contaminated land and water resulting from spills during storage,
transportation and disposal of fuel oil, coal tar, etc. fCalEPA. 2004: IARC. 20021. Because tobacco
smoke and numerous consumer products contain and release naphthalene, naphthalene is a
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Protocol for the Naphthalene IRIS Assessment
contaminant of indoor air (CalEPA. 2004: IARC. 20021. For nonsmokers exposed to environmental
tobacco smoke in their residences, the naphthalene intake rate is estimated to be 1 to 3 |ig day-1 flia
and Batterman. 2010: Nazaroff and Singer. 20041. An estimate of the average total intake rate of
naphthalene via inhalation in ambient and indoor air is 19 [ig day-1 flia and Batterman. 2010:
Howard. 19891. Children can receive additional exposure to naphthalene through ingestion of soil
or food contaminated with naphthalene or through accidental ingestion of household products
containing naphthalene, such as mothballs and deodorant blocks fATSDR. 20051. that are
sometimes mistaken for candy. Occupational exposure to naphthalene occurs through inhalation
and dermal contact by workers in facilities where naphthalene is produced or used, such as
mothball manufacturing plants and creosote-impregnation facilities. High exposures to naphthalene
have also been suggested to occur in forest firefighters fRobinson etal.. 20081.
Naphthalene is readily absorbed into the systemic circulation following oral, dermal, or
inhalation exposure and distributed by the blood throughout the body. It can be transferred to the
developing fetus of pregnant women (Anziulewicz etal.. 1959: Zinkham and Childs. 1958.19571
and has been detected in human breast milk (Cok etal.. 2012: Tsang etal.. 2011: Pellizzari etal..
19821 and umbilical cord serum (Tsang etal.. 20111. Naphthalene is rapidly metabolized into a
wide array of metabolites, including reactive epoxide and quinone intermediates that may interact
with cellular macromolecules such as proteins and DNA. Two major metabolic pathways for
naphthalene have been identified: (1) a cytochrome P450 (CYP)-dependent pathway and (2) a
glutathione (GSH)-conjugation-dependent pathway. Metabolites pertaining to both major pathways
have been identified in the blood and urine of occupationally-exposed individuals and in
experimentally-exposed animals fATSDR. 2005: CalEPA. 2004: IARC. 20021. The naphthalene
metabolites 1-naphthol and 2-naphthol have been widely detected in the urine of the U.S. general
population, including in children aged 6-19 years old fCDC. 20221.
A summary of existing human health reference values for naphthalene (surveyed in August
2022 using methods described in Appendix A) is provided in Figure 1 (inhalation) and Figure 2
(oral). See Appendix Tables A-2 (inhalation reference values) and A-3 (oral reference values) for a
tabular summary, including derivation details of the displayed values; values with no derivation
details are listed in Table A-4.
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Naphthalene Inhalation Reference Values
1.E+04
1.E+03
1.E+02
1.E+01
1.E+00
1.E-01
1.E-02
1.E-03
1.E-04 ฆ-
1.E-05
ACUTE
i
~ PAC-3
NIOSH IDIH*
A PAC-2
NIOSH-STEL"
A PAC-1
ACGIH-STEL*
c:
Short Term
NIOSH-REL (TWA)*
Avg. of Other State Values |
b
0-
~ MDH HBV(lhr)
| Avg, of Other State Values]
Subchronic
OSHA-PEl (TWA)*
ACGIH-TLV (TWA)*
Cal/OSHAPEL (TWA)*
Health Canada Indoor RfC
MDH HBV(lyr) -0
*
Chronic
OEHHA REL (Chronic)
ATSDR-MRL (> 1yr| T EPA/IRIS RfC
OEHHA Cancer Risk Range
*
Avg. or
Other State Values
rrl i i r
10 100 1,000
Duration (hours)
r!
[August 202^
A PAC-3 jT ฎ
ฎ ง
A PAC-2 5> ง.
i i
A PAC-1 ฃ (2
ซ NIOSH IDLH*
ฉ NIOSH-STEL*
O NIOSH-REL (TWA)*
O ACGIH-STEL*
O ACGIH-TLV (TWA)*
O
O OSHA-PEL (TWA)*
O Cal/OSHA-PEL (TWA)*
X ATSDR-MRL (> 1yr)
~ MDHHBV(lhr)
~ MDHHBV(lyr)
o
-X OEHHA REL (Chronic) Z
3
-m- EPA/IRIS RfC
-m- RIVM TCA
-0 Health Canada Indoor RfC 15
~ Avg. of Other State Values
o OEHHA Cancer Risk Range
10,000 100,000 1,000,000
* Indicates an occupational value; expert judgment necessary prior to applying these values to the general public.
Figure 2-1. Available health effect reference values for inhalation exposure to
naphthalene. See Appendix Table A1 for a tabular summary, including information on how
each value was derived. Categories for the reference values based on their intended purpose are
shown in the legend - red for Emergency Response, gold for Occupational, and green for values
applicable to the General Public. OEHHA cancer risk range: range associated with a 10 s -104
cancer risk calculated based on the OEHHA cancer slope factor. Abbreviations: ACGIH = American
Conference of Governmental Industrial Hygienists; ATSDR = Agency for Toxic Substances and
Disease Registry; HBV = Health-Based Value; IDLH = Immediately Dangerous to Life and Health;
IRIS = Integrated Risk Information System; MDH = Minnesota Department of Health; MRL =
Minimal Risk Level; NIOSH = National Institute for Occupational Safety and Health; OEHHA =
California Environmental Protection Agency's Office of Environmental Health Hazard Assessment;
OSHA = Occupational Safety and Health Administration; PAC = Protective Action Criteria; PEL =
Permissible Exposure Limit; REL= Recommended Exposure Limit (NIOSH) or Reference Exposure
Level (California); RfC = Reference Concentration; RIVM = Rijksinstituut voor Volksgezondheid en
Milieu, The Netherlands Institute for Public Health and the Environment; STEL = Short-term
Exposure Limit; TCA = Tolerable Concentration; TLV = Threshold Limit Value; TWA = Time-
weighted average.
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Protocol for the Naphthalene IRIS Assessment
10
1
o.i
">
(O
"~
i
w
^ 0.01
ao
O)
tS o.ooi
0)
tn
O
Q
0.0001
0.00001
0.000001
000
Figure 2-2. Available health effect reference values for oral exposure to
naphthalene. See Appendix Table A2 for a tabular summary, including information on how
each value was derived. All values in this figure are intended for application in the general public.
OEHHA cancer risk range: range associated with a 10"6 -10"4 cancer risk calculated based on the
OEHHA cancer slope factor. Abbreviations: ATSDR = Agency for Toxic Substances and Disease
Registry; IRIS = Integrated Risk Information System; MRL = Minimal Risk Level; OPP = Office of
Pesticide Programs; RfD = Reference Dose; RIVM = Rijksinstituut voor Volksgezondheid en Milieu,
The Netherlands Institute for Public Health and the Environment; TDI = Tolerable Daily Intake.
2.2. SCOPING SUMMARY
1 Naphthalene is subject to regulation under several environmental statutes implemented by
2 EPA, including the Clean Water Act (CWA), Clean Air Act (CAA), Federal Fungicide Insecticide and
3 Rodenticide Act (FIFRA), Toxic Substances Control Act (TSCA); Emergency Planning and
4 Community Right-to-Know Act (EPCRA), Comprehensive Environmental Response, Compensation,
5 and Liability Act (CERCLA), and the Resource Conservation and Recovery Act (RCRA). Naphthalene
Naphthalene Oral Reference Values
August 2022
Acute
Short-Term
Subchronic
Chronic
ATSDR-MRL
EPA/OPP RfD
ATSDR-MRL ^
EPA/OPP RfD
RIVM TDI ฆ
EPA/IRIS RfD ฆ
X ATSDR-MRL
~ EPA/IRIS RfD
~ EPA/OPP RfD
ฆ RIVM TDI
OEHHA Cancer Risk Range
I ฆ ฆ ฆ
OEHHA Cancer Risk Range
^ | |
10 100 1,000
Duration (Days)
10,000
100,
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is also listed as a Hazardous Air Pollutant (HAP) by EPA and is a contaminant found at more than
300 National Priority List (Superfund) fU.S. EPA. 20231.
During initial scoping, the IRIS Program met with EPA program and regional offices that had
interest in an IRIS assessment for naphthalene to discuss specific assessment needs. Table 2-1
provides a summary of current programmatic interest. Additional programmatic and regional
needs and interests will be reviewed and updated as the assessment progresses.
Table 2-1. EPA program interest in reassessment of naphthalene
EPA program
Oral
Inhalation
Statutes/regulations/policies
Anticipated uses/interest
OLEM, Regions
X
X
Comprehensive Environmental
Response, Compensation and
Liability Act (CERCLA)
Naphthalene toxicological
information could be used to make
risk determinations for response
actions (e.g., short-term removals,
long-term remedial response
actions) under CERCLA and RCRA.
OCSPP
X
X
Toxic Substances Control Act
(TSCA)
Naphthalene toxicological
information could be used to
inform risk assessment and risk
management decisions under
TSCA.
OAR
X
X
Clean Air Act (CAA)
Naphthalene is listed as a
Hazardous Air Pollutant (HAP) and
is also a mobile source air toxic.
Naphthalene toxicological
information could be used to
inform risk assessment and risk
management decisions under CAA.
OLEM (Office of Land and Emergency Management)
OCSPP (Office of Chemical Safety and Pollution Prevention)
OAR (Office of Air and Radiation)
2.3. PROBLEM FORMULATION
A 1998 assessment of naphthalene is currently available on the IRIS website at
https://cfpub.epa.gov/ncea/iris2 /chemicalLanding.cfm7substance nmbr=436 (U.S. EPA. 1998b).
This assessment includes a review of inhalation studies which provide support for a reference
concentration (RfC) of 3 x 10 3 mg/m3 for noncancer effects based on hyperplasia and metaplasia in
respiratory and olfactory epithelium in mice, and a review of oral studies which provide support for
a reference dose (RfD) of 2 x 10 2 mg/kg-day for noncancer effects based on decreased body weight
in male rats. EPA's 1998 IRIS Toxicological Review of Naphthalene, which was conducted using
EPA's 1986 Cancer Guidelines fU.S. EPA. 19861. classified naphthalene as a Group C, possible human
carcinogen. This classification was based on inadequate carcinogenicity data in humans exposed to
naphthalene via the oral and inhalation routes, and limited evidence of carcinogenicity in animals
exposed to naphthalene via inhalation. The 1998 assessment concluded that a genotoxic
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1 mechanism appeared unlikely but hypothesized that the mechanism for tumorigenesis involves
2 oxygenated reactive metabolites produced via the cytochrome P450 monooxygenase system.
4 release of EPA's cancer guidelines fU.S. EPA. 2005al. new information on naphthalene has become
5 available (see Section 4.5), including bioassay data, potency estimations, and physiologically-based
6 pharmacokinetic (PBPK) models with the potential to assist in performing route-to-route and
7 animal-to-human extrapolations. More specifically, several significant studies on naphthalene
8 toxicity have been published, including a 2-year inhalation study performed by NTP in which
9 naphthalene-exposed rats showed an increased incidence of nasal tumors (NTP. 20001. In addition
10 to this NTP study, numerous studies (>70) have been published which provide mechanistic
11 information that could inform the naphthalene mode of action for cancer or noncancer effects.
12 These include studies that report on the involvement of specific cytochrome P450 subfamilies like
13 CYP2F and CYP2A in the metabolism and possible activation of reactive naphthalene intermediates
14 (Buckpittetal.. 2013: Morris. 2013: Morris and Buckpitt. 2009: Carlson. 2008: Genter etal.. 2006:
15 Buckpitt etal.. 2002: Su etal.. 2000: Lanza etal.. 1999: Shultz etal.. 1999) that may interact with
16 biological macromolecules such as proteins or DNA. Additionally, a PBPK model for naphthalene
17 was developed using controlled human dermal and inhalation exposures to JP-8, of which
18 naphthalene is a component fKim etal.. 20071. The results of this more recent research will be
19 evaluated using EPA's current cancer guidelines fU.S. EPA. 2005al and may provide new evidence
20 to better inform naphthalene toxicity values.
3
Since the posting of the IRIS toxicological review of naphthalene in 1998 and the 2005
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Evaluating interspecies differences in metabolism and toxicity: Naphthalene toxicity is
typically attributed to protein binding by naphthalene quinone metabolites and/or the
participation of naphthalene quinone metabolites in redox cycles leading to oxidative stress
and DNA damage fO'Brien. 19911. These quinone intermediates are produced via
cytochrome P450 (CYP)-dependent metabolism and may specifically involve the CYP2F
subfamily. While much progress has been made in the characterization of CYP2F2, the CYP
thought to be primarily involved in naphthalene metabolism in mice, characterizing the
relative contribution of P450 oxidizing enzymes to naphthalene metabolism in rats and
humans has been more difficult fBuckpitt etal.. 2002: Shultz etal.. 19991. Recent studies
show that, in addition to the CYP2F subfamily, the CYP2A class also plays an important role
in naphthalene-induced lung toxicity and may be the more pertinent enzyme in naphthalene
metabolism in humans fLi etal.. 2017: Su etal.. 20001. The rate and extent of metabolism of
naphthalene in various tissues and in different animal species, along with anatomical
differences in the nasal turbinates between species, will be important considerations in
evaluating differences in naphthalene toxicity across species.
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Cancer mode of action: Multiple animal and in vitro studies published since the 1998 IRIS
Toxicological Review have provided mechanistic information and postulated the
involvement of several biological processes in the development of naphthalene-induced
tumor formation. These proposed processes include genotoxicity, cytotoxicity, and
sustained regenerative cell proliferation. Among the key events identified by these studies
are the depletion of glutathione and the formation of reactive naphthalene quinone
metabolites via the cytochrome P450 pathway. These quinone metabolites may lead to
oxidative stress and DNA damage. To help inform the analysis and interpretation of the role
and biological plausibility of each of these proposed mechanisms occurring in humans and
their role in the formation of naphthalene-induced tumors, the supplemental materials
identified in the literature search will be reviewed to identify relevant information [e.g.,
workshops fU.S. EPA. 2014bl] that inform these topics. Differences in enzyme activities
between human and rodent tissues exist; therefore, evaluation of the cancer MOA in the
context of toxic metabolite formation and the relevance of these toxic metabolites to human
cancer hazard will also be evaluated.
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3.0VERALL OBJECTIVES AND SPECIFIC AIMS
The overall objective of this assessment is to identify adverse health effects and
characterize exposure-response relationships for these effects of naphthalene to derive toxicity
values (e.g., reference doses [RfDs], reference concentrations [RfCs], cancer risk estimates) as
supported by the available data. This assessment will use systematic review methods to evaluate
the epidemiological and toxicological literature for naphthalene, including consideration of relevant
mechanistic evidence. The evaluation conducted in this assessment will be consistent with relevant
EPA guidelines.2
3.1. SPECIFIC AIMS
Develop a systematic evidence map (SEM) to identify an initial literature inventory of
epidemiological studies (i.e., human), toxicological studies (i.e., experimental animal), PBPK
models, and supplemental literature pertinent to characterizing the health effects of
naphthalene exposure. The PECO criteria used to develop the SEM (referred to "problem
formulation PECO") is conducted according to the methods for literature search, screening,
and inventory described in Section 4 fThayer etal.. 2022: NASEM. 2021: Wolffe etal.. 20191.
o Epidemiological studies, toxicological studies, and PBPK models are identified for
inclusion based on predefined populations, exposure, comparators, and outcomes
(PECO) criteria.
o Supplemental material content includes: mechanistic studies, including in vivo, in
vitro, ex vivo, or in silico models; toxicokinetic and absorption, distribution,
metabolism, and excretion (ADME) studies; studies with routes of exposure other
than oral, inhalation, and dermal; case studies; studies that evaluate exposure and
health effects associated with the jet fuel JP-8; studies that are in a non-English
language; and studies that are abstract-only or did not have the full text available.
Use the initial literature inventory identified in the SEM to (1) develop assessment PECO
criteria that define the subset of studies that will be the focus of the systematic review; (2)
define the unit(s) of analysis at the level of endpoint or health outcome for hazard
characterization; and (3) identify priority analyses of supplemental material to address the
specific aims, uncertainties in hazard characterization, susceptibility, and dose-response
analysis.
Conduct study evaluations (risk of bias and sensitivity) for individual epidemiological and
toxicological studies that meet refined assessment PECO criteria.
2EPA guidelines: http://www.epa.gov/iris/basic-information-about-integrated-risk-information-
svstem#guidance/
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Conduct a scientific and technical review for PBPK models considered for use in the
assessment If a PBPK or PK model is selected for use, the most reliable dose metric will be
applied based on analyses of the available dose metrics and the outcomes to which they are
being applied.
Conduct data extraction (summarizing study methods and results) from epidemiological
and animal toxicological studies that meet the refined assessment PECO criteria.
For each evidence stream, and for each unit of analysis, use a structured framework to
develop and describe the strength of evidence across studies and the supporting rationale
("evidence synthesis"). Depending on the specific health endpoint or outcome, mechanistic
information and precursor events might be included in a unit of analysis.
For each health effect category, use a structured framework to develop and describe weight
of evidence judgments across evidence streams and the supporting rationale for those
judgments ("evidence integration"). The evidence integration analysis presents inferences
and conclusions on human relevance of findings in animals, cross-evidence stream
coherence, potentially susceptible populations and lifestages, and other critical inferences
supported by mechanistic, ADME, or PK/PBPK data (e.g., biological plausibility).
For each health effect category, summarize evidence synthesis and evidence integration
conclusions in an evidence profile table.
Derive toxicity values (e.g., reference doses [RfDs], reference concentrations [RfCs], cancer
risk estimates) as supported by the available data.
Characterize uncertainties and identify key data gaps and research needs, such as
limitations of the evidence base, limitations of the systematic review, and consideration of
dose relevance and pharmacokinetic differences when extrapolating findings from higher
dose animal studies to lower levels of human exposure.
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4.LITERATI)RE SEARCH, SCREENING, AND
INVENTORY
The literature search and screening processes described in this section were used to
conduct an SEM and identify an initial literature inventory for naphthalene (Appendix C), using
problem formulation PECO criteria (see Section 4.1) and supplemental screening criteria (see
Section 4.2) to guide the inclusion of studies. The resulting initial literature inventory was used to
develop assessment PECO criteria and identify priority analyses of supplemental material
(described in Chapter 5). The initial literature search as well as all subsequent literature search
updates are conducted using the processes described in this chapter, and therefore for the purposes
of this assessment the literature inventory developed as part of the SEM will be continually updated
with new studies as the assessment progresses.
4.1. POPULATIONS, EXPOSURES, COMPARATORS, AND OUTCOMES
(PECO) CRITERIA FOR THE SYSTEMATIC EVIDENCE MAP
PECO criteria are used to focus the research question(s), search terms, and inclusion criteria
in a systematic review. The PECO criteria used to develop the SEM and identify an initial literature
inventory are referred to hereafter as the "problem formulation PECO" (see Table 5-1) and were
intentionally broad in order to identify all the available evidence in humans and animal models.
The problem formulation PECO for naphthalene (see Table 4-1) was based on: (1)
nomination of the chemical for assessment, (2) discussions with scientists in EPA program and
regional offices to determine the scope of the assessment that will best meet Agency needs, and (3)
preliminary review of the health effects literature for naphthalene (primarily focusing on reviews
and authoritative health assessment documents) to identify the potential major health hazards
associated with exposure to naphthalene and key areas of scientific complexity.
Table 4-1. Populations, exposures, comparators, outcomes (PECO) criteria for
the systematic evidence map (i.e., problem formulation PECO)
PECO element
Evidence
Populations3
Human: Anv population and lifestage (occupational or general population, including children
and other sensitive populations). The following study designs will be considered most
informative: controlled exposure, cohort, case-control, cross-sectional, and ecological.
Animal: Nonhuman mammalian animal species (whole organism) of anv lifestage (including
preconception, in utero, lactation, peripubertal, and adult stages). Studies of transgenic
animals will be tracked as mechanistic studies under "potentially relevant supplemental
material."
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PECO element
Evidence
Exposures
Human: Anv exposure to naphthalene (CASRN 91-20-3), including occupational exposures.
Animal: Anv exposure to naphthalene (CASRN 91-20-3) via oral or inhalation routefsl. Studies
involving exposures to mixtures will be included only if they include an arm with exposure to
naphthalene alone. Other exposure routes, including injection and dermal, will be tracked
during title and abstract screening and tagged as "supplemental information."
Studies describing physiologically-based pharmacokinetic (PBPK) models for naphthalene will
be included.
Comparators
Human: A comparison or referent population exposed to lower levels (or no
exposure/exposure below detection limits) of naphthalene, or exposure to naphthalene for
shorter periods of time.
Animal: A concurrent control group exposed to vehicle-onlv treatment.
Outcomes
All health outcomes (both cancer and noncancer). In general, endpoints related to clinical
diagnostic criteria, disease outcomes, histopathological examination, or other
apical/phenotypic outcomes will be prioritized for evidence synthesis over outcomes such as
biochemical measures.
4,2. SUPPLEMENTAL SCREENING CRITERIA
1 During the literature screening process, studies containing information potentially relevant
2 to the specific aims of the assessment are tagged as supplemental material by category. Some
3 studies could emerge as being critically important to the assessment and may need to be evaluated
4 and summarized at the individual study level (e.g., certain cancer MOA or ADME studies), or might
5 be helpful to provide context (e.g., provide hazard evidence from routes or durations of exposure
6 not meeting the refined assessment PECO), or might not be cited at all in the assessment
7 (e.g., individual studies that contribute to a well-established scientific conclusion). Because it is
8 often difficult to assess the impact of individual studies tagged as supplemental material on
9 assessment conclusions at the screening stage, the tagging structure, described in Table 4-2, allows
10 for easy retrieval later in the assessment process.
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Table 4-2. Categories of "Potentially Relevant Supplemental Material"
Category (Tag)
Description
Mechanistic
Studies that do not meet PECO criteria but do report measurements related to a health outcome that inform the biological
or chemical events associated with phenotypic effects. Experimental design could include in vitro, in vivo (by any route of
exposure), ex vivo, and in silico studies in mammalian and nonmammalian model systems. Studies where the chemical is
used as a laboratory reagent generally do not need to be tagged (e.g., as a chemical probe used to measure antibody
response).
[During screening, especially at the title and abstract (TIAB) level, it may not be readily apparent for studies that meet P, E,
and C criteria if the endpoint(s) in a study are best classified as phenotypic or mechanistic with respect to the 0 criteria. In
these cases, the study should be screened as "unclear" during TIAB screening, and a determination made based on full-text
review (in consultation with a content expert as needed). Full-text retrieval is performed for studies of transgenic model
systems that meet E and C criteria to determine if they include phenotypic information in wildtype animals that meet P and 0
criteria but is not reported in the abstract.]
Toxicokinetic
(ADME)
Toxicokinetic (ADME) studies are primarily controlled experiments, where defined exposures usually occur by intravenous,
oral, inhalation, or dermal routes, and the concentration of particles, a chemical, or its metabolites in blood or serum, other
body tissues, or excreta are then measured.
These data are used to estimate the amount absorbed (A), distributed (D), metabolized (M), and/or excreted (E).
The most informative studies involve measurements over time such that the initial increase and subsequent
concentration decline is observed, preferably at multiple exposure levels.
Data collected from multiple tissues or excreta at a single time-point also inform distribution.
ADME data can also be collected from human subjects who have had environmental or workplace exposures that are
not quantified or fully defined. However, to be useful such data must involve either repeated measurements over a
time-period when exposure is known (e.g., is zero because previous exposure ended) *or* time- and subject-matched
tissue or excreta concentrations (e.g., plasma and urine, or maternal and cord blood).
ADME data, especially metabolism and tissue partition coefficient information, can be generated using in vitro model
systems. Although in vitro data may not be as definitive as in vivo data, these studies should also be tracked as ADME.
For large evidence bases it may be appropriate to separately track the in vitro ADME studies.
*Studies describing environmental fate and transport or metabolism in bacteria or model systems not applicable to humans
or animals should not be tagged.
Non-PECO route
of exposure
Epidemiological or animal studies that use a non-PECO route of exposure, (e.g., injection, dermal).
*This categorization generally does not apply to epidemiological studies where the exposure route may be unclear; such
studies advance to full-text review to determine PECO relevance if the route(s) of exposure are plausible.
PBPK model
application
Studies that describe the application of PBPK model(s) for naphthalene but do not develop a novel, whole-organism PBPK
model. Examples: pharmacokinetic and toxicological studies that make use of existing PBPK models; cell culture analogs of
PBPK models.
Case reports or
case series
Case reports of < 3 subjects that describe health outcomes after exposure.
JP-8 health
effect studies
Studies that evaluate exposure and health effects associated with the jet fuel JP-8 but do not evaluate the effects of
naphthalene as a standalone compound. Human studies that use measures of JP-8 rather than naphthalene alone in
regression analyses will be tagged to this category.
Non-English
studies
Records that are in a non-English language.
Abstract only or
full text not
available
Records that do not contain sufficient documentation to support study evaluation and data extraction.
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4,3. LITERATURE SEARCH STRATEGIES
4.3.1. Core Database Searches
Literature search strategies were developed using key terms and words related to the
problem formulation PECO criteria. Standard terms were used to gather information on health
outcomes (e.g., toxicity, hematology, teratogen). Terms for specific experimental animal species
were also included. Exposure terms were used to capture studies that are not indexed by the
chemical name (e.g., moth balls, camphor). Because each database has its own search architecture,
the resulting search strategy was tailored to account for each database's unique search
functionality.
The following databases were searched:
PubMed (National Library of Medicine)
Web of Science (Thomson Reuters)
Toxline (National Library of Medicine)3
Database searches were conducted in February 2013, December 2014, November 2015,
January 2017, September 2017, February 2019, January 2021, and January 2022. Searches
conducted in January 2017 added terms to the PubMed query looking for information on
naphthalene metabolites (1,4-naphthoquinone; 1,2-naphthoquinone; naphthalene 1,2-oxide; and
l,2-dihydroxy-l,2-dihydronaphthalene). Searches were not restricted by publication date and no
language restrictions were applied. The detailed search strategies are presented in Appendix B
(Table B-l). Literature searches were conducted using EPA's Health and Environmental Research
Online (HERO) database.4
The database searches will be updated throughout assessment draft development to
identify literature published during the course of review. The last full literature search update will
be conducted less than 1 year before the planned release of the draft document for public comment
The results returned (i.e., the number of "hits" from each electronic database or other literature
source), including the results of any literature search updates, are documented in the literature
flow diagrams (see Appendix C), which also reflect the literature screening decisions. The IRIS
Program takes extra steps to ensure identification of pertinent studies by encouraging the scientific
community and the public to identify additional studies and ongoing research and by considering
late breaking studies that would impact the credibility of the conclusions, even during the review
3 The ToxLine database was migrated to PubMed after the 2019 literature search update, so was not included in
subsequent literature search updates.
4Health and Environmental Research Online: https: //hero.epa.gov/hero/.
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1 process.5 Studies identified after peer review begins will be considered for inclusion only if they
2 meet the assessment PECO criteria and could fundamentally alter the assessment's primary
3 conclusions.
4.3.2. Targeted Search for PBPK Models
4 To ensure that PBPK models for naphthalene were not missed by the broad literature
5 search described in the section above, an additional targeted search for PBPK models for
6 naphthalene was conducted in PubMed in August 2022. This search strategy is presented in
7 Appendix B (Table B-2). These studies were screened according to the methods in Section 4.4 by
8 two independent reviewers with expertise in PBPK modeling.
4.3.3. Other Resources Consulted
9 The literature search strategies described above are designed to be broad, but like any
10 search strategy, studies can be missed [e.g., cases where the specific chemical is not mentioned in
11 title, abstract, or keyword content; ability to capture "gray" literature (studies not reported in the
12 peer-reviewed literature) that is not indexed in the databases listed above]. Thus, in addition to the
13 core database searches, the sources below are used to identify studies that could have been missed
14 (see Appendix B, Table B-3 and B-4 for details):
15 Identification of Toxic Substances Control Act Test Submissions (TSCATS) by searching
16 TSCATS 2, TSCATS 1, EPA's Chemical Data Access Tool (CDAT), and Google searches for
17 TSCA recent submissions.
18 Manually searching citations from published review articles and national and international
19 health agency documents.
20 "Backward" searches (to identify articles cited by included studies, reviews, or prior
21 assessments by other agencies) and "forward" searches (to identify articles that cite those
22 studies).
23 References that had been previously added to the HERO project page for the naphthalene
24 assessment during the development of earlier draft materials.
25 Searching a combination of Chemical Abstract Service Registry Numbers (CASRNs) and
26 synonyms on chemical assessment-related websites.
27 High throughput screening information for naphthalene from EPA's ToxCast or Tox21 will
28 not be pursued in this assessment due to quality control (QC) concerns. The analytical QC
29 performed by ToxCast found that naphthalene was present in the sample at the initial timepoint
30 (TO) but was not detectable at a later timepoint (at 4 months T4), indicating that decomposition
5IRIS "stopping rules": https://www.epa.gov/sites/production/files/2014-
06/documents /iris stoppingrules.pdf.
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had occurred at some point during that time period. Considering that naphthalene is volatile/semi-
volatile and the ToxCast assays rely on liquid-based cell and cell-free systems, the stability of the
chemical in the test system is uncertain and bioactivity results are difficult to interpret. Access to
the naphthalene assays and QC for these may be found at the ToxCast Dashboard by following this
link (click on "QC Data ID" to view the results):
https://comptox.epa.gov/dash board/dsstoxdb/results?search=DTXSID802 0913 #invitrodb-
bioassays-toxcast-tox21.
4.3.4. Non Peer-Reviewed Data
IRIS assessments rely mainly on publicly accessible, peer-reviewed studies. However, it is
possible that unpublished data directly relevant to the PECO might be identified during assessment
development In these instances, EPA will try to get permission to make the data publicly available
(e.g., in HERO); data that cannot be made publicly available are not used in IRIS assessments. In
addition, on rare occasions where unpublished data would be used to support key assessment
decisions (e.g., deriving a toxicity value), EPA may obtain external peer review if the owners of the
data are willing to have the study details and results made publicly accessible, or if an unpublished
report is publicly accessible (or submitted to EPA in a non-confidential manner) fU.S. EPA. 2015b!
This independent, contractor driven, peer review would include an evaluation of the study similar
to that for peer review of a journal publication. The contractor would identify and typically select
three scientists knowledgeable in scientific disciplines relevant to the topic as potential peer
reviewers. Persons invited to serve as peer reviewers would be screened for conflict of interest. In
most instances, the peer review would be conducted by letter review. The study and its related
information, if used in the IRIS assessment, would become publicly available. In the assessment,
EPA would acknowledge that the document underwent external peer review managed by the
Agency, and the names of the peer reviewers would be identified. In certain cases, IRIS will assess
the utility of an analysis of accessible raw data (with descriptive methods) that has undergone
rigorous quality assurance/quality control review (e.g., ToxCast/Tox21 data, results of NTP studies
not yet published) but that have not yet undergone external peer review.
Unpublished data from personal author communication can supplement a peer-reviewed
study as long as the information is made publicly available. If such ancillary information is acquired,
it will be documented in the Health Assessment Workspace Collaborative (HAWC) or HERO project
page (depending on the nature of the information received).
4.4. LITERATURE SCREENING
This screening strategy was used to identify an initial literature inventory (described in
Appendix C) and will be used in subsequent literature search updates. The problem formulation
PECO criteria described in Section 4.1 are used to determine inclusion or exclusion of a reference as
a primary source of health effects data or a published PBPK model. In addition to the inclusion of
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studies that meet the problem formulation PECO criteria, studies containing supplemental material
that is potentially relevant to the specific aims are tracked during the screening process using the
categories described in Section 4.2. Although not considered to directly meet PECO criteria, these
studies are not strictly excluded unless otherwise specified. Unlike studies that meet PECO criteria,
supplemental studies may not be subject to systematic review unless specifically defined questions
are identified that focus the mechanistic (or other) analysis to inform the specific aims (see
Section 3.1).
4.4.1. Title and Abstract-Level Screening
Following a pilot phase to calibrate screening guidance, two screeners independently
conduct a title and abstract screen of the search results to identify records that appeared to meet
the problem formulation PECO criteria. For literature searches conducted through November 2015,
all identified records were first electronically screened with a set of terms intended to prioritize
"on-topic" references for title and abstract review (see Appendix B for a description of electronic
screening methods and the list of inclusion terms). Title/abstract screening was then performed
manually on all records prioritized by the electronic screen. For literature searches conducted after
November 2015, no electronic screen was performed due to the smaller number of records
identified, and title/abstract screening was performed on all records.
The software platforms used for screening the literature for naphthalene changed over
time, reflecting the technology that was available at the time of each literature search. In all cases,
screening was performed manually (machine learning functionality was not applied), and therefore
EPA does not anticipate that screening results are affected by the type of software used. The
software platforms used for title/abstract screening are EndNote (for literature searches conducted
between 2013 and 2017), SWIFT-Active Screener software (for literature search conducted in
2019) fhttps://swi ft.sciome.com/activescreenerI or DistillerSR (for literature searches conducted
in 2021 and thereafter) fhttps: //www.evidencepartners.com/products/distillersr-systematic-
re view-software/).
For citations with no abstract, articles are screened based on all or some of the following:
title relevance, page numbers (articles two pages in length or less may be assumed to be conference
reports, editorials, or letters), and PubMed MeSH (Medical Subject Headings, e.g., a study might not
be considered further if there are no human health- or biology-related MeSH terms). Screening
conflicts are resolved by discussion among the primary screeners with consultation by a third
reviewer or technical advisor (if needed) to resolve any remaining disagreements. Eligibility status
of non-English studies is assessed using the same approach with online translation tools or
engagement with a native speaker. Non-English studies were tracked during screening and tagged
as supplemental for possible further evaluation.
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4.4.2. Full-Text Level Screening
Records that are not excluded based on the title and abstract are advanced to full-text
review. Full-text copies of these potentially relevant records are retrieved, stored in the HERO
database, and independently assessed by two screeners to confirm eligibility according to the
problem formulation PECO criteria. Screening conflicts are resolved by discussion among the
primary screeners with consultation by a third reviewer or technical advisor (as needed to resolve
any remaining disagreements). Studies that advance to full-text review can also be tagged as
"potentially relevant supplemental material." Approaches for language translation include use of an
online translation tool, an engagement of a native speaker from within EPA, or use of fee-based
translation services. Fee-based translation services for non-English studies are typically reserved
for studies that are anticipated as being useful for toxicity value derivation.
4.4.3. Multiple Publications of the Same Data
When there were multiple publications using the same or overlapping data, all publications
on the research were included, with one selected for use as the primary study; the others were
considered as secondary publications with annotation indicating their relationship to the primary
record during data extraction. For epidemiology studies, the primary publication is generally the
one with the longest follow-up, the largest number of cases, or the most recent publication date. For
animal studies, the primary publication is generally the one with the longest duration of exposure,
or the one that assessed the outcome(s) most informative to the PECO. For both epidemiology and
animal studies, EPA will include relevant data from all publications of the study; although, if the
same outcome is reported in more than one report, the data will only be extracted once.
4.4.4. Literature Screening Results
The results of this screening process are posted on the project page for this assessment in
the HERO database fhttps://hero.epa.gov/hero/index.cfm/proiect/page/project id/3671 and
studies have been "tagged" with appropriate category descriptors (e.g., included, excluded,
potentially relevant supplemental material). The literature inventory of studies meeting problem
formulation PECO criteria is shown in Appendix C (see Section 4.5 for details on how literature
inventories are created).
4.5. LITERATURE INVENTORY
During title/abstract or full text level screening, studies are categorized by evidence type
(human or animal) or category of supplemental information (e.g., mechanistic, ADME). Next, study
design details for studies that meet the problem formulation PECO criteria are summarized as
described in Section 4.5.1. A more granular tagging of supplemental material may also be conducted
as described in Section 4.5.2. The results of this categorization and tagging are referred to as the
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literature inventory and is the key analysis output of the SEM. The literature inventory of studies
meeting the problem formulation PECO criteria is shown in the SEM described in Appendix C.
4.5.1. Studies that Meet the Problem Formulation PECO Criteria
During full text screening, all human and animal studies that met the problem formulation
PECO criteria are briefly summarized to facilitate subsequent review by subject matter experts. For
animal studies, the following information is captured: study type [acute (<24 hours), short term (1-
30 days), subchronic (30-90 days), chronic (>90 days), reproductive, developmental], duration and
timing of treatment, route, species, strain, sex, dose or concentration levels tested, dose or
concentration units, health system and specific endpoints assessed, and a brief summary of findings
at the health system level based on author-reported statistical significance. For human studies, the
following information is summarized: population type (e.g., general population-adult, occupational,
pregnant women, infants and children), study type (e.g., controlled trial, cross-sectional, cohort,
case-control), short free text description of study population, sex, major route of exposure (if
known), description of how exposure was assessed, health system and specific outcome assessed,
and a summary of findings at the health system level based on author-reported statistical
significance (null or an indication of any associations found and a description of how the exposure
was quantified in the analysis). Studies are extracted into Excel by one team member and checked
by at least one other team member. These study summaries are referred to as literature inventories
and are presented using Tableau visualization software (https: //www.tableau.com/).
All PBPK models identified in the literature search are reviewed by subject matter experts
and are summarized in Appendix C of this protocol in both descriptive text and in a tabular format
4.5.2. Organizational Approach for Supplemental Material
Inventories may also be created for other categories of studies that were tagged as
"potentially relevant supplemental material" during screening, including mechanistic studies
(e.g., in vitro or in silico models), ADME studies, and other studies that do not meet the specific
PECO criteria but that may still be relevant to the research question(s). Here, the objective is to
create an inventory of studies that can be tracked and further summarized as neededfor example,
by model system, key characteristic [e.g., of carcinogens; Smith etal. (2016)] mechanistic endpoint,
or key eventto support analyses of critical questions that arise at various stages of the systematic
review. See Section 5.3 for a description how the inventory and analysis of supplemental material
will be approached. Any inventories of potentially relevant supplemental material created for this
assessment will be made publicly available.
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5.SPECIFY ASSESSMENT APPROACH
The primary purpose of this step is to provide further specification to the assessment
methods based on characterization of the extent and nature of the evidence identified from the
literature inventory. This includes refinements to PECO criteria and defining the unit(s) of analysis
for health endpoints/outcomes during evidence synthesis, and presenting analysis approaches for
mechanistic, ADME, and other types of supplemental material content. A unit of analysis is an
outcome or group of related outcomes within a health effect category that are considered together
during evidence synthesis (see Section 8).
5.1. REFINEMENTS TO PECO CRITERIA
Refinements to the problem formulation PECO criteria were made based on the creation of
initial literature inventories by subject matter experts, which are presented in Appendix C. The
assessment PECO criteria (see Table 5-1) reflect the subset of studies that will be the focus of the
systematic review and will move forward for study evaluation and evidence synthesis.
The systematic review will focus on the health outcome categories identified in the
literature inventory, that appear to have sufficient information available to support hazard
identification, i.e., respiratory system (nasal and pulmonary), hematological, immune system,
reproductive system, developmental, and cancer. Ocular effects such as cataracts were not included
in the assessment PECO because they are reported to occur at higher naphthalene exposure levels
compared to other types of health outcomes fYostetal.. 20211 and therefore are not likely to drive
the derivation of toxicity values. Other health outcome categories identified in the initial literature
inventory were not included in the assessment PECO because they do not appear to have enough
information to support hazard identification. For instance, although an association between
naphthalene and severe neonatal jaundice was identified in a cross-sectional study (Familusi and
Dawodu. 1985). this is thought to be a secondary effect of hemolytic anemia and therefore hepatic
effects were not included in the assessment PECO. Cardiometabolic effects including obesity,
hypertension, and metabolic syndrome were identified in two cross-sectional studies that
evaluated association with naphthalene metabolites in urine fRanibar etal.. 2015: Scinicariello and
Buser. 20141 but these observations were considered too limited to support hazard identification.
Evidence for other health outcome categories such as renal/urinary and endocrine/exocrine was
largely null based on the available studies. Therefore, unless additional evidence becomes available,
studies that do not report on any of the health outcome categories listed in the assessment PECO
will not be included in the systematic review and will not undergo study evaluation.
Among the available animal studies, literature screening indicated that there were generally
sufficient numbers of multi-dose chronic, subchronic, or developmental exposure studies available
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to inform weight of evidence and dose-response analysis for each of the major health effect
categories being considered for systematic review. Because longer duration studies are preferred
for dose-response assessment to inform lifetime toxicity values, it was decided for the purposes of
this assessment that non-developmental studies with exposures <30 days in duration will only be
included in the systematic review for a given health effect if longer duration studies are not
available or if they contribute critical information to the weight of evidence or dose-response
analysis. An iterative approach will be applied when determining which acute and short-term
duration studies will be included in the systematic review. For instance, the 1- and 5-day inhalation
studies by Dodd etal. (20101 will be included in the systematic review because they provide
information on the concentration- and time-dependent development of nasal and olfactory necrosis
in rats exposed to naphthalene, which is anticipated to be useful for dose-response analysis.
Likewise, the 14-day oral study by Shopp etal. T19841 will be included along with the 90-day study
from the same report to demonstrate dose- and time-dependent responses. All studies exposing
animals during developmental life stages (e.g., gestational exposure studies) will be included
regardless of exposure duration, as short-term exposures may coincide with windows of
susceptibility. Studies with exposure durations <30 days that do not meet these criteria will not be
included in the systematic review and will not undergo study evaluation.
Table 5-1. Refined assessment PECO criteria for naphthalene
PECO element
Evidence
Populations3
Human: Anv population and lifestage (occupational or general population, including children
and other sensitive populations). The following study designs will be considered most
informative: controlled exposure, cohort, case-control, cross-sectional, and ecological.
Animal: Nonhuman mammalian animal species (whole organism) of anv lifestage (including
preconception, in utero, lactation, peripubertal, and adult stages). Studies of transgenic
animals will be tracked as mechanistic studies under "potentially relevant supplemental
material."
Exposures
Human: Anv exposure to naphthalene (CASRN 91-20-3), including occupational exposures.
Animal: Anv exposure to naphthalene (CASRN 91-20-3) via oral or inhalation, routefsl for >30
days. Non-developmental studies with exposures < 30 days in duration will only be included in
the systematic review for a given health effect if longer duration studies are not available or if
they contribute critical information to the weight of evidence or dose-response analysis.
Studies exposing animals during developmental lifestages (e.g., gestational exposure) will be
included regardless of exposure duration. Studies involving exposures to mixtures will be
included only if they include an arm with exposure to naphthalene alone. Other exposure
routes, including injection and dermal, will be tracked during title and abstract screening and
tagged as "supplemental information."
Studies describing physiologically-based pharmacokinetic (PBPK) models for naphthalene will
be included.
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PECO element
Evidence
Comparators
Human: A comparison or referent population exposed to lower levels (or no
exposure/exposure below detection limits) of naphthalene, or exposure to naphthalene for
shorter periods of time.
Animal: A concurrent control group exposed to vehicle-onlv treatment.
Outcomes
Health outcomes: respiratory svstem, hematological, immune svstem, reproductive svstem,
developmental, and cancer. In general, endpoints related to clinical diagnostic criteria, disease
outcomes, histopathological examination, or other apical/phenotypic outcomes will be
prioritized for evidence synthesis over outcomes such as biochemical measures.
5.2. UNITS OF ANALYSIS FOR DEVELOPING EVIDENCE SYNTHESIS AND
INTEGRATION JUDGMENTS FOR HEALTH EFFECT CATEGORIES
1 The planned units of analysis based on outcomes identified in the assessment PECO criteria
2 are summarized in Table 5-2. General considerations for defining the units of analysis are
3 presented in the IRIS Handbook (U.S. EPA. 20221. Each unit of analysis is initially synthesized and
4 judged separately within an evidence stream (see Section 8.1). Evidence integration judgments
5 focus on the stronger within evidence stream synthesis conclusions when multiple units of analysis
6 are synthesized. The evidence synthesis judgments are used alongside other key considerations
7 (i.e., human relevance of findings in animal evidence, coherence across evidence streams,
8 information on susceptible populations or lifestages, and other critical inferences that draw on
9 mechanistic evidence) to draw an overall evidence integration judgment for each health effect
10 category or more granular health outcome grouping (see Section 8.2). As new evidence to inform
11 potential naphthalene-associated health hazards become available, the assessment team will
12 consider updates to the units of analysis as appropriate.
Table 5-2. Health effect categories and human and animal evidence unit of
analysis endpoint groupings for which evidence integration judgments will be
developed for naphthalene
Health Effect Categories
for Evidence Integration
Units of Analysis for Evidence Synthesis That Inform Evidence Integration
(Each bullet represents a unit of analysis)
Human Evidence
Animal Evidence
Respiratory
Any noncancer respiratory outcomes
Pulmonary lesions
Nasal/olfactory lesions
Lung weight
Hematological
Hematological evaluations of red blood
cells, platelets, and clotting factors
Hematological evaluations of red blood
cells, platelets, and clotting factors
Immune
Functional immune measures of
sensitization or allergic response (asthma,
dermal and nasal allergic measures)
Functional immunotoxicity battery
Leukocyte counts
Thymus and spleen weights
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Health Effect Categories
for Evidence Integration
Units of Analysis for Evidence Synthesis That Inform Evidence Integration
(Each bullet represents a unit of analysis)
Human Evidence
Animal Evidence
Observable immune measures of
sensitization or allergic response (e.g.,
leukocyte counts, cytokine secretion)
Immunosuppression
Histopathology of lymph nodes, thymus,
and spleen
Reproductive
Sperm/semen parameters
Reproductive hormones
Preterm birth
Pregnancy outcomes (pregnant at
sacrifice/premature delivery, maternal
body weight)
Gonad weights
Histopathology of male and female
reproductive organs
Developmental
Fetal growth (e.g., birth weight, birth
length)
Neurodevelopment
*Maternal-fetal parameters described in the
analysis of reproductive outcomes (preterm birth,
cord blood hormone levels) may also be used to
support the analysis of developmental outcomes.
Fetal viability (live and dead fetuses,
implantations, resorptions)
Fetal body weight
Fetal structural alterations
Postnatal growth and viability
*An analysis of dam health (e.g., weight gain, food
consumption) is also conducted to support
conclusions of specificity of the effects as being
developmental (versus derivative of maternal
toxicity). Exposure during pregnancy can affect
both the mother and the fetus, and it is frequently
not possible to determine whether effects on the
fetus are in response to or separate from maternal
toxicity in studies that report both. The maternal
endpoints in animal toxicology studies described in
this section (maternal body weight gain and
gestation length) must therefore be considered in
conjunction with the fetal endpoints (survival,
growth, and structural alterations)
Carcinogenicity
Lung cancer
Pulmonary tumors or precancerous lesions
Nasal tumors or precancerous lesions
5.3. CONSIDERATION OF SUPPLEMENTAL MATERIAL
5.3.1. Toxicokinetic (ADME) Information
1 Naphthalene toxicity is related to the production of reactive metabolites in the body
2 (naphthalene 1,2-oxide; 1,2-naphthoquinone; and 1,4-naphthoquinone). The analysis of
3 interspecies differences that could affect the formation and elimination of these toxic metabolites
4 was identified as a key science issue during problem formulation (Section 2.4). The studies
5 identified as "Toxicokinetic (ADME)" in the literature search will be reviewed and synthesized with
6 focus on interspecies differences, such as CYP enzyme activity, that could affect the biological
7 plausibility of these toxic metabolites being formed in humans.
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5.3.2. Mechanistic Information
The analysis of biological processes underlying naphthalene-induced tumor formation was
identified as a key science issue during problem formulation (see Section 2.4). Studies tagged as
containing mechanistic information will be inventoried to identify and organize data that can be
used to support the analysis of cancer MOA in the context of toxic naphthalene metabolite
formation.
5.3.3. Case Studies
Human case studies exist for naphthalene that may provide relevant supporting
information for hazard identification. For instance, case reports have documented laryngeal cancer
among workers in a German naphthalene purification plant fWolf. 1978.19761 and colorectal
cancer among Nigerian patients with a history of taking a naphthalene-containing indigenous
treatment fAiao etal.. 19881. Hemolytic anemia has been frequently documented in case reports of
individuals exposed to naphthalene, particularly among children who have ingested mothballs and
in infants whose clothing or bedding was stored in mothballs fATSDR. 20051. The case reports
identified in the literature search for naphthalene will be inventoried to capture information on the
study populations and the types of health effects observed and may be used to supplement the
human evidence syntheses.
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6.STUDY EVALUATION (RISK OF BIAS AND
SENSITIVITY)
The general approach for evaluating primary health effect studies that meet assessment
PECO criteria is described in Section 6.1. Instructional and informational materials for study
evaluations are available at https://hawcprd.epa.gov/assessment/100000039/. The approach is
conceptually the same for epidemiology, controlled human exposure, animal toxicology, and in vitro
studies but the application specifics differ; thus, they are described separately in Sections 6.2, 6.3
and 6.5, respectively. Any physiologically based PBPK models used in the assessment are evaluated
using methods described in the Quality Assurance Project Plan for PBPK models (U.S. EPA. 2018d).
which is summarized in Section 6.4.
6.1. STUDY EVALUATION OVERVIEW FOR HEALTH EFFECT STUDIES
The IRIS Program uses a domain-based approach to evaluate studies. Key concerns for the
review of epidemiology and animal toxicology studies are potential bias (factors that affect the
magnitude or direction of an effect in either direction) and insensitivity (factors that limit the
ability of a study to detect a true effect; low sensitivity is a bias toward the null when an effect
exists). The study evaluations are aimed at discerning the expected magnitude of any identified
limitations (focusing on limitations that could substantively change a result), considering the
expected direction of the bias. The study evaluation approach is designed to address a range of
study designs, health effects, and chemicals. The general approach for reaching an overall judgment
regarding confidence in the reliability of the results is illustrated in Figure 6-1.
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(a) Individual evaluation domains
Epidemiology
Animal
In vitro
Exposure measurement
Reporting quality
Reporting quality
Outcome ascertainment
Allocation
Observational bias/blinding
Participant selection
Observational bias/blinding
Variable control
Confounding
Confounding
Specificity
Analysis
Selective reporting and attrition
Selective reporting
Selective reporting
Chemical administration and
Chemical administration and
Sensitivity
characterization
characterization
Exposure timing, frequency, and
Exposure timing, frequency, and
duration
duration
Endpoint sensitivity and specificity
Endpoint sensitivity
Results presentation
Results presentation and analysis
(b) Domain level judgments and overall study rating
Domain judgments
Judgment
Interpretation
0 Good
Appropriate study conduct relating to the domain and minor
deficiencies not expected to influence results.
Adequate
A study that may have some limitations relating to the domain, but
they are not likely to be severe or to have a notable impact on results.
9
Deficient
Identified biases or deficiencies interpreted as likely to have had a
notable impact on the results or prevent reliable interpretation of
study findings.
ฎ Critically
Deficient
A serious flaw identified that makes the observed effect(s)
uninterpretable. Studies with a critical deficiency are considered
"uninformative" overall.
Overall study rating for an outcome
Rating
Interpretation
High
Medium
No notable deficiencies or concerns identified; potential for bias
unlikely or minimal; sensitive methodology.
Possible deficiencies or concerns noted but they are unlikely to have a
significant impact on results.
Low
Uninformative
Deficiencies or concerns were noted, and the potential for substantive
bias or inadequate sensitivity could have a significant impact on the
study results or their interpretation.
Serious flaw(s) makes study results uninterpretable but may be used
to highlight possible research gaps.
Figure 6-1. Overview of Integrated Risk Information System (IRIS) study
evaluation approach, (a) individual evaluation domains organized by evidence
type, and (b) individual evaluation domains, judgments, and definitions for overall
ratings (i.e., domain and overall judgments are performed on an outcome-specific
basis}.
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To calibrate the assessment specific considerations, the study evaluation process includes a
pilot phase to assess and refine the evaluation process. Following this pilot, at least two reviewers
independently evaluate studies to identify characteristics that bear on the informativeness
(i.e., validity and sensitivity) of the results. The independent reviewers use structured web-forms
for study evaluation housed within EPA's version of HAWC fhttps://hawc.prd.epa.govl to record
separate judgments for each domain and the overall study for each outcome and unit of analysis, to
reach consensus between reviewers, and when necessary, resolve differences by discussion
between the reviewers or consultation with additional independent reviewers. As reviewers
examine a group of studies, additional chemical specific knowledge or methodological concerns
could emerge, and a second pass of all pertinent studies might become necessary.
In general, considerations for reviewing a study with regard to its conduct for specific
health outcomes are based on considerations presented in the IRIS Handbook fU.S. EPA. 20221 and
use of existing guideline documents when available, including EPA guidelines for carcinogenicity,
neurotoxicity, reproductive toxicity, and developmental toxicity fU.S. EPA. 2005a. 1998a. 1996.
19911.
Authors might be queried to obtain critical information, particularly that involving missing
key study design, results information, or additional analyses that could address potential study
limitations. During study evaluation, the decision on whether to seek missing information focuses
on information that could result in a reevaluation of the overall study confidence for an outcome.
Outreach to study authors is documented in HAWC and considered unsuccessful if researchers do
not respond to an email or phone request within one month. Only information or data that can be
made publicly available (e.g., within HAWC or HERO) will be considered.
When evaluating studies that examine more than one outcome, the evaluation process is
explicitly conducted at the individual outcome level within the study. Thus, the same study may
have different outcome domain judgments for different outcomes. These measures could still be
grouped for evidence synthesis.
During review, for each evaluation domain, reviewers reach a consensus judgment of good,
adequate, deficient, not reported, or critically deficient. If a consensus is not reached, a third
reviewer performs conflict resolution. It is important to emphasize that evaluations are performed
in the context of the study's utility for identifying individual hazards. Limitations specific to the
usability of the study for dose-response analysis are useful to note and applicable to selecting
studies for that purpose (see Section 9), but they do not contribute to the study confidence
classifications. These four categories are applied to each evaluation domain for each outcome
considered within a study, as follows:
Good represents a judgment that the study was conducted appropriately in relation to the
evaluation domain, and any minor deficiencies noted are not expected to influence the
study results or interpretation of the study findings.
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Adequate indicates a judgment that methodological limitations related to the evaluation
domain are (or are likely to be) present, but those limitations are unlikely to be severe or to
notably impact the study results or interpretation of the study findings.
Deficient denotes identified biases or deficiencies interpreted as likely to have had a notable
impact on the results, or that limit interpretation of the study findings.
Not reported indicates the information necessary to evaluate the domain question was not
available in the study. Depending on the expected impact, the domain may be interpreted as
adequate or deficient for the purposes of the study confidence rating.
Critically deficient reflects a judgment that the study conduct relating to the evaluation
domain introduced a serious flaw that is interpreted to be the primary driver of any
observed effect(s) or makes the study uninterpretable. Studies with critically deficient
judgments in any evaluation domain are almost always classified as overall uninformative
for the relevant outcome (s).
Once the evaluation domains are rated, the identified strengths and limitations are
considered collectively to reach a study confidence classification of high, medium, or low confidence,
or uninformative for each specific health outcome(s). This classification is based on the reviewer
judgments across the evaluation domains and considers the likely impact that the noted
deficiencies in bias and sensitivity have on the outcome-specific results. There are no pre-defined
weights for the domains, and the reviewers are responsible for applying expert judgment to make
this determination. The study confidence classifications, which reflect a consensus judgment
between reviewers, are defined as follows:
High confidence: No notable deficiencies or concerns were identified; the potential for bias
is unlikely or minimal, and the study used sensitive methodology. High confidence studies
generally reflect judgments of good across all or most evaluation domains.
Medium confidence: Possible deficiencies or concerns were identified, but the limitations
are unlikely to have a significant impact on the study results or their interpretation.
Generally, medium confidence studies include adequate or good judgments across most
domains, with the impact of any identified limitation not being judged as severe.
Low confidence: Deficiencies or concerns are identified, and the potential for bias or
inadequate sensitivity is expected to have a significant impact on the study results or their
interpretation. Typically, low confidence studies have a deficient evaluation for one or more
domains, although some medium confidence studies might have a deficient rating in
domain(s) considered to have less influence on the magnitude or direction of effect
estimates. Low confidence results are given less weight compared to high or medium
confidence results during evidence synthesis and integration (see Sections 7 and 8) and are
generally not used as the primary sources of information for hazard identification or
derivation of toxicity values unless they are the only studies available (in which case, this
significant uncertainty would be emphasized during dose-response analysis). Studies rated
low confidence only because of sensitivity concerns are asterisked or otherwise noted
because they often require additional consideration during evidence synthesis. Effects
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observed in studies that are biased toward the null may increase confidence in the results,
assuming the study is otherwise well conducted (see Section 8).
Uninformative: Serious flaw(s) are judged to make the study results uninterpretable for use
in the assessment. Studies with critically deficient judgments in any evaluation domain are
almost always rated uninformative. Studies with multiple deficient judgments across
domains may also be considered uninformative. Given that the findings of interest are
considered uninterpretable based on the identified flaws (see above definition of critically
deficient) and do not provide information of use to assessment interpretations, these
studies have no impact on evidence synthesis or integration judgments and are not useable
for dose-response analyses but may be used to highlight research gaps.
As previously noted, study evaluation determinations reached by each reviewer and the
consensus judgment between reviewers are recorded in HAWC. Final study evaluations housed in
HAWC are made available when the draft is publicly released. The study confidence classifications
and their rationales are carried forward and considered as part of evidence synthesis (see
Section 11) to help interpret the results across studies.
6.2. EPIDEMIOLOGY STUDY EVALUATION
Evaluation of epidemiology studies of health effects to assess risk of bias and study
sensitivity are conducted for the following domains: exposure measurement, outcome
ascertainment, participant selection, potential confounding, analysis, study sensitivity, and selective
reporting. Bias can result in false positives and negatives (i.e., Types I and II errors), whereas study
sensitivity is typically concerned with identifying the latter.
The principles and framework used for evaluating epidemiology studies are adapted from
the principles in the Cochrane Risk of Bias in Nonrandomized Studies of Interventions [ROBINS-I;
Sterne etal. (2016)] but modified to address environmental and occupational exposures. The types
of information that may be the focus of those criteria are listed in Table 6-1. Core and prompting
questions, presented in Table 6-2, are used to collect information to guide evaluation of each
domain. Core questions represent key concepts while the prompting questions help the reviewer
focus on relevant details under each key domain. Exposure- and outcome-specific criteria to use
during study evaluation are developed using the core and prompting questions and refined during a
pilot phase with engagement from topic-specific experts. The protocol may also be adjusted in the
early phases of the study evaluation process if corrections are identified based on initial literature
reviews. Exposure domain considerations specific to naphthalene are presented in Sections 6.2.1 to
6.2.2.
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Table 6-1. Information relevant to evaluation domains for epidemiology
studies
Domain
Types of information that may need to be collected or are important for evaluating
the domain
Exposure
measurement
Source(s) of exposure (e.g., consumer products, occupational, an industrial accident) and
source(s) of exposure data, blinding to outcome, level of detail for job history data, when
measurements were taken, type of biomarker(s), assay information, reliability data from
repeated-measures studies, validation studies.
Outcome
ascertainment
Source of outcome (effect) measure, blinding to exposure status or level, how
measured/classified, incident vs. prevalent disease, evidence from validation studies, prevalence
(or distribution summary statistics for continuous measures).
Participant
selection
Study design, where and when was the study conducted, and who was included? Recruitment
process, exclusion and inclusion criteria, type of controls, total eligible, comparison between
participants and nonparticipants (or followed and not followed), and final analysis group. Does
the study include potential susceptible populations or life stages? (See discussion in Section 9.)
Confounding
Background research on key confounders for specific populations or settings; participant
characteristic data, by group; strategy/approach for consideration of potential confounding;
strength of associations between exposure and potential confounders and between potential
confounders and outcome; and degree of exposure to the confounder in the population.
Analysis
Extent (and if applicable, treatment) of missing data for exposure, outcome, and confounders;
approach to modeling; classification of exposure and outcome variables (continuous vs.
categorical); testing of assumptions; sample size for specific analyses; and relevant sensitivity
analyses.
Sensitivity
What are the ages of participants (e.g., not too young in studies of pubertal development)? What
is the length of follow-up (for outcomes with long latency periods)? Choice of referent group, the
exposure range, and the level of exposure contrast between groups (i.e., the extent to which the
"unexposed group" is truly unexposed, and the prevalence of exposure in the group designated
as "exposed").
Selective
reporting
Are results presented with adequate detail for all the endpoints and exposure measures
reported in the methods section, and are they relevant to the PECO? Are results presented for
the full sample as well as for specified subgroups? Were stratified analyses (effect modification)
motivated by a specific hypothesis?
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Table 6-2. Questions to guide the development of criteria for each domain in epidemiology studies
Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Exposure
measurement
Does the
exposure
measure
reliably
distinguish
between levels
of exposure in
a time window
considered
most relevant
for a causal
effect with
respect to the
development
of the
outcome?
For all:
Does the exposure measure capture the
variability in exposure among the participants,
considering intensity, frequency, and duration of
exposure?
Does the exposure measure reflect a relevant
time window? If not, can the relationship
between measures in this time and the relevant
time window be estimated reliably?
Is the exposure measurement likely to be
affected by a knowledge of the outcome?
Is the exposure measurement likely to be
affected by the presence of the outcome
(i.e., reverse causality)?
For case-control studies of occupational exposures:
Is exposure based on a comprehensive job history
describing tasks, setting, time period, and use of
specific materials?
For biomarkers of exposure, general population:
Is a standard assay used? What are the intra- and
inter-assay coefficients of variation? Is the assay
likely to be affected by contamination? Are values
less than the limit of detection dealt with
adequately?
What exposure time period is reflected by the
biomarker? If the half-life is short, what is the
correlation between serial measurements of
exposure?
Is the degree of
exposure
misclassification
likely to vary by
exposure level?
If the correlation
between
exposure
measurements is
moderate, is
there an
adequate
statistical
approach to
ameliorate
variability in
measurements?
If there is a
concern about
the potential for
bias, what is the
predicted
direction or
distortion of the
bias on the effect
estimate (if there
is enough
information)?
These considerations require customization to the exposure and outcome
(relevant timing of exposure).
Good
Valid exposure assessment methods used, which represent the etiologically
relevant time period of interest.
Exposure misclassification is expected to be minimal.
Adequate
Valid exposure assessment methods used, which represent the etiologically
relevant time period of interest.
Exposure misclassification may exist but is not expected to greatly change
the effect estimate.
Deficient
Valid exposure assessment methods used, which represent the etiologically
relevant time period of interest. Specific knowledge about the exposure and
outcome raise concerns about reverse causality, but there is uncertainty
about whether it is influencing the effect estimate.
Exposed groups are expected to contain a notable proportion of unexposed
or minimally exposed individuals, the method did not capture important
temporal or spatial variation, or there is other evidence of exposure
misclassification that would be expected to notably change the effect
estimate.
Critically deficient
Exposure measurement does not characterize the etiologically relevant time
period of exposure or is not valid.
There is evidence that reverse causality is very likely to account for the
observed association.
Exposure measurement was not independent of outcome status.
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Outcome
ascertainment
Does the
outcome
measure
reliably
distinguish the
presence or
absence(or
degree of
severity) of the
outcome?
For all:
Is outcome ascertainment likely to be affected by
knowledge of, or presence of, exposure
(e.g., consider access to health care, if based on
self-reported history of diagnosis)?
For case-control studies:
Is the comparison group without the outcome
(e.g., controls in a case-control study) based on
objective criteria with little or no likelihood of
inclusion of people with the disease?
For mortality measures:
How well does cause-of-death data reflect
occurrence of the disease in an individual? How
well do mortality data reflect incidence of the
disease?
For diagnosis of disease measures:
Is the diagnosis based on standard clinical
criteria? If it is based on self-report of the
diagnosis, what is the validity of this measure?
For laboratory-based measures (e.g., hormone levels):
Is a standard assay used? Does the assay have an
acceptable level of inter-assay variability? Is the
sensitivity of the assay appropriate for the
outcome measure in this study population?
Is there a concern
that any outcome
misclassification
is nondifferential,
differential, or
both?
What is the
predicted
direction or
distortion of the
bias on the effect
estimate (if there
is enough
information)?
These considerations require customization to the outcome.
Good
High certainty in the outcome definition (i.e., specificity and sensitivity),
minimal concerns with respect to misclassification.
Assessment instrument is validated in a population comparable to the one
from which the study group was selected.
Adequate
Moderate confidence that outcome definition was specific and sensitive,
some uncertainty with respect to misclassification but not expected to
greatly change the effect estimate.
Assessment instrument is validated but not necessarily in a population
comparable to the study group.
Deficient
Outcome definition was not specific or sensitive.
Uncertainty regarding validity of assessment instrument.
Critically deficient
Invalid/insensitive marker of outcome.
Outcome ascertainment is very likely to be affected by knowledge of, or
presence of, exposure.
Note: Lack of blinding should not be automatically construed to be critically
deficient.
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Participant
selection
Is there
evidence that
selection into
or out of the
study (or
analysis
sample) is
jointly related
to exposure
and to
outcome?
For longitudinal cohort:
Did participants volunteer for the cohort based
on knowledge of exposure and/or preclinical
disease symptoms? Was entry into the cohort or
continuation in the cohort related to exposure
and outcome?
For occupational cohort:
Did entry into the cohort begin with the start of
the exposure?
Was follow-up or outcome assessment
incomplete, and if so, was follow-up related to
both exposure and outcome status?
Could exposure produce symptoms that would
result in a change in work assignment/work
status ("healthy worker survivor effect")?
For case-control study:
Were controls representative of population and
time periods from which cases were drawn?
Are hospital controls selected from a group
whose reason for admission is independent of
exposure?
Could recruitment strategies, eligibility criteria, or
participation rates result in differential
participation relating to both disease and
exposure?
Are differences in
participant
enrollment and
follow-up
evaluated to
assess bias?
If there is a
concern about
the potential for
bias, what is the
predicted
direction or
distortion of the
bias on the effect
estimate (if there
is enough
information)?
Are appropriate
analyses
performed to
address changing
exposures over
time in relation to
symptoms?
Is there a
comparison of
participants and
nonparticipants
to address
whether
differential
selection is likely?
These considerations may require customization to the outcome. This could
include determining what study designs effectively allow analyses of associations
appropriate to the outcome measures (e.g., design to capture incident vs.
prevalent cases, design to capture early pregnancy loss).
Good
Minimal concern for selection bias based on description of recruitment
process (e.g., selection of comparison population, population-based random
sample selection, recruitment from sampling frame including current and
previous employees).
Exclusion and inclusion criteria are specified and do not induce bias.
Participation rate is reported at all steps of study (e.g., initial enrollment,
follow-up, selection into analysis sample). If rate is not high, there is
appropriate rationale for why it is unlikely to be related to exposure
(e.g., comparison between participants and nonparticipants or other
available information indicates differential selection is not likely).
Adequate
Enough of a description of the recruitment process to be comfortable that
there is no serious risk of bias.
Inclusion and exclusion criteria are specified and do not induce bias.
Participation rate is incompletely reported but available information
indicates participation is unlikely to be related to exposure.
Deficient
Little information on recruitment process, selection strategy, sampling
framework and/or participation or aspects of these processes raise the
potential for bias (e.g., healthy worker effect, survivor bias).
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Continued:
Continued:
For population-based survey:
Was recruitment based on advertisement to
people with knowledge of exposure, outcome,
and hypothesis?
Continued:
Continued:
Critically deficient
Aspects of the processes for recruitment, selection strategy, sampling
framework, or participation result in concern that selection bias resulted in a
large impact on effect estimates (e.g., convenience sample with no
information about recruitment and selection, cases and controls are
recruited from different sources with different likelihood of exposure,
recruitment materials stated outcome of interest, and potential participants
are aware of or are concerned about specific exposures).
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Confounding
Is confounding
of the effect of
the exposure
likely?
Is confounding adequately addressed by
considerations in:
Participant selection (matching or restriction)?
Accurate information on potential confounders
and statistical adjustment procedures?
Lack of association between confounder and
outcome, or confounder and exposure in the
study?
Information from other sources?
Is the assessment of confounders based on a
thoughtful review of published literature, potential
relationships (e.g., as can be gained through directed
acyclic graphing), and minimizing potential overcontrol
(e.g., inclusion of a variable on the pathway between
exposure and outcome)?
If there is a
concern about
the potential for
bias, what is the
predicted
direction or
distortion of the
bias on the effect
estimate (if there
is enough
information)?
These considerations require customization to the exposure and outcome, but
this may be limited to identifying key covariates.
Good
Conveys strategy for identifying key confounders. This may include a priori
biological considerations, published literature, causal diagrams, or statistical
analyses; with recognition that not all "risk factors" are confounders.
Inclusion of potential confounders in statistical models not based solely on
statistical significance criteria (e.g., p < 0.05 from stepwise regression).
Does not include variables in the models that are likely to be influential
colliders or intermediates on the causal pathway.
Key confounders are evaluated appropriately and considered to be unlikely
sources of substantial confounding. This often will include:
o Presenting the distribution of potential confounders by levels of the
exposure of interest and/or the outcomes of interest (with amount
of missing data noted),
o Consideration that potential confounders are rare among the study
population or are expected to be poorly correlated with exposure
of interest,
o Consideration of the most relevant functional forms of potential
confounders, and
o Examination of the potential impact of measurement error or
missing data on confounder adjustment.
Adequate
Similar to good but may not have included all key confounders, or
less detail may be available on the evaluation of confounders
(e.g., subbullets in good). It is possible that residual confounding
could explain part of the observed effect, but concern is minimal.
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Continued:
Continued:
Continued:
Continued:
Deficient
Does not include variables in the models that are likely to be influential
colliders or intermediates on the causal pathway.
And any of the following:
The potential for bias to explain some of the results is high based on an
inability to rule out residual confounding, such as a lack of demonstration
that key confounders of the exposure-outcome relationships are considered;
Descriptive information on key confounders (e.g., their relationship relative
to the outcomes and exposure levels) is not presented; or
Strategy of evaluating confounding is unclear or is not recommended
(e.g., only based on statistical significance criteria or stepwise regression
[forward or backward elimination]).
Critically deficient
Includes variables in the models that are colliders and/or intermediates in
the causal pathway, indicating that substantial bias is likely from this
adjustment, or
Confounding is likely present and not accounted for, indicating that all of the
results are most likely due to bias.
o Presenting a progression of model results with adjustments for
different potential confounders, if warranted.
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Analvsis
Does the
analysis
strategy and
presentation
convey the
necessary
familiarity with
the data and
assumptions?
Are missing outcome, exposure, and covariate
data recognized, and if necessary, accounted for
in the analysis?
Does the analysis appropriately consider variable
distributions and modeling assumptions?
Does the analysis appropriately consider
subgroups of interest (e.g., based on variability in
exposure level or duration or susceptibility)?
Is an appropriate analysis used for the study
design?
Is effect modification considered, based on
considerations developed a priori?
Does the study include additional analyses
addressing potential biases or limitations
(i.e., sensitivity analyses)?
If there is a
concern about
the potential for
bias, what is the
predicted
direction or
distortion of the
bias on the effect
estimate (if there
is enough
information)?
These considerations may require customization to the outcome. This could
include the optimal characterization of the outcome variable and ideal statistical
test (e.g., Cox regression).
Good
Use of an optimal characterization of the outcome variable.
Quantitative results are presented (effect estimates and confidence limits or
variability in estimates) (i.e., not presented only as a p-value or
"significant"/"not significant").
Descriptive information about outcome and exposure is provided (where
applicable).
Amount of missing data is noted and addressed appropriately (discussion of
selection issuesmissing at random vs. differential).
Where applicable, for exposure, includes LOD (and percentage below the
LOD), and decision to use log transformation.
Includes analyses that address robustness of findings, e.g., examination of
exposure-response (explicit consideration of nonlinear possibilities,
quadratic, spline, or threshold/ceiling effects included, when feasible);
relevant sensitivity analyses; effect modification examined based only on
a priori rationale with sufficient numbers.
No deficiencies in analysis evident. Discussion of some details may be absent
(e.g., examination of outliers).
Adequate
Same as good, except:
Descriptive information about exposure is provided (where applicable) but
may be incomplete; might not have discussed missing data, cutpoints, or
shape of distribution.
Includes analyses that address robustness of findings (examples in good), but
some important analyses are not performed.
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Continued:
Continued:
Continued:
Continued:
Deficient
Does not conduct analysis using optimal characterization of the outcome
variable.
Descriptive information about exposure levels is not provided (where
applicable).
Effect estimate and p-value are presented, without standard error or
confidence interval.
Results are presented as statistically "significant"/"not significant."
Critically deficient
Results of analyses of effect modification are examined without clear a priori
rationale and without providing main/principal effects (e.g., presentation
only of statistically significant interactions that were not hypothesis driven).
Analysis methods are not appropriate for design or data of the study.
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Selective
reporting
Is there reason
to be
concerned
about selective
reporting?
Are results provided for all the primary analyses
described in the methods section?
Is there appropriate justification for restricting
the amount and type of results that are shown?
Are only statistically significant results presented?
If there is a
concern about
the potential for
bias, what is the
predicted
direction or
distortion of the
bias on the effect
estimate (if there
is enough
information)?
These considerations generally do not require customization and might have
fewer than four levels.
Good
The results reported by study authors are consistent with the primary and
secondary analyses described in a registered protocol or methods paper.
Adequate
The authors described their primary (and secondary) analyses in the
methods section and results are reported for all primary analyses.
Deficient
Concerns are raised based on previous publications, a methods paper, or a
registered protocol indicating that analyses are planned or conducted that
are not reported, or that hypotheses originally considered to be secondary
are represented as primary in the reviewed paper.
Only subgroup analyses are reported, suggesting that results for the entire
group are omitted.
Only statistically significant results are reported.
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Sensitivity
Is there a
concern that
sensitivity of
the study is not
adequate to
detect an
effect?
Is the exposure range adequate to detect
associations and exposure-response
relationships?
Was the appropriate population included?
Was the length of follow-up adequate? Is the
time/age of outcome ascertainment optimal
given the interval of exposure and the health
outcome?
Are there other aspects related to risk of bias or
otherwise that raise concerns about sensitivity?
These considerations may require customization to the exposure and outcome.
Depending on the needs of the assessment, there may be fewer than four rating
levels. Some study features that affect study sensitivity may have already been
included in the other evaluation domains; these should be noted in this domain
again, along with any features that have not been addressed elsewhere so that
the rating provides an overall summary of factors that may impact sensitivity.
When determining the overall study confidence rating, the evaluator should be
conscious that a limitation could contribute to multiple domains and not
double-penalize the study. Some considerations include:
Good
The range of exposure levels provides sufficient variability in exposure
distribution and/or sufficient range or contrasts (e.g., across groups or
exposure categories) to detect associations or exposure-response
relationships that may be present.
The population was exposed to levels expected to have an impact on
response.
The study population was at risk of developing the outcomes of interest
(e.g., ages, life stage, sex).
The timing of outcome ascertainment was appropriate given expected
latency for outcome development (i.e., adequate follow-up interval).
There was evidence of sufficient statistical power (which may include formal
power calculations) to observe an effect if one exists.
No other concerns raised regarding study sensitivity (e.g., no evidence that
results would be attenuated enough to preclude detection of an adverse
health effect).
Adequate
Same considerations as good, except:
o Issues are identified that could reduce sensitivity, but they are
unlikely to impact the overall findings of the study.
Deficient
Concerns were raised about the issues described for good that are expected
to notably decrease the sensitivity of the study to detect associations for the
outcome (i.e., reasonably high likelihood of a false null result).
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Domain and
core question
Prompting questions
Follow-up
questions
Considerations that apply to most exposures and outcomes
Note: Deficient sensitivity indicates that null findings should be interpreted
with caution and may not represent a lack of association.
Critically deficient
Severe concerns were raised about the sensitivity of the study such that any
observed association is uninterpretable (e.g., exposure gradients/contrasts
that precluded an ability to distinguish exposure levels between study
participants).
1
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For evaluation of the exposure measures domain, studies in which human exposure is
quantified in the air or in urinary biomarker measurements will be preferred. Studies where
naphthalene exposure is inferred but not confirmed by quantitative measurements will be given
lower preference. Studies that only use measurements of JP-8 jet fuel rather than naphthalene alone
in regression analyses will be marked as potentially relevant supplemental material, given the
concerns with confounding due to the diverse components of the jet fuel.
6.2.1. Air monitoring or modeling
Naphthalene can exist in both the vapor and particulate phases, but more than 95% is
anticipated to occur in the vapor phase fLai etal.. 2009: Eiguren-Fernandez etal.. 2004: Fangetal..
2004: Harrison et al.. 19961. The half-life of naphthalene in the atmosphere is less than 1 day
fATSDR. 20051: specific data about the half-life in indoor environments were not identified but
would depend on concentrations of hydroxyl radicals present fATSDR. 20051. Naphthalene
concentrations may be higher in indoor air than outdoor air due to certain exposure sources, such
as mothballs or paint (WHO. 2010: ATSDR. 20051. In these situations where indoor sources are
expected to dominate, measurement of naphthalene concentrations in indoor air is preferred over
outdoor air estimates alone. In general, however, due to the relevance of both indoor and outdoor
sources, individual-level exposure assessments for health effects studies ideally would capture
contributions from time at home, school or work, and in-transit. For this reason, individual-level or
time-weighted summaries are preferred over area-level monitoring that does not incorporate
individual movement/behaviors and the potential contribution of multiple sources.
The effectiveness of air monitoring for naphthalene depends on the approach (active vs.
passive) and the sorbent utilized. Passive sampling approaches require long sampling times in
situations with low PAH concentrations and low sensitivity of analytical methods. With regard to
sorbent, the U.S. EPA Compendium Method TO-13A for PAHs (including naphthalene) in ambient
air allows for either a polyurethane (PUF) or XAD-2 adsorbent cartridge fU.S. EPA. 19991. However,
PUF has a lower recovery efficiency for naphthalene and may result in an underestimate of airborne
concentrations, particularly with passive sampling (Strandberg etal.. 2018: Chuang etal.. 19871.
Therefore, XAD-2 active sampling is the preferred method for naphthalene sampling (Pineiro etal..
20211. Additional methods are described in (EIC. 20151.
The time frame represented by the exposure estimates should correspond to the period in
which the health outcomes were expected to have developed. Indoor exposure assessments
representing a period of week(s) in more than one season could reasonably characterize average
exposure over the previous year and would be relevant to immune-related or other symptoms (e.g.,
asthma, wheezing illness, allergy symptoms, sensoiy irritation) occurring over the previous several
weeks to a year. Daily sampling is best, but periodic sampling on a less than daily basis could be
sufficient depending on the variability in air concentrations. Shorter duration monitoring could be
relevant for acute outcomes. Developmental outcomes should be evaluated in relation to the
relevant critical exposure periods during pregnancy if they are known. Exposure measurements
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with shorter time frames are less informative for studying the prevalence or incidence of chronic
disease, such as physician-diagnosed asthma, cardiovascular disease, or cancer.
There has been limited use of modeling (e.g., land use regression (LUR)) to assess exposure
to naphthalene fLu etal.. 20191. Primary concerns with these approaches are that they only capture
potential outdoor sources of exposure and there is uncertainty regarding their validity or reliability
given the lack of a robust literature base. As such, decisions regarding the appropriateness of
modeling approaches will be made on a case-by-case basis based on the description of model
development and how adequately the model characterizes spatial variation in the community.
6.2.2. Biomarker assessment
Urinary
When biomarkers of exposure are used to identify the presence of naphthalene,
monohydroxylated metabolites of naphthalene are preferred. Alternative metabolites, such as
dihydroxy urinary metabolites of naphthalene, are more challenging to quantify and analyze with
current capabilities (Klotz etal.. 20111 but may be more reliable in the future. With regard to
monohydroxylated metabolites, studies measuring 2-naphthol are preferred versus studies
measuring 1-naphthol only. 1-Naphthol is a metabolite of both naphthalene and the pesticide
carbaryl (one of the most commonly used insecticides in home and garden settings, with
widespread low-level exposure expected across the population), and therefore is a less specific
biomarker of naphthalene exposure compared to 2-naphthol. Measurement of 1-naphthol may be
appropriate if the study uses approaches to distinguish between source (e.g., naphthalene vs.
carbaryl) (Meeker et al.. 20071. Naphthalene metabolites measured in urine may reflect internal
dose and can be utilized as sensitive biomarkers of exposure if specific metabolites are measured in
relation to etiologically relevant periods. However, because the half-life of naphthalene in the body
is short [4 hours fATSDR. 20051] and the metabolites are excreted rapidly, there are temporal
variations in urinary metabolite levels relative to the timeframe of exposure. A single spot urine
sample therefore may not be a reliable surrogate for longer-term exposure. This question of
reproducibility of biomarker measures over time has been discussed for other environmental
exposures, such as phthalates (Radke etal.. 2018: Tohns etal.. 20151. The intraclass correlation
coefficient (ICC), a measure of reliability, for naphthalene metabolites in urine has been reported in
a variety of populations and in a variety of settings as approximately 0.3-0.7 fZhu etal.. 2021:
Cathev et al.. 2018: Dobraca etal.. 2018: Yang etal.. 2017a: Wheeler etal.. 2014: Li etal.. 20101.
though poorer reproducibility has also been reported (Yang etal.. 2017b). While 2-naphthol is a
more specific marker of naphthalene exposure, it sometimes - but not always - has a lower ICC
than 1-naphthol in a sample of examined studies. If results are available for both metabolites,
consistent patterns across both would provide more confidence in drawing conclusions. Overall,
use of a single spot sample to reflect longer term exposure is likely to induce non-differential
exposure misclassification into the analysis (which, in most cases, would produce bias towards the
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null). Use of pooled samples over multiple days is preferred over a spot sample from a single day
fPerrier etal.. 20161.
Overall, judgement of the adequacy of a spot urine sample depends in part upon whether
the exposure source is expected to be consistent over time and whether the sample falls within the
etiologically relevant time period. There is more concern regarding the appropriateness of spot
samples for chronic compared to acute outcomes. General guidelines are provided in the table
below.
Nonurinary
Most studies evaluating PAH exposure, such as naphthalene, measure the concentration of
PAH metabolites in urine, as PAHs are metabolized rapidly in the body fYin etal.. 20171. Other
potential biomarkers of exposure include umbilical cord blood, breast milk, and placenta tissue;
however, there is currently limited information on the usefulness of these measures as exposure
biomarkers for naphthalene in epidemiological research (Powers. 20221. Combined with the short
elimination half-life of naphthalene in the body, biomarkers other than urine will be rated as
critically deficient.
Additionally, some studies have used unmetabolized PAHs to measure body burden fDe
Craemer etal.. 20161. Because of the short half-life of PAH parent compounds, the appropriate
quantification approach is to measure metabolites. Therefore, studies attempting to quantify
naphthalene burden through assessment of the parent compound only will be rated critically
deficient.
Table 6-3. Evaluation of exposure biomarkers in general population studies of
naphthalene (adapted from Phthalates SR protocol) fRadke et al.. 20181
Level
Criteria
Biomarkers
Air
Good
Two or more urine samples within the
etiologically relevant period [i.e.,
temporality is established, and
sufficient latency occurred before
disease onset] for development of the
outcome based on current biological
understanding)
and
Measurement of 2-naphthol
metabolites in urine
and
Discussion of laboratory QC
procedures or no discussion of
laboratory QC procedures but analysis
Integrated personal measurements or time-
weighted summary concentrations
incorporating concentrations in residence and
school/workplace
and
Appropriate and validated methods used for
sampling (e.g., NMAM 5528, T013A, XAD) and
analysis (e.g., GC/MS, HPLC). Sampling details
provided (e.g., type of samplers, placement of
samplers, sampling periods, status of activities
in structures, chemical analysis methods (or
citation provided). Validation with paired tests
to ensure consistency. Calibration of
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Level
Criteria
Biomarkers
Air
by an experienced laboratory (e.g.,
Centers for Disease Control and
Prevention [CDC])
automated instruments if relevant. Sufficient
samples above the LOD
and
Time-frame of measurements appropriate to
development of health outcome
Adequate
One urine sample within etiologically
relevant period for development of
outcome
and
Measurement of 2-naphthol
metabolites in urine or measurement
of 1-naphthol with methods to
distinguish original source
and
Evidence that exposure was
consistently assessed using
methods described in Good, but
there were some concerns about
quality control measures or other
potential for nondifferential
misclassification
Area measurements in home, average of
measurements in 1 or more rooms; over
multiple seasons if estimating annual average
and
Appropriate and validated methods used (e.g.,
NMAM 5528, XAD) and analysis (e.g., GC/MS,
HPLC). Sufficient samples above the LOD.
Sampling details provide adequate level of
confidence in approach, though less detailed
provided than for "Good" above
and
Time-frame of measurements appropriate to
development of health outcome
Or
Average estimates based on land use
regression models developed for location
where study was conducted including
description of model development and
sufficient information about how the model
adequately characterizes spatial variation in
the community. Potentially other methods
besides LUR might fall into this category if
detailed validation information was provided
to ensure model adequately characterizes
spatial variation
and
Time-frame of modeling relevant to the
development of health outcome
Deficient
One urine sample; sample collection
may be outside the etiologically
relevant period and/or there is some
concern for reverse causation
For monitoring:
Monitoring with PUF adsorbent cartridge, or
an approach that may not be fully appropriate
or validated
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Level
Criteria
Biomarkers
Air
Or Measurement of 1-naphthol
metabolites in urine without methods
to account for original source
or
Concerns with QC/QA
Monitoring of outdoor air concentrations only
if indoor sources are expected to dominate
Area measurements in home obtained on one
occasion but study is estimating annual
average
Or
For modeling:
Average estimates based on land use
regression models developed for location
where study was conducted, but some
uncertainties remain regarding how the model
was developed or how the model adequately
characterizes spatial variation in the
community due to what was known about
sources
Estimates based on other modeling
approaches (e.g., NATA, CMAQ) with more
limited ability to accurately capture
spatial/temporal variation
Or
Use of questionnaires or observations of
sources in the home by trained study
personnel
Critically
Deficient
Biomarker measured in tissue other
than urine
or
Clear concern for reverse causation
would make the results
uninterpretable
No explanation or insufficient detail provided
about air monitoring or modeling methods
Air monitoring or modeling occurred outside
of a relevant window for health outcome of
interest
Use of air monitoring approach that has not
been validated for naphthalene or does not
sufficiently capture spatial/temporal variation
Technical issues during monitoring (e.g.,
inconsistency during sampling, pump faults
from overloading)
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6.3. EXPERIMENTAL ANIMAL STUDY EVALUATION
The evaluation of experimental animal studies applies similar principles as those described
above for the evaluation of epidemiology studies. The evaluation process focuses on assessing
aspects of the study design and conduct through three broad types of evaluations: reporting quality,
risk of bias, and study sensitivity. A set of domains with accompanying core questions fall under
each evaluation type and direct individual reviewers to evaluate specific study characteristics. For
each domain and core question pairing, basic considerations provide additional guidance on how a
reviewer might evaluate and judge a study for that domain.
Table 6-3 provides the standard domains and core questions along with some basic
considerations for guiding the evaluation. Each domain receives a consensus judgment of Good,
Adequate, Deficient, Not Reportedor Critically Deficient (as described in Section 6.1) accompanied
by a rationale for the judgment. Once all domains are rated, an overall confidence classification of
High, Medium, or Low confidence or Uninformative is assigned (as described in Section 6.1). The
rationale for the classification, including a brief description of any identified strengths and/or
limitations from the domains and their potential impact on the overall confidence determination,
should be documented clearly and consistently. This rationale should, to the extent possible, reflect
an interpretation of the potential influence on the results (including the direction and/or
magnitude of influence).
This document is a draft for review purposes only and does not constitute Agency policy.
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Table 6-4. Questions to guide the development of criteria for each domain in experimental animal toxicology
studies
Evaluation
type
Domain name -
core question
Prompting questions
Basic considerations
cr
no
c
t
o
Q.
a>
cc
Reporting quality
Does the study report
information for
evaluating the design and
conduct of the study for
the endpoint(s)/
outcome(s) of interest?
Note: Reviewers should
reach out to authors to
obtain missing
information when studies
are considered key for
hazard evaluation and/or
dose-response.
This domain is limited to
reporting. Other aspects
of the exposure methods,
experimental design, and
endpoint evaluation
methods are evaluated
using the domains related
to risk of bias and study
sensitivity.
Does the study report the following?
Critical information necessary to
perform study evaluation:
o Species, test article name, levels
and duration of exposure, route
(e.g., oral, inhalation), qualitative or
quantitative results for at least one
endpoint of interest
Important information for evaluating
the study methods:
o Test animal: strain, sex, source, and
general husbandry procedures
o Exposure methods: source, purity,
method of administration
o Experimental design: frequency of
exposure, animal age, and life stage
during exposure and at
endpoint/outcome evaluation
o Endpoint evaluation methods:
assays or procedures used to
measure the endpoints/outcomes
of interest
These considerations typically do not need to be refined by
assessment teams, although in some instances the important
information may be refined depending on the endpoints/outcomes
of interest or the chemical under investigation.
A judgment and rationale for this domain should be given for the
study. Typically, these will not change regardless of the
endpoints/outcomes investigated by the study. In the rationale,
reviewers should indicate whether the study adhered to GLP,
OECD, or other testing guidelines.
Good: All critical and important information is reported or
inferable for the endpoints/outcomes of interest.
Adequate: All critical information is reported but some
important information is missing. However, the missing
information is not expected to significantly impact the
study evaluation.
Deficient: All critical information is reported but important
information is missing that is expected to significantly
reduce the ability to evaluate the study.
Critically Deficient: Study report is missing any pieces of
critical information. Studies that are Critically Deficient for
reporting are Uninformative for the overall rating and not
considered further for evidence synthesis and integration.
This document is a draft for review purposes only and does not constitute Agency policy.
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Evaluation
Domain name -
type
core question
Prompting questions
Basic considerations
Allocation
For each study:
These considerations typically do not need to be refined by assessment
Were animals
Did each animal or litter have an equal
teams.
assigned to
experimental groups
using a method that
chance of being assigned to any
experimental group (i.e., random
allocation)?
A judgment and rationale for this domain should be given for each
cohort or experiment in the study.
l/>
.5
minimizes selection
bias?
Is the allocation method described?
Good: Experimental groups were randomized, and any specific
randomization procedure was described or inferable (e.g.,
a;
u
E
Aside from randomization, were any
computer-generated scheme). Note: Normalization is not the
(/)
(0
E
steps taken to balance variables
same as randomization (see response for Adequate).
.5
M-
o
V
i-
a
a>
a.
across experimental groups during
allocation?
Adequate: Authors report that groups were randomized but do
not describe the specific procedure used (e.g., "animals were
be
ฆc
c
ro
ฃ
randomized"). Alternatively, authors used a nonrandom
method to control for important modifying factors across
o
+ฆป
l/l
experimental groups (e.g., body-weight normalization).
Not Reported (interpreted as Deficient): No indication of
randomization of groups or other methods (e.g.,
normalization) to control for important modifying factors
across experimental groups.
Critically Deficient: Bias in the animal allocations was reported
or inferable.
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Evaluation
type
Domain name -
core question
Prompting questions
Basic considerations
Observational
bias/blinding
For each endpoint/outcome or grouping of
endpoints/outcomes in a study:
These considerations typically do not need to be refined by the
assessment teams.
lisk of bias
l/>
.5
a.
ฆc
c
Did the study
implement
measures to reduce
observational bias?
Does the study report blinding or
other methods/procedures for
reducing observational bias?
If not, did the study use a design or
approach for which such procedures
can be inferred?
What is the expected impact of failure
to implement (or report
implementation) of these
methods/procedures on results?
Note: It can be useful for teams to identify highly subjective measures of
endpoints/outcomes where observational bias may strongly influence
results prior to performing evaluations.
A judgment and rationale for this domain should be given for each
endpoint/outcome or group of endpoints/outcomes investigated in the
study.
Good: Measures to reduce observational bias were described
(e.g., blinding to conceal treatment groups during endpoint
evaluation; consensus-based evaluations of histopathology
lesions).
Adequate: Methods for reducing observational bias (e.g.,
blinding) can be inferred or were reported but described
incompletely.
ro
ฃ
o
+ฆป
l/l
Not Reported: Measures to reduce observational bias were not
described.
o Interpreted as Adequate: The potential concern for bias
was mitigated based on the use of
automated/computer-driven systems; standard laboratory
kits; relatively simple, objective measures (e.g., body or
tissue weight); or screening-level evaluations of
histopathology.
o Interpreted as Deficient: The potential impact on the
results is major (e.g., outcome measures are highly
subjective).
Critically Deficient: Strong evidence for observational bias that
could have impacted results.
This document is a draft for review purposes only and does not constitute Agency policy.
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Evaluation
Domain name -
type
core question
Prompting questions
Basic considerations
Confounding
For each study:
These considerations may need to be refined by assessment teams, as
Are variables with
Are there differences across the
the specific variables of concern can vary by experiment or chemical.
o
the potential to
confound or modify
results controlled
and consistent
treatment groups (e.g., co-exposures,
vehicle, diet, palatability, husbandry,
health status, etc.) that could bias the
results?
A judgment and rationale for this domain should be given for each
cohort or experiment in the study, noting when the potential for
confounding is restricted to specific endpoints/outcomes.
+-ป
c
across all
If differences are identified, to what
extent are they expected to impact
the results?
Good: Outside of the exposure of interest, variables that are
l/>
.5
<->
o
u
Q)
-Q
.5
experimental
groups?
likely to confound or modify results appear to be controlled
and consistent across experimental groups.
M-
o
(D
>
Adequate: Some concern that variables that were likely to
confound or modify results were uncontrolled or inconsistent
be
C
3
ฃ
ฃ
o
u
across groups but are expected to have a minimal impact on
the results.
Deficient: Notable concern that potentially confounding
variables were uncontrolled or inconsistent across groups and
are expected to substantially impact the results.
Critically Deficient: Confounding variables were presumed to
be uncontrolled or inconsistent across groups and are
expected to be a primary driver of the results.
This document is a draft for review purposes only and does not constitute Agency policy.
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type
Domain name -
core question
Prompting questions
Basic considerations
.5
.5
ฆa
c
ro
V3J0
c
t
o
Q.
ai
cc
Selective reporting
and attrition
Did the study report
results for all
prespecified
outcomes and
tested animals?
Note: This domain
does not consider
the appropriateness
of the
analysis/results
presentation. This
aspect of study
quality is evaluated
in another domain.
For each study:
Selective reporting bias:
Are all results presented for
endpoints/outcomes described in the
methods (see note under core
question)?
Attrition bias:
Are all animals accounted for in the
results?
If there are discrepancies, do authors
provide an explanation (e.g., death or
unscheduled sacrifice during the
study)?
If omitted results and/or attrition are
unexplained, what is the expected
impact on the interpretation of the
results?
These considerations typically do not need to be refined by assessment
teams.
A judgment and rationale for this domain should be given for each
cohort or experiment in the study.
Good: Quantitative or qualitative results were reported for all
prespecified outcomes (explicitly stated or inferred), exposure
groups and evaluation timepoints. Data not reported in the
primary article is available from supplemental material. If
results omissions or animal attrition are identified, the authors
provide an explanation, and these are not expected to impact
the interpretation of the results.
Adequate: Quantitative or qualitative results are reported for
most prespecified outcomes (explicitly stated or inferred),
exposure groups and evaluation time points. Omissions and/or
attrition are not explained but are not expected to significantly
impact the interpretation of the results.
Deficient: Quantitative or qualitative results are missing for
many prespecified outcomes (explicitly stated or inferred),
exposure groups and evaluation time points and/or high
animal attrition; omissions and/or attrition are not explained
and may significantly impact the interpretation of the results.
Critically Deficient: Extensive results omission and/or animal
attrition are identified and prevent comparison of results
across treatment groups.
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>
ฆ>
ai
1/1
>
'>
-a
o
.c
a!
E
ai
o
a.
x
Chemical
administration and
characterization
Did the study
adequately
characterize
exposure to the
chemical of interest
and the exposure
administration
methods?
Note: Consideration
of the
appropriateness of
the route of
exposure is not
evaluated at the
individual study
level. Relevance and
utility of the routes
of exposure are
considered in the
PECO criteria for
study inclusion and
during evidence
synthesis.
For each study:
Does the study report the source and
purity and/or composition (e.g.,
identity and percent distribution of
different isomers) of the chemical? If
not, can the purity and/or
composition be obtained from the
supplier (e.g., as reported on the
website)?
Was independent analytical
verification of the test article purity
and composition performed?
Did the authors take steps to ensure
the reported exposure levels were
accurate?
o For inhalation studies: Were
target concentrations confirmed
using reliable analytical
measurements in chamber air?
o For oral studies: If necessary,
based on consideration of
chemical-specific knowledge (e.g.,
instability in solution; volatility)
and/or exposure design (e.g., the
frequency and duration of
exposure), were chemical
concentrations in the dosing
solutions or diet analytically
confirmed?
Are there concerns about the
methods used to administer the
chemical (e.g., inhalation chamber
type, gavage volume, etc.)?
It is essential that these criteria are considered, and potentially refined,
by assessment teams, as the specific variables of concern can vary by
chemical.
A judgment and rationale for this domain should be given for each
cohort or experiment in the study.
Good: Chemical administration and characterization is
complete (i.e., source, purity, and analytical verification of the
test article are provided). There are no concerns about the
composition, stability, or purity of the administered chemical
or the specific methods of administration. For inhalation
studies, chemical concentrations in the exposure chambers are
verified using reliable analytical methods.
Adequate: Some uncertainties in the chemical administration
and characterization are identified but these are expected to
have minimal impact on interpretation of the results (e.g.,
source and vendor-reported purity are presented, but not
independently verified; purity of the test article is suboptimal
but not concerning; for inhalation studies, actual exposure
concentrations are missing or verified with less reliable
methods).
Deficient: Uncertainties in the exposure characterization are
identified and expected to substantially impact the results
(e.g., source of the test article is not reported; levels of
impurities are substantial or concerning; deficient
administration methods, such as the use of static inhalation
chambers or a gavage volume considered too large for the
species and/or life stage at exposure).
Critically Deficient: Uncertainties in the exposure
characterization are identified and there is reasonable
certainty that the results are largely attributable to factors
other than exposure to the chemical of interest (e.g., identified
impurities are expected to be a primary driver of the results).
This document is a draft for review purposes only and does not constitute Agency policy.
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Evaluation
type
Domain name -
core question
Prompting questions
Basic considerations
>
'>
a>
to
>
">
ฆa
o
.c
tu
E
ai
o
a.
x
Exposure timing,
frequency and
duration
Was the timing,
frequency, and
duration of exposure
sensitive for the
endpoint(s)/
outcome(s) of
interest?
For each endpoint/outcome or grouping of
endpoints/outcomes in a study:
Does the exposure period include the
critical window of sensitivity?
Was the duration and frequency of
exposure sensitive for detecting the
endpoint of interest?
Considerations for this domain are highly variable depending on the
endpoint(s)/outcome(s) of interest and must be refined by assessment
teams.
A judgment and rationale for this domain should be given for each
endpoint/outcome or group of endpoints/outcomes investigated in the
study.
Good: The duration and frequency of the exposure was
sensitive, and the exposure included the critical window of
sensitivity (if known).
Adequate: The duration and frequency of the exposure was
sensitive, and the exposure covered most of the critical
window of sensitivity (if known).
Deficient: The duration and/or frequency of the exposure is
not sensitive and did not include most of the critical window of
sensitivity (if known). These limitations are expected to bias
the results towards the null.
Critically Deficient: The exposure design was not sensitive and
is expected to strongly bias the results towards the null. The
rationale should indicate the specific concern(s).
This document is a draft for review purposes only and does not constitute Agency policy.
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type
Domain name -
core question
Prompting questions
Basic considerations
>
'>
ai
to
>
a.
ai
*_
T3
C
TO
U)
ai
ro
ai
E
ai
E
o
Endpoint sensitivity
and specificity
Are the procedures
sensitive and
specific for
evaluating the
endpoint(s)/
outcome(s) of
interest?
Note: Sample size
alone is not a reason
to conclude an
individual study is
critically deficient.
For each endpoint/outcome or grouping of
endpoints/outcomes in a study:
Are there concerns regarding the
specificity and validity of the
protocols?
Are there serious concerns regarding
the sample size (see note)?
Are there concerns regarding the
timing of the endpoint assessment?
Considerations for this domain are highly variable depending on the
endpoint(s)/outcome(s) of interest and must be refined by assessment
teams.
A judgment and rationale for this domain should be given for each
endpoint/outcome or group of endpoints/outcomes investigated in the
study.
Examples of potential concerns include:
Selection of protocols that are insensitive or nonspecific for
the endpoint of interest
Use of unreliable methods to assess the outcome
Assessment of endpoints at inappropriate or insensitive ages,
or without addressing known endpoint variation (e.g., due to
circadian rhythms, estrous cyclicity, etc.)
Decreased specificity or sensitivity of the response due to the
timing of endpoint evaluation, as compared to exposure (e.g.,
short-acting depressant or irritant effects of chemicals;
insensitivity due to prolonged period of non-exposure before
testing)
This document is a draft for review purposes only and does not constitute Agency policy.
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type
Domain name -
core question
Prompting questions
Basic considerations
>
">
ai
to
>
a.
73
a>
*_
T3
C
TO
U)
ai
ro
ai
E
a>
E
o
Results
presentation
Are the results
presented in a way
that makes the data
usable and
transparent?
For each endpoint/outcome or grouping of
endpoints/outcomes in a study:
Does the level of detail allow for an
informed interpretation of the
results?
Are the data analyzed, compared, or
presented in a way that is
inappropriate or misleading?
Considerations for this domain are highly variable depending on the
outcomes of interest and must be refined by assessment teams.
A judgment and rationale for this domain should be given for each
endpoint/outcome or group of endpoints/outcomes investigated in the
study.
Examples of potential concerns include:
Nonpreferred presentation, such as developmental toxicity
data averaged across pups in a treatment group, when litter
responses are more appropriate
Failing to present quantitative results
Pooling data when responses are known or expected to differ
substantially (e.g., across sexes or ages)
Failing to report on or address overt toxicity when exposure
levels are known or expected to be highly toxic
Lack of full presentation of the data (e.g., presentation of
mean without variance data; concurrent control data are not
presented)
This document is a draft for review purposes only and does not constitute Agency policy.
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type
Domain name -
core question
Prompting questions
Basic considerations
a>
u
a>
ฆc
ai
>
O
Overall confidence
Considering the
identified strengths
and limitations,
what is the overall
confidence rating for
the endpoint(s)/
outcome(s) of
interest?
Note: Reviewers
should mark studies
that are rated lower
than high confidence
only due to low
sensitivity (i.e., bias
towards the null) for
additional
consideration during
evidence synthesis. If
the study is
otherwise
well-conducted and
an effect is
observed, the
confidence may be
increased.
For each endpoint/outcome or grouping of
endpoints/outcomes in a study:
Were concerns (i.e., limitations or
uncertainties) related to the reporting
quality, risk of bias, or sensitivity
identified?
If yes, what is their expected impact
on the overall interpretation of the
reliability and validity of the study
results, including (when possible)
interpretations of impacts on the
magnitude or direction of the
reported effects?
The overall confidence rating considers the likely impact of the noted
concerns (i.e., limitations or uncertainties) in reporting, bias, and
sensitivity on the results.
A confidence rating and rationale should be given for each
endpoint/outcome or group of endpoints/outcomes investigated in the
study.
High Confidence: No notable concerns are identified (e.g., most
or all domains rated Good).
Medium Confidence: Some concerns are identified but
expected to have minimal impact on the interpretation of the
results (e.g., most domains rated Adequate or Good; may
include studies with Deficient ratings if concerns are not
expected to strongly impact the magnitude or direction of the
results). Any important concerns should be carried forward to
evidence synthesis.
Low Confidence: Identified concerns are expected to
significantly impact on the study results or their interpretation
(e.g., generally, Deficient ratings for one or more domains).
The concerns leading to this confidence judgment must be
carried forward to evidence synthesis (see note).
Uninformative: Serious flaw(s) that make the study results
unusable for informing hazard identification (e.g., generally, a
Critically Deficient rating in any domain; many Deficient
ratings). Uninformative studies are not considered further in
the synthesis and integration of evidence.
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6.4, PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODEL
EVALUATION
PBPK (or classical pharmacokinetic [PK])6 models should be used in an assessment when an
applicable one exists and no equal or better alternative for dosimetric extrapolation is available.
Any models used should represent current scientific knowledge and accurately translate the
science into computational code in a reproducible, transparent manner. For a specific target
organ/tissue, it may be possible to employ or adapt an existing PBPK model or develop a new PBPK
model or an alternate quantitative approach. Data for PBPK models could come from studies across
various species and may be in vitro or in vivo in design.
Existing naphthalene PBPK models were identified through a literature search and are
summarized in Appendix C. Of these, the model of Campbell etal. (20141 is the penultimate model
in its lineage and it explicitly describes dosimetry for specific regions in the upper respiratory tract,
which is a feature that distinguishes it from all previous models. Kapraun et al. f20201 extended the
model of Campbell et al. f20141 by incorporating a skin route of exposure and demonstrated that
their model could be used to reproduce human pharmacokinetic data; they also performed quality
assurance procedures (U.S. EPA. 2018dl for their model. This most recently published naphthalene
PBPK model (Kapraun et al.. 20201 is therefore the clear choice for use in this assessment.
EPA has evaluated the Kapraun et al. (20201 model in accordance with criteria outlined by
U.S. EPA (2018dl. Judgments on the suitability of a model are separated into two categories:
scientific and technical (see Table 6-5). The scientific criteria focus on whether the biology,
chemistry, and other information available for chemical MOA(s) are justified (i.e., preferably with
citations to support use) and represented by the model structure and equations. The scientific
criteria are judged based on information presented in the publication or report that describes the
model and do not require evaluation of the computer code. Preliminary technical criteria include
availability of the computer code and completeness of parameter listing and documentation.
Studies that meet the preliminary scientific and technical criteria are then subjected to an in-depth
technical evaluation, which includes a thorough review and testing of the computational code. The
in-depth technical and scientific analyses focus on the accurate implementation of the conceptual
model in the computational code, use of scientifically supported and biologically consistent
parameters in the model, and reproducibility of model results reported in journal publications and
6 Note that the terms "pharmacokinetic" (adjective) and "pharmacokinetics" (noun), which are both abbreviated as
"PK," are used in this document when discussing absorption, distribution, metabolism, and excretion (ADME) of a
substance by an organism or any related quantities, experiments, or models. The terms "toxicokinetic" and
"toxicokinetics," which are both abbreviated as "TK," are frequently used as synonyms for "pharmacokinetic" and
"pharmacokinetics" in the literature, but the latter terms are used preferentially here for document-wide
consistency. Also, PBPK models are sometimes described as "physiologically based toxicokinetic models"
(abbreviated "PBTK models") or even as "physiologically based kinetic models" (abbreviated "PBK models") in the
literature, but in this document the term "PBPK model" is used preferentially for purposes of consistency.
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1 other documents. This approach stresses (1) clarity in the documentation of model purpose,
2 structure, and biological characterization; (2) validation of mathematical descriptions, parameter
3 values, and computer implementation; and (3) evaluation of each plausible dose metric. The
4 in-depth analysis is used to evaluate the potential value and cost of developing a new model or
5 substantially revising an existing one.
Table 6-5. Criteria for evaluating physiologically based pharmacokinetic
(PBPK) models
Category
Specific criteria
Scientific
Biological basis for the model is accurate.
Consistent with mechanisms that significantly impact dosimetry.
Predicts dose metric(s) expected to be relevant.
Applicable for relevant route(s) of exposure.
Consideration of model fidelity to the biological system strengthens the scientific basis of the
assessment relative to standard exposure-based extrapolation (default) approaches.
Ability of model to describe critical behavior, such as nonlinear kinetics in a relevant
dose range, better than the default (i.e., BW3/4 scaling).
Model parameterization for critical life stages or windows of susceptibility. Evaluation of
these criteria should also consider the model's fidelity vs. default approaches and
possible use of an intraspecies uncertainty factor (UF) in conjunction with the model to
account for variations in sensitivity between life stages.
Predictive power of model-based dose metric vs. default approach, based on exposure.
o Specifically, model-based metrics may correlate better than the applied doses
with animal/human dose-response data.
o The degree of certainty in model predictions vs. default is also a factor. For
example, while target tissue metrics are generally considered better than blood
concentration metrics, lack of data to validate tissue predictions when blood
data are available may lead to choosing the latter.
Principle of parsimony
Model complexity or biological scale, including number and parameterization of
(sub)compartments (e.g., tissue or subcellular levels) should be commensurate with
data available to identify parameters.
Model describes existing PK data reasonably well, both in "shape" (matches curvature, inflection
points, peak concentration time, etc.) and quantitatively (e.g., within factor of 2-3).
Model equations are consistent with biochemical understanding and biological plausibility.
Initial
Well-documented model code is readily available to EPA and the public.
technical
Set of published parameters is clearly identified, including origin/derivation.
Parameters do not vary unpredictably with dose (e.g., any dose dependence in absorption
constants is predictable across the dose ranges relevant for animal and human modeling).
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Category
Specific criteria
Sensitivity and uncertainty analysis has been conducted for relevant exposure levels (local
sensitivity analysis is sufficient, but global analysis provides more information).
If a sensitivity analysis was not conducted, EPA may decide to independently conduct
this additional work before using the model in the assessment.
A sound explanation should be provided when sensitivity of the dose metric to model
parameters differs from what is reasonably expected based on experience.
6.5. IN VITRO STUDY EVALUATION
As described in Section 4.4, the initial literature screening identifies sets of other potentially
informative studies, including mechanistic studies, as "potentially relevant supplemental
information." Mechanistic information includes any experimental measurement related to a health
outcome that informs the biological or chemical events associated with phenotypic effects; these
measurements can improve understanding of the mechanisms involved in the biological effects
following exposure to a chemical but are not generally considered by themselves adverse outcomes.
Mechanistic data are reported in a diverse array of observational and experimental studies across
species, model systems, and exposure paradigms, including in vitro, in vivo (by various routes of
exposure), ex vivo, and in silico studies. Section 5.3.2 outlines an approach for the consideration of
information from mechanistic studies where the specific analytical approach is targeted to the
assessment needs depending on the extent and nature of the human and animal evidence.
Individual study-level evaluations of mechanistic endpoints are not typically pursued. This
is because each identified study that reported mechanistic information would need to undergo a full
evaluation of risk of bias and sensitivity before the relevant toxicity pathways are identified and the
needs of the assessment are better understood, which would not be an effective use of time and
resources. For some chemical assessments, however, it may be necessary to identify assay-specific
considerations for study endpoint evaluations on a case-by-case basis to provide a more detailed
summary and evaluation for the most relevant individual studies. This may be done, for example,
when the scientific understanding of a critical mechanistic event or MOA is less established or lacks
scientific consensus, the reported findings on a mechanistic endpoint are conflicting, the available
mechanistic evidence addresses a complex and influential aspect of the assessment, or in vitro or in
silico data make up the bulk of the evidence base and there is little or no evidence from
epidemiological studies or animal bioassays.
If a subset of individual mechanistic studies is identified for evaluation, the study evaluation
considerations will differ depending on the type of endpoints, study designs, and model systems or
populations evaluated. It should be noted that because the evaluation process is outcome specific,
overall confidence classifications for human or animal studies that have already been determined
will not automatically apply to mechanistic endpoints if reported in the same study; a separate
evaluation of the mechanistic endpoints should be performed as the utility of a study may vary for
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the different outcomes reported. Developing specific considerations requires a familiarity with the
studies to be evaluated and cannot be conducted in the absence of knowledge of the relevant study
designs, measurements, and analytic issues. Knowledge of issues related to the hazards and the
outcomes identified in the revised evaluation plan is also important for developing specific
evaluation considerations. One challenge is that novel methodologies for studying mechanistic
evidence are continuously being developed and implemented and often no "standard practices"
exist
The evaluation of mechanistic studies applies similar principles as those described above
for the evaluation of epidemiological and experimental animal studies. Table 6- provides the
standard domains and core questions for the evaluation of studies conducted in in vitro test
systems, along with some basic considerations for guiding the evaluation. The evaluation process
focuses on assessing aspects of the study design and conduct through three broad types of
evaluations: reporting quality, risk of bias, and study sensitivity. Some domain considerations are
tailored to the chemical and to the assay(s) or endpoint(s) being evaluated. Assessment teams work
with subject matter experts to develop specific considerations. These specific considerations are
determined prior to performing study evaluation, although they may be refined as the study
evaluation proceeds (e.g., during pilot testing). Assessment- or assay-specific considerations are
documented and made publicly available in the assessment
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Table 6-6. Domains, questions, and general considerations to guide the evaluation of in vitro studies
Domain and core
question
Prompting questions
General considerations
Observational bias/blinding
Did the study implement
measures, where possible, to
reduce observational bias?
Considerations will vary
depending on the specific
assay/model system being
used and may not be
applicable to some analyses.
For each assay or endpoint in a study:
Did the study report steps taken to minimize
observational bias during analysis (e.g.,
blinding/coding of slides or plates for
analysis; collection of data from randomly
selected fields; positive controls that are not
immediately identifiable)?
If not, did the study use a design or
approach for which such procedures can be
inferred, or which would not be possible to
implement?
Were the assays evaluated using automated
approaches (e.g., microplate readers) that
reduce concern for observational bias?
What is the expected impact of failure to
implement (or report implementation) of
these methods/procedures on results?
These considerations typically do not need to be refined by the
assessment teams. Prior to performing evaluations, teams should
consider the specific assay to identify highly subjective measures
of endpoints where observational bias may strongly influence
results.
A judgment and rationale for this domain should be given for
each assay or endpoint or group of endpoints investigated in the
study.
Good: Measures to reduce observational bias were described
(e.g., specific mention of blinding and/or coding of slides for
analysis), or observational bias is not a concern because of use of
automated/computer driven systems and/or standard laboratory
kits.
Not reported, interpreted as adequate: Measures to reduce
observational bias were not described, but the potential concern
for bias was mitigated because protocol cited includes a
description of requirements for blinding/coding, or the impact on
results is expected to be minor because the specific measurement
is more objective.
Not reported, interpreted as deficient: No protocol cited; the
potential impact on the results is major because the endpoint
measures are highly subjective (e.g., counting plaques or live vs.
dead cells).
Critically deficient: Strong evidence for observational bias that
could have impacted the results.
Variable Control
For each study:
These considerations will need to be refined by assessment teams
as the specific variables of concern can vary by the experimental
test system and chemical.
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Domain and core
question
Prompting questions
General considerations
Are all introduced variables
with the potential to affect
the results of interest
controlled for and consistent
across experimental groups?
Are there any known or presumed
differences across treatment groups (e.g.,
co-exposures, culture conditions, cell
passages, variations in reagent production
lots, mycoplasma infections) that could bias
the results? If differences are identified, to
what extent are they expected to impact the
results?
Did the study address feature inherent to
the physico-chemical properties of the test
substance(s) that have the potential to bias
the results away from the null? For example,
could the test article interfere with a given
assay (e.g., auto-fluoresces or inhibits
enzymatic processes necessary for assay
signals), potentially leading to an erroneous
positive signal? (Note that concerns related
to dose are addressed in chemical
administration and characterization.)
Are there known variations in cellular
signaling unique to the model system that
could influence the possibility of detecting
the effect(s) of interest?
Are there concerns regarding the negative
(untreated and/or vehicle) controls used?
Were negative controls run concurrently?
A judgment and rationale for this domain should be given for
each experiment in the study, noting when the potential to affect
results is restricted to specific assays or endpoints.
Good: Outside of the exposure of interest, variables or features of
the test system and/or chemical properties that are likely to
impact results appear to be controlled for and consistent across
experimental groups.
Adequate: Some concern that variables or features of the test
system and/or chemical properties that are likely to modify or
interfere with results were uncontrolled or inconsistent across
groups but are expected to have a minimal impact on the results.
Deficient: Notable concern that important study variables and/or
features of the test system lacked specificity or were uncontrolled
or inconsistent across groups and are expected to substantially
impact the results.
Critically deficient: Features of the test system are known to be
nonspecific for this endpoint, and/or influential study variables
were presumed to be uncontrolled or inconsistent across groups
and are expected to be a primary driver of the results.
Selective Reporting
Did the study present
results, quantitatively or
qualitatively, for all
prespecified assays or
For each study:
Are results presented for all
endpoints/outcomes described in the
methods?
These considerations typically do not need to be refined by
assessment teams.
A judgment and rationale for this domain should be given for
each assay or endpoint in the study.
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Domain and core
question
Prompting questions
General considerations
endpoints and replicates
described in the methods?
Note: The appropriateness of
the analysis or results
presentation is considered
under results presentation.
Did the study clearly indicate the number of
replicate experiments performed? Were the
replicates technical (from the same sample)
or independent (from separate, distinct
exposures)?
If unexplained results omissions are
identified, what is the expected impact on
the interpretation of the results?
Good: Quantitative or qualitative results were reported for all
prespecified assays or endpoints (explicitly stated or inferred),
exposure groups and evaluation timepoints. Data not reported in
the primary article is available from supplemental material. If
results omissions are identified, the authors provide an
explanation, and these are not expected to impact the
interpretation of the results.
Adequate: Quantitative or qualitative results are reported for
most prespecified assays or endpoints (explicitly stated or
inferred), exposure groups and evaluation timepoints. Omissions
are not explained but are not expected to significantly impact the
interpretation of the results.
Deficient: Quantitative or qualitative results are missing for many
prespecified assays or endpoints (explicitly stated or inferred),
exposure groups and evaluation timepoints; omissions are not
explained and may significantly impact the interpretation of the
results.
Critically Deficient: Extensive results omissions are identified,
preventing comparisons of results across treatment groups.
Chemical administration
and characterization
Did the study adequately
characterize exposure to the
chemical of interest and the
exposure administration
methods?
For each study:
Are there concerns regarding the purity
and/or composition (e.g., identity and
percent distribution of different isomers) of
the test material/chemical? If so, can the
purity and/or composition be obtained from
the supplier (e.g., as reported on the
website)?
Was independent analytical verification of
the test article purity and composition
It is essential that these criteria are considered, and potentially
refined, by assessment teams, as the specific variables of concern
can vary by chemical (e.g., stability may be an issue for one
chemical but not another).
A judgment and rationale for this domain should be given for
each experiment in the study.
Good: Chemical administration and characterization is complete
(i.e., source, purity, and analytical verification of the test article
are provided). There are no concerns about the composition,
stability, or purity of the administered chemical, or the specific
methods of administration.
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Domain and core
question
Prompting questions
General considerations
performed? If not, is this a significant
concern for this substance?
Are there concerns about the stability of the
test chemical in the vehicle and/or culture
media (e.g., pH, solubility, volatility,
adhesion to plastics) that were not
corrected for, leading to potential bias away
from the null (e.g., observed precipitate
formation at high concentrations) or toward
the null (e.g., enclosed chambers not used
for testing volatile chemicals)?
Are there concerns about the preparation or
storage conditions of the test substance?
Are there concerns about the methods used
to administer the chemical?
Adequate: Some uncertainties in the chemical administration and
characterization are identified but these are expected to have
minimal impact on interpretation of the results (e.g., source and
vendor-reported purity are presented but not independently
verified; purity of the test article is suboptimal but not
concerning).
Deficient: Uncertainties in the exposure characterization are
identified and expected to substantially impact the results (e.g.,
the source and purity of the test article are not reported, and no
independent verification of the test article was conducted; levels
of impurities are substantial or concerning; deficient
administration methods were used).
Critically deficient: Uncertainties in the exposure characterization
are identified and there is reasonable certainty that the results
are largely attributable to factors other than exposure to the
chemical of interest (e.g., identified impurities are expected to be
a primary driver of the results).
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Endpoint measurement
Are the selected protocols,
procedures, and test systems
adequately described and
appropriate for evaluating
the endpoint(s) of interest?
Notes:
Considerations related to
adjustments or corrections to
endpoint measurements are
addressed under results
presentation.
Considerations related to the
sensitivity of the animal
model and timing of
endpoint measurement are
evaluated under sensitivity.
For each endpoint or grouping of endpoints
in a study:
Are the evaluation methods and test
systems adequately described and
appropriate?
Are there concerns regarding the
methodology selected (e.g., accepted
guidelines, established criteria) for endpoint
evaluation?
Are there concerns about the specificity of
the experimental design? Did the study
address feature inherent to the test system
or experiment that have the potential to
lead to bias away from the null?
Are there serious concerns about the
number of replicates or sample size in the
study?
Are appropriate control groups for the
study/assay type included? Was there a
need for the assay to include specific
controls to reduce potential sources of
underlying bias?
Did the test compound induce cytotoxicity
(known, or expected based on other studies
of similar design) to a degree that is
expected to affect interpretation of results?
Considerations for this domain are highly variable depending on
the assay or endpoint(s) of interest and must be refined by
assessment teams.
A judgment and rationale for this domain should be given for
each assay or endpoint or group of endpoints investigated in the
study.
Some considerations include the following:
Good:
Adequate description of methods and test system.
Use of generally accepted and reliable endpoint methods
that are consistent with accepted guidelines or
established criteria for the assay(s)/endpoint(s) of
interest.
Sample sizes are generally considered adequate for the
assay or protocol of interest and there are no notable
concerns about sampling in the context of the endpoint
protocol.
Includes appropriate control groups (e.g., use of loading
controls) and any use of nonconcurrent or historical
control data (e.g., for comparison to background levels in
negative controls) is justified (e.g., authors or evaluators
considered the similarity between current cell cultures
and laboratory conditions to historical controls).
Ratings of Adequate, Deficient, and Critically Deficient are
generally defined as follows:
Adequate: Issues are identified that may affect endpoint
measurement but are considered unlikely to substantially impact
the overall findings or the ability to reliably interpret those
findings.
Deficient: Concerns are raised that are expected to notably affect
endpoint measurement and reduce the reliability of the study
findings.
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Domain and core
question
Prompting questions
General considerations
Critically deficient: Severe concerns are raised about endpoint
measurement and any findings are likely to be largely explained
by these limitations.
The following specific examples of relevant concerns are typically
associated with a Deficient rating, but Adequate or Critically
Deficient might be applied depending on the expected impact of
limitations on the reliability and interpretation of the results:
Study report lacks important details that are necessary to
evaluate the appropriateness of the study design (e.g.,
description of the assays or protocols; information on
the cell line, passage number).
Selection of protocols that are nonpreferred or lack
specificity for investigating the endpoint of interest. This
includes omission of additional experimental criteria
(e.g., inclusion of a positive control or dosing up to levels
causing minimal toxicity) when required by specific
testing guidelines/protocols. *
Cytotoxicity is observed or expected based on findings from
similarly designed studies and may mask interpretation
of outcome(s) of interest.
Sample sizes are smaller than is generally considered
adequate for the assay or protocol of interest.
Inadequate sampling can also be raised within the
context of the endpoint protocol (e.g., in a pathology
study, bias that is introduced by only sampling a single
tissue depth or an inadequate number of slides per
animal).**
Controls are not included or considered inappropriate.
*These limitations typically also raise a concern for insensitivity.
**Sample size alone is not a reason to conclude an individual
study is critically deficient.
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Results presentation
Are the results presented
and compared in a way that
is appropriate and
transparent and makes the
data usable?
For each assay/endpoint or grouping of
endpoints in a study:
Does the level of detail allow for an
informed interpretation of the results?
If applicable, was the assay signal
normalized to account for non-biological
differences across replicates and exposure
groups?
Are the data compared or presented in a
way that is inappropriate or misleading (e.g.,
presenting western blot images without
including numerical values for densitometry
analysis, or vice versa)? Flag potentially
inappropriate statistical comparisons for
further review.
Considerations for this domain are highly variable depending on
the endpoints of interest and must be refined by assessment
teams.
A judgment and rationale for this domain should be given for
each assay or endpoint or group of endpoints investigated in the
study.
Some considerations include the following:
Good:
No concerns with how the data are presented.
Results are quantified or otherwise presented in a manner
that allows for an independent consideration of the data
(assessments do not rely on author interpretations).
No concerns with completeness of the results reporting.*
Ratings of Adequate, Deficient, and Critically Deficient are
generally defined as follows:
Adequate: Concerns are identified that may affect results
presentation but are considered unlikely to substantially impact
the overall findings or the ability to reliably interpret those
findings.
Deficient: Concerns with results presentation are identified and
expected to substantially impact results interpretation and
reduce the reliability of the study findings.
Critically deficient: Severe concerns about results presentation
were identified and study findings are likely to be largely
explained by these limitations.
The following specific examples of relevant concerns are typically
associated with a Deficient rating but Adequate or Critically
Deficient might be applied depending on expected impact of
limitations on the reliability and interpretation of the results:
Nonpreferred presentation of data (e.g., averaging technical
replicates rather than independent replicates).
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Domain and core
question
Prompting questions
General considerations
Failure to present quantitative results.
Pooling data when responses are known or expected to differ
substantially (e.g., across cell types or passage number).
Incomplete presentation of the data* (e.g., presentation of
mean without variance data; concurrent control data are
not presented; failure to report or address overt
cytotoxicity).
*Failure to describe any findings for assessed outcomes (i.e.,
report lacks any qualitative or quantitative description of the
results in tables, figures, or text) will result in a critically deficient
rating for the outcome(s) of interest for Results Presentation;
overall completeness of reporting at the study level is addressed
under Selective Reporting.
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Sensitivity
Are there concerns that
sensitivity in the study is not
adequate to detect an
effect?
Was the exposure period, timing (i.e., cell
passage number, insufficient culture
maturity for the adequate expression of
mature cell markers; insufficient treatment
and/or measurement duration for the
production of protein above the level of
detection), frequency, and duration of
exposure sensitive for the assay/model
system of interest, particularly in the
absence of a positive control?
Assay-specific considerations regarding
sensitivity, specificity, and validity of the
selection of the test methods will be
described here (e.g., metabolic competency,
antibody specificity) (some of these external
considerations may have been applied
during prioritization of studies for
evaluation). Are there aspects related to risk
of bias domains that raise concerns about
insensitivity (e.g., selection of protocols or
methods that are known to be insensitive or
nonspecific for the outcome(s) of interest)?
Are there concerns regarding the need for
positive controls (e.g., concerns that the
effects of interest may be inhibited or
otherwise poorly manifest in the test
system, for example due to differences from
in vivo biology)? If used, was the selected
positive test substance (and dose)
reasonable and appropriate and was the
intended positive response induced?
Are there concerns regarding the need for positive controls (e.g.,
concerns that the effects of interest may be inhibited or
otherwise poorly manifest in the test system, for example due to
differences from in vivo biology)? If used, was the selected
positive test substance (and dose) reasonable and appropriate
and was the intended positive response induced?
Considerations for this domain are highly variable depending on
the specific assay/model system used or endpoint(s) of interest
and must be refined by assessment teams. Some study design
features that affect study sensitivity may have already been
included in the other evaluation domains; these should be noted
in this domain, along with any features that have not been
addressed elsewhere.
Some considerations include:
Good
The experimental design (considering exposure period,
timing, frequency, and duration) is appropriate and
sensitive for evaluating the outcome(s) of interest.
The selected test system is appropriate and sensitive for
evaluating the outcome(s) of interest (e.g., cell line/cell
type is appropriate and routinely used for the selected
assay).
No significant concerns with the ability of the experimental
design to detect the specific outcome(s) of interest (e.g.,
study designed to address known endpoint variability
that is unrelated to treatment, such as doubling time or
confluency).
Timing of endpoint measurement in relation to the chemical
exposure is appropriate and sensitive (e.g., cultures
adequately express mature cell markers).
Potential sources of bias towards the null are not a
substantial concern.
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Domain and core
question
Prompting questions
General considerations
Adequate
Potential issues are identified related to the considerations
described for Good that could reduce sensitivity, but
they are unlikely to impact the overall findings of the
study.
Deficient
Concerns were raised about the considerations described for
Good that are expected to notably decrease the
sensitivity of the study to detect a response in the
exposed group(s).
Critically deficient
Severe concerns were raised about the sensitivity of the
study and experimental design such that any observed
associations are likely to be explained by bias. The
rationale should indicate the specific concern(s).
Overall confidence
Considering the identified
strengths and limitations,
what is the overall
confidence rating for the
assay(s) or endpoint(s) of
interest?
For each assay or endpoint or grouping of
endpoints in a study:
Were concerns (i.e., limitations or
uncertainties) related to the risk of
bias or sensitivity identified?
If yes, what is their expected impact
on the overall interpretation of the
reliability and validity of the study
results, including (when possible)
interpretations of impacts on the
magnitude or direction of the
reported effects?
The overall confidence rating considers the likely impact of the
noted concerns (i.e., limitations or uncertainties) in reporting,
bias, and sensitivity on the results.
A confidence rating and rationale should be given for each assay
or endpoint, or group of endpoints investigated in the study.
Confidence rating definitions are described above (see
Section 4.1).
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7.DATA EXTRACTION OF STUDY METHODS AND
RESULTS
The process of summarizing study methods and results is referred to as data extraction. All
epidemiology and experimental animal studies meeting the problem formulation PECO criteria
after full-text review are briefly summarized in literature inventories and visualized using Tableau
software (see Section 4.5 for a description of the information captured in the literature inventory).
For this assessment, for all studies that met the refined assessment PECO criteria in Table 5-1,
HAWC is used for full extraction of study methods and results. For animal studies, compared to the
literature inventory forms used to describe studies that meet initial PECO criteria, full data
extraction in HAWC includes summarizing more details of study design (e.g., diet, chemical purity)
and gathering effect size information. Instructions on how to conduct data extraction in HAWC are
available at https: //hawcproiect.org/resources/. Over 100 distinct extraction fields are collected
for each animal study and endpoint (for list of data extraction fields, see Downloads > Animal
Bioassay Data > Complete Export at the HAWC Naphthalene Project
https: //hawc.epa.gOv/assessment/100500288 /l. An additional resource used to implement use of
a consistent vocabulary to summarize endpoints assessed in animal studies is available in the
HAWC project "IRIS PPRTV SEM Template Figures and Resources" (see "Attachments", then select
the "Environmental Health Vocabulary (EHV) a recommended terminology for
outcomes/endpoints" file).
All findings are considered for extraction, regardless of statistical significance. The level of
extraction for specific outcomes within a study could differ (i.e., narrative only if the finding was
qualitative). For quality control, studies are summarized by one member of the evaluation team and
independently verified by at least one other member. Discrepancies are resolved by discussion or
consultation within the evaluation team. Data extraction results are presented via figures, tables, or
interactive web-based graphics in the assessment The information is also made available for
download in Excel format when the draft is publicly released.
For non-English studies online translation tools (e.g., Google translator) or engagement with
a native speaker will be considered for use in summarizing studies at the level of the literature
inventory. Fee-based translation services for non-English studies are typically reserved for studies
considered potentially informative for dose response, a consideration that occurs after preparation
of the initial literature inventory during draft assessment development. Digital rulers, such as
WebPlotDigitizer fhttp://arohatgi.info/WebPlotDigitizer/). are used to extract numerical
information from figures, and their use is be documented during extraction. For studies that
evaluate endpoints at multiple time points (e.g., 7 days, 3 weeks, 3 months) data are generally
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summarized for the longest duration in the study report, but other durations may be summarized if
they provide important contextual information for hazard characterization (e.g., an effect was
present at an interim time point but did not appear to persist or the magnitude of the effect
diminished). A free text field is available in HAWC to describe cases when the approach for
summarizing results requires explanation.
Author queries may be conducted for studies considered for dose-response analysis to
facilitate quantitative analysis (e.g., information on variability or availability of individual animal
data). Outreach to study authors or designated contact persons is documented and considered
unsuccessful if researchers do not respond to email or phone requests within 1 month of initial
attempt(s) to contact Only information or data that can be made publicly available (e.g., within
HAWC or HERO) will be considered.
In some cases, EPA may conduct its own statistical analysis of human and animal toxicology
data (assuming the data are amenable to doing so and the study is otherwise well-conducted)
during evidence synthesis.
Exposures will be standardized to common units. Exposure levels in oral studies will be
expressed in units of mg/kg-day. Where study authors provide exposure levels in concentrations in
the diet or drinking water, dose conversions will be made using study-specific food or water
consumption rates and body weights when available. Otherwise, EPA defaults will be used fU.S.
EPA. 19881. addressing age and study duration as relevant for the species/strain and sex of the
animal of interest Exposure levels in inhalation studies will be expressed in units of mg/m3.
Assumptions used in performing dose conversions will be documented. Unless otherwise reported
by study authors, the background level in experimental animal studies is assumed 0 ppm
(0 mg/kg-day).
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8.EVIDENCE SYNTHESIS AND INTEGRATION
Evidence synthesis7 is a within-stream analysis, conducted separately for human, animal,
and mechanistic evidence. Findings from human and animal evidence for each unit of analysis are
separately judged to reach an expression of certainty in the evidence for a hazard (robust, moderate,
slight, indeterminate, or compelling evidence of no effect). Within-stream evidence synthesis
conclusions directly inform the integration across the evidence streams to draw overall conclusions
for each of the assessed health effect categories (evidence demonstratesฆ, evidence indicates; evidence
suggestsฆ, evidence inadequate, or strong evidence supports no effect). A structured framework
approach is used to guide both evidence synthesis and integration. While there are circumstances
where specific mechanistic evidence (typically biological precursors) is included in the unit of
analysis for human or animal evidence synthesis, in most cases mechanistic findings are presented
separately from the human and animal evidence and used to inform conclusions on (1) the
coherence, directness of outcome measures, and biological significance of findings within the
animal or human evidence streams during evidence synthesis and, (2) evidence integration
judgments on the human relevance of findings in animals, coherence across evidence streams
("cross-stream coherence"), information on susceptible populations or lifestages, understanding of
biological plausibility and MOA, and possibly other critical inferences (e.g., read-across analyses).
The structured framework also accommodates consideration of supplemental information (e.g.,
ADME, non-PECO route of exposure) that can inform evidence synthesis and integration judgments.
Evidence synthesis: A summary of findings and judgment(s) regarding the certainty in the
evidence for hazard for each unit of analysis from the human and animal studies are made
in parallel, but separately. A unit of analysis is an outcome or group of related outcomes
within a health effect category that are considered together during evidence synthesis.
These judgments can incorporate mechanistic and other supplemental evidence when the
unit of analysis is defined as such (see Section 3). The units of analysis can also include or be
framed to focus on precursor events (e.g., biomarkers). In addition, this can include an
evaluation of coherence across units of analysis within an evidence stream. At this stage, the
animal evidence judgment(s) does not yet consider the human relevance of that evidence.
Evidence integration: The animal and human evidence judgments are combined to draw an
overall evidence integration judgment(s) that incorporates inferences drawn based on
information on the human relevance of the animal evidence, coherence across evidence
7 The phrases "evidence synthesis" and "evidence integration" used here are analogous to the phrases "strength of
evidence" and "weight of evidence," respectively, used in some other assessment processes (EFSA, 2017: U.S. EPA,
2017: NRC, 2014: U.S. EPA. 2005a).
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streams, potential susceptibility, understanding of biological plausibility and MOA, and
other critical inferences informed by mechanistic, ADME, or other supplemental data.
Evidence synthesis and integration judgments are expressed both narratively in the
assessment and summarized in tabular format in evidence profile tables (see Table 8-1). Key
findings and analyses of mechanistic and other supplemental content are also summarized in
narrative and tabular format to inform evidence synthesis and integration judgments (see Table 8-
2). In brief, after synthesis a certainty in the evidence judgment is drawn for each unit of analysis
summarized as robust, moderate, slight, indeterminate, or compelling evidence of no effect (see
Section 8.1). Next, these judgments are used to inform evidence integration judgments summarized
as evidence demonstrates, evidence indicates, evidence suggests, evidence inadequate, or
strong evidence supports no effect) (see Section 8.2). These summary judgments are included as
part of the evidence synthesis and integration narratives. When multiple units of analysis are
synthesized, the main evidence integration judgments typically focus on the unit of analysis with
the strongest evidence synthesis judgments, although exceptions may occur.8 Health outcomes or
endpoints where the unit of analysis is considered to present slight, indeterminant or compelling
evidence of no effect can inform the evidence integration hazard judgement but would typically not
be used as the basis for deriving a toxicity value. Structured evidence profile tables are used to
summarize these analyses and foster consistency within and across assessments. Instructions for
using HAWC to create these tables are available at the HAWC project "IRIS PPRTV SEM Template
Figures and Resources" (see "Attachments," then select the "Creating Evidence Profile Tables in
HAWC").
8In some cases, it may be appropriate to draw multiple evidence integration judgments within a given health
effect category. This is generally dependent on data availability (i.e., more narrowly defined categories may
be possible with more evidence) and the ability to integrate the different evidence streams at the level of
these more granular categories. More granular categories will generally be organized by pre-defined
manifestations of potential toxicity. For example, within the health effect category of immune effects,
separate and different evidence integration judgments might be appropriate for immusuppression,
immunostimulation, and sensitization and allergic response (i.e., the three types of immunotoxicity described
in the WHO guidance [2012]). Likewise, within the category of developmental effects, it may be appropriate
to draw separate judgments for potential effects on fetal death, structural abnormality, altered growth, and
functional deficits [i.e., the four manifestations of developmental toxicity described in EPA guidelines (U.S.
EPA. 1991)]. These separate judgments are particularly important when the evidence supports that the
different manifestations might be based on different toxicological mechanisms. As described for the evidence
synthesis judgments, the strongest evidence integration judgment will typically be used to reflect certainty in
the broader health effect category.
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Table 8-1. Generalized evidence profile table to show the relationship between evidence synthesis and evidence
integration to reach judgment of the evidence for hazard
Evidence Synthesis Judgments
(note that many factors and judgments require elaboration or evidence-based justification; see IRIS Handbook for details)
Evidence Integration
(Weight of Evidence)
Judgment(s)
Studies
Summary of key
findings
Factors that increase certainty
(Applied to each unit of analysis)
Factors that decrease certainty
(Applied to each unit of analysis)
Evidence Synthesis
Judgment(s)
Describe overall evidence integration
judgment(s):
ฉฉฉ Evidence demonstrates
ฉฉO Evidence indicates (likely)
ฉOO Evidence suggests
Evidence from human studies
Unit of analysis #1
Studies considered
and study confidence
Description of the
primary results
All/Mostly medium or high
confidence studies
Consistency
Dose-response gradient
Large or concerning magnitude
of effect
Coherence*
All/Mostly low confidence
studies
Unexplained inconsistency
Imprecision
Concerns about biological
significance*
Indirect outcome measures*
Lack of expected coherence*
Judgment reached for
each unit of analysis*
ฉ0ฉ Robust
ฉฉO Moderate
ฉOO Slight
OOO Indeterminate
Compelling
evidence of no effect
OOO Evidence inadequate
Strong evidence supports no
effect
Highlight the primary supporting
evidence for each integration
judgment*
Present inferences and conclusions on:
Human relevance of findings in
animals*
Evidence from animal studies
Unit of analysis #1
Studies considered
and study confidence
Description of the
primary results
All/Mostly medium or high
confidence studies
Consistency
Dose-response gradient
Large or concerning magnitude
of effect
Coherence*
All/Mostly low confidence
studies
Unexplained inconsistency
Imprecision
Concerns about biological
significance*
Indirect outcome measures*
Lack of expected coherence*
Judgment reached for
each unit of analysis
ฉฉฉ Robust
ฉฉO Moderate
ฉOO Slight
OOO Indeterminate
Compelling
evidence of no effect
Cross-stream coherence*
Potential susceptibility*
Understanding of biological
plausibility and MOA*
Other critical inferences
*Can be informed by key findings from the mechanistic analyses (see Table 8-2)
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Table 8-2. Generalized evidence profile table to show the key findings and supporting rationale from mechanistic
analyses
Mechanistic analyses
Biological events or pathways (or
other relevant evidence grouping)
Summary of key findings and interpretation
Judgment(s) and rationale
Different analyses mav be presented
separately, e.g., bv exposure route or
key uncertainty addressed
Each analysis mav include multiple rows
separated bv biological events or other
feature of the approach used for the
analysis
Generally, will cite mechanistic
synthesis (e.g., for references, for
detailed analysis)
Does not have to be chemical-
specific (e.g., read-across)
Mav include separate summaries, for example bv studv type
(e.g., new approach methods vs. in vivo biomarkers), dose, or
design
Interpretation: Summary of expert interpretation for the
body of evidence and supporting rationale
Key findings: Summary of findings across the body of
evidence (may focus on or emphasize highly informative
designs or findings), including key sources of uncertainty or
identified limitations of the study designs tested
(e.g., regarding the biological event or pathway being
examined)
Overall summary of expert interpretation across the assessed set of
biological events, potential mechanisms of toxicity, or other analysis
approach (e.g., AOP)
Includes the primary evidence supporting the interpretation(s)
Describes and informs the extent to which the evidence influences
inferences across evidence streams
Characterizes the limitations of the evaluation and highlights existing
data gaps
May have overlap with factors summarized for other streams
AOP = Adverse Outcome Pathway.
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8.1. EVIDENCE SYNTHESIS
IRIS assessments synthesize the evidence separately for each unit of analysis by focusing on
factors that increase or decrease certainty in the reported findings (see Table 8-1). These factors
are adapted from considerations for causality introduced by Austin Bradford Hill fHill. 1965] with
some expansion and adaptation of how they are applied to facilitate transparent application to
chemical assessments that consider multiple streams of evidence. Specifically the factors
considered are confidence in study findings (risk of bias and sensitivity), consistency across studies
or experiments, dose/exposure response gradient, strength (effect magnitude) of the association,
directness of outcome or endpoint measures, and coherence [Table 8-3; see additional discussion in
U.S. EPA (2005a), U.S. EPA (1994), and U.S. EPA (2020b)]. These factors are similar to the domains
considered in the GRADE Quality of Evidence framework fSchiinemann et al.. 20131. Each of the
considered factors and the certainty of evidence judgments require elaboration or evidence-based
justification in the synthesis narrative. Analysis of evidence synthesis considerations is qualitative
(i.e., numerical scores are not developed, summed, or subtracted).
Biological understanding (e.g., knowledge of how an effect manifests or progresses) or
mechanistic inference (e.g., dependency on a conserved key event across outcomes) can be used to
define which related outcomes are considered as a unit of analysis. The units of analysis may also
include predefined categories of mechanistic evidence (typically precursor events). When
mechanistic evidence is included in the units of analysis, it is evaluated against all evidence
synthesis factors. Mechanistic and other supplemental evidence not included in the units of analysis
can be analyzed to inform select evidence synthesis factors (i.e., coherence, directness of outcome
measures, or biological significance) within the animal and human evidence synthesis. Additional
mechanistic evaluations (e.g., biological plausibility) are considered as part of across stream
evidence integration (see Section 8.2).
Five levels of certainty in the evidence for a hazard are used to summarize evidence
synthesis judgments: robust (ฉฉฉ, very little uncertainty exists), moderate (ฉฉO, some
uncertainty exists), slight (ฉOO, large uncertainty exists), indeterminate (OOO), or compelling
evidence of no effect ( , little to no uncertainty exists for lack of hazard) (see Tables 8.4 and 8.5
for descriptions). Conceptually, before the evidence synthesis framework is applied, certainty in the
evidence is neutral (i.e., functionally equivalent to indeterminate). Next, the level of certainty
regarding the evidence for (or against) hazard is increased or decreased depending on
interpretations using the factors described in Table 8.3. Level of certainty analyses are conducted
for each unit of analysis within an evidence stream. Observations that increase certainty are having
an evidence base exhibiting a signal of an effect on the health outcome based on evaluation of
consistency across studies or experiments, the presence of a dose or exposure-response gradient,
observing a large or concerning magnitude of effect, and coherent findings for closely related
endpoints (can include mechanistic endpoints). These patterns are more compelling when
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1 observed among high or medium confidence studies. Observations that decrease certainty are
2 having an evidence base of mostly low confidence studies, unexplained inconsistency, imprecision,
3 concerns about biological significance, indirect measures of outcomes, and lack of expected
4 coherence. Study sensitivity considerations can be expressed as a factor that can either increase or
5 decrease certainty in the evidence, depending on whether an association is observed. An evidence
6 base of mostly null findings where insensitivity is a serious concern decreases certainty that the
7 evidence is sufficient to support a lack of health effect or association. Conversely, there may be an
8 increase in the evidence certainty in cases where an association is observed although the expected
9 impact of study sensitivity is towards the null.
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Table 8-3. Considerations that inform evaluations and judgments of the strength of the evidence for hazard
Consideration
Increased evidence certainty
(of the human or animal evidence for hazard3)
Decreased evidence certainty
(of the human or animal evidence for hazard3)
Risk of bias & sensitivity
(across studies)
An evidence base of mostly (or all) high or medium confidence
studies is interpreted as being only minimally affected by bias and
insensitivity.
This factor should not be used if no other factors would increase or
decrease the confidence for a given unit of analysis.
In addition, consideration of risk of bias and sensitivity should
inform how other factors are evaluated, i.e., can inconsistency be
potentially explained by variation in confidence judgments?
An evidence base of mostly (or all) low confidence studies decreases certainty. An
exception to this is an evidence base of studies in which the issues resulting in low
confidence are related to insensitivity. This may increase evidence certainty in cases
where an association is identified because the expected impact of study insensitivity
is towards the null.
An evidence base of mostly null findings where insensitivity is a serious concern
decreases certainty that the evidence is sufficient to support a lack of health effect or
association.
Decisions to increase certainty for other considerations in this table should generally
not be made if there are serious concerns for risk of bias.
Consistency
Similarity of findings for a given outcome (e.g., of a similar
direction) across independent studies or experiments, especially
when medium or high confidence, increases certainty. The increase
in certainty is larger when consistency is observed across
populations (e.g., geographical location) or exposure scenarios in
human studies, and across laboratories, species, or exposure
scenarios (e.g., route, timing) in animal studies. When seemingly
inconsistent findings are identified, patterns should be further
analyzed to discern if the inconsistencies can potentially be
explained based on study confidence, dose or exposure levels,
population, or experimental model differences, etc. This factor is
typically given the most attention during evidence synthesis.
Unexplained inconsistency [i.e., conflicting evidence: see (U.S. EPA, 2005a)l
decreases certainty. Generally, certainty should not be decreased if discrepant
findings can be reasonably explained by considerations such as study confidence
conclusions (including sensitivity); variation in population or species, sex, or lifestage
(including understanding of differences in pharmacokinetics); or exposure patterns
(e.g., intermittent versus continuous), levels (low versus high), or duration. Similar to
current recommendations in the Cochrane Handbook ffHiggins et al., 2022), see
Section 7.8.6], clear conflicts of interest (COI) related to funding source can be
considered as a factor to explain apparent inconsistency. For small evidence bases, it
may be hard to assess consistency. An evidence base of a single or a few studies
where consistency cannot be accurately assessed does not, on its own, increase or
decrease evidence certainty. Similarly, a reasonable explanation for inconsistency
does not necessarily result in an increase in evidence certainty.
Effect magnitude and
imprecision
Evidence of a large or concerning magnitude of effect can increase
certainty (generally only when observed in medium or high
confidence studies).
Judgments on effect magnitude and imprecision consider the
rarity and severity of the effect.
Certainty may be decreased if the findings are considered not likely to be biologically
significant. Effects that are small in magnitude might not be considered to be
biologically significant (adverse15) based on information such as historical responses
and variability. However, effects that appear to be of small magnitude may be
meaningful at the population level (e.g., IQ shifts); in such cases, certainty would not
be decreased.
Certainty may also be decreased for imprecision, particularly if there are only a few
studies available to evaluate consistency in effect magnitude across studies.
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Consideration
Increased evidence certainty
(of the human or animal evidence for hazard3)
Decreased evidence certainty
(of the human or animal evidence for hazard3)
Dose-response
Evidence of dose-response or exposure-response in high or
medium confidence studies increases certainty. Dose-response
may be demonstrated across studies or within studies, and it can
be dose- or duration-dependent. It may also not be a monotonic
dose-response (monotonicity should not necessarily be expected
as different outcomes may be expected at low vs. high doses or
long vs. short durations due to factors such as activation of
different mechanistic pathways, systemic toxicity at high doses, or
tolerance/acclimation). Sometimes, grouping studies by level of
exposure is helpful to identify the dose-response pattern.
Decreases in a response (e.g., symptoms of current asthma) after
a documented cessation of exposure also may increase certainty
in a relationship between exposure and outcome (this is primarily
applicable to epidemiology studies because of their observational
nature).
A lack of dose-response when expected based on biological understanding can
decrease certainty in the evidence. If the data are not adequate to evaluate a dose-
response pattern, however, then certainty is neither increased nor decreased.
In some cases, duration-dependent patterns in the dose-response can decrease
evidence certainty. Such patterns are generally only observable in experimental
studies. Specifically, the magnitude of effects at a given exposure level might decrease
with longer exposures (e.g., due to tolerance or acclimation). Or, effects might rapidly
resolve under certain experimental conditions (e.g., reversibility after removal of
exposure). As many reversible and short-lived effects can be of high concern, decisions
about whether such patterns decrease evidence certainty depend on considering the
pharmacokinetics of the chemical and the conditions of exposure [see (U.S. EPA,
1998a)l, endpoint severity, judgments regarding the potential for delayed or
secondary effects, the underlying mechanism(s) involved, as well as the exposure
context focus of the assessment (e.g., addressing intermittent or short-term
exposures).
Directness of
outcome/endpoint
measures
Not applicable
If the evidence base primarily includes outcomes or endpoints that are indirect
measures (e.g., biomarkers) of the unit of analysis, certainty (for that unit of analysis)
is typically decreased. Judgments to decrease certainty based on indirectness should
focus on findings that have an unclear linkage to an apical or clinical (adverse15)
outcome. Scenarios where the magnitude of the response is not considered to reflect
a biologically meaningful level of change (i.e., biological significance; see 'effect
magnitude and imprecision' row above) are not considered under indirectness.
Related to indirectness, certainty in the evidence may be decreased when the findings
are determined to be nonspecific to the hazard under evaluation. This consideration is
generally only applicable to animal evidence and the most common example is effects
only with exposures (level, duration) shown to cause excessive toxicity in that species
and lifestage (including consideration of maternal toxicity in developmental
evaluations). This does not apply when an effect is viewed as secondary to other
changes (e.g., effects on pulmonary function because of disrupted immune
responses).
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Consideration
Increased evidence certainty
(of the human or animal evidence for hazard3)
Decreased evidence certainty
(of the human or animal evidence for hazard3)
Coherence
Biologically related findings within or across studies, within an
organ system or across populations (e.g., sex), increase strength
(generally only when observed in medium or high confidence
studies). Certainty is further increased when a temporal or dose-
dependent progression of related effects is observed within or
across studies, or when related findings of increasing severity are
observed with increasing exposure.
Coherence across findings within a unit of analysis (e.g., consistent
changes in disease markers and biological precursors in exposed
humans) can increase certainty in the evidence for an effect.
Coherence within or across biologically related units of analysis
can also increase strength for a given (or multiple) unit(s) of
analysis. This considers certainty in the biological relationships
between the endpoints being compared, and the sensitivity and
specificity of the measures used.
Mechanistic support for, or biological understanding of, the
relatedness between different endpoints within (or across
different) units of analysis, can inform an understanding of
coherence.
An observed lack of expected coherent changes (e.g., in well-established biological
relationships) within or across biologically related units of analysis typically decrease
evidence strength. This includes mechanistic changes when included in the unit of
analysis. However, as described for decisions to increase strength, certainty in the
biological relationships between the endpoints being compared, and the sensitivity
and specificity of the measures used, need to be carefully examined. The decision to
decrease depends on the availability of evidence across multiple related endpoints for
which changes would be anticipated, and it considers factors (e.g., dose and duration
of exposure, strength of expected relationship) across the studies of related changes.
Other factors
Unusual scenarios that cannot be addressed by the considerations
above, e.g., read across inferences supporting the adversity of
observed changes.
Unusual scenarios that cannot be addressed by the considerations above, e.g., strong
evidence of publication bias.c
aWhile the focus is on identifying potential adverse human health effects (hazards) of exposure, these factors can also be used to increase or decrease certainty in the evidence
supporting lack of an effect (e.g., leading to a judgment of compelling evidence of no effect). The latter application is not explicitly outlined here.
bWithin this framework, evidence synthesis judgments reflect an interpretation of the evidence for) a hazard; thus, consideration of the adversity of the findings is an explicit
aspect of the analyses. To better define how adversity is evaluated, the consideration of adversity is broken into the two, sometimes related, considerations of the indirectness
of the outcome measures and the interpreted biological significance of the effect magnitude.
Publication bias involves the influence of the direction, magnitude, or statistical significance of the results on the likelihood of a paper being published; it can result from
decisions made, consciously or unconsciously, by study authors, journal reviewers, and journal editors (Dickersin, 1990). This may make the available evidence base
unrepresentative. However, publication bias can be difficult to evaluate (NTP, 2019) and should not be used as a factor that decreases certainty unless there is strong
evidence.
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A structured framework approach is used to draw evidence synthesis judgments for human
and animal evidence. Tables 8-3 and 8-4 (for human and animal evidence, respectively) provide the
example-based criteria that guide how to draw the strength of evidence judgments for each unit of
analysis within a health effect category and the terms used to summarize those judgments. These
terms are applied to human and animal evidence separately. The terms robust and moderate are
characterizations for judgments that the evidence (across studies) supports that the effect(s)
results from the exposure being assessed. These two terms are differentiated by the quality and
amount of information available to rule out alternative explanations for the results. For example,
repeated observations of effects by independent studies or experiments examining various aspects
of exposure or response (e.g., different exposure settings, dose levels or patterns, populations or
species, biologically related endpoints) result in a stronger certainty of evidence judgment. The
term slight indicates situations in which there is some evidence supporting an association within
the evidence stream, but substantial uncertainties in the data exist to prevent judgments that the
effect(s) can be reliably attributed to the exposure being assessed. Indeterminate reflects judgments
for a wide variety of evidence scenarios, including when no studies are available or when the
evidence from studies of similar confidence has a high degree of unexplained inconsistency.
Compelling evidence of no effect represents a rare situation in which extensive evidence across a
range of populations and exposures has demonstrated that no effects are likely to be attributable to
the exposure being assessed. This category is applied at the health effect level (e.g., hepatic effects)
rather than more granular units of analysis level to avoid giving the impression of confidence in
lack of a health effect when aspects of potential toxicity have not been adequately examined.
Reaching this judgment is infrequent because it requires both a high degree of confidence in the
conduct of individual studies, including consideration of study sensitivity, as well as comprehensive
assessments of outcomes and lifestages of exposure that adequately address concern for the hazard
under evaluation.
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Table 8-4. Framework for strength of evidence judgments from studies in
humans
Strength of
evidence
judgment
Description
Robust (ฉฉฉ)
...evidence in human
studies
(strong signal of
effect with very little
uncertainty)
A set of high or medium confidence independent studies (e.g., in different populations) reporting an
association between the exposure and the health outcome(s), with reasonable confidence that
alternative explanations, including chance, bias, and confounding, can be ruled out across studies.
The set of studies is primarily consistent, with reasonable explanations when results differ; the
findings are considered adverse (i.e., biologically significant and without notable concern for
indirectness); and an exposure response gradient is demonstrated. Additional supporting evidence,
such as associations with biologically related endpoints in human studies (coherence) or large
estimates of risk or severity of the response, can increase certainty, but are not required.
Supplemental evidence included in the unit of analysis (e.g., mechanistic studies in exposed humans
or human cells) may raise the strength of evidence to robust for a set of studies that otherwise would
be described as moderate. Such evidence not included in the unit of analysis can also inform
evaluations of the coherence of the human evidence, the directness of the outcome measures, and
the biological significance of the findings. Causality is inferred for a human evidence base of robust.
Moderate
(ฉฉO)
...evidence in human
studies
(signal of effect with
some uncertainty)
A set of evidence that does not reach the degree of certainty required for robust, but which includes
at least one high or medium confidence study reporting an association and additional information
increasing the strength of evidence. For multiple studies, there is primarily consistent evidence of an
association with reasonable support for adversity, but there may be some uncertainty due to
potential chance, bias, or confounding or because of the indirectness of some measures.
For a single study, there is a large magnitude or severity of the effect, or a dose-response gradient, or
other supporting evidence, and there are no serious residual methodological uncertainties.
Supporting evidence could include associations with related endpoints, including mechanistic
evidence from exposed humans when included within the unit of analysis.
When available and included in the unit of analysis, mechanistic data in humans that address the
above considerations may raise the strength of evidence to moderate for a set of studies that
otherwise would be described as slight. In exceptional cases, biological support from mechanistic
evidence in exposed humans may support raising the strength of evidence to moderate for evidence
that would otherwise be described as indeterminate.
Slight
(ฉOO)
...evidence in human
studies
(signal of effect with
large amount of
uncertainty)
One or more studies reporting an association between exposure and the health outcome, but
considerable uncertainty exists and supporting coherent evidence is sparse. In general, the evidence
is limited to a set of consistent low confidence studies, or higher confidence studies with significant
unexplained heterogeneity or other serious residual uncertainties. It also applies when one medium
or high confidence study is available without additional information strengthening the likelihood of a
causal association (e.g., coherent findings within the same study or from other studies). This category
serves primarily to encourage additional study where evidence does exist that might provide some
support for an association, but for which the evidence does not reach the degree of confidence
required for moderate.
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Strength of
evidence
judgment
Description
Indeterminate
(OOO)
...evidence in human
studies
(signal cannot be
determined for or
against an effect)
No studies available in humans or situations when the evidence is inconsistent and primarily of low
confidence. In addition, this may include situations where higher confidence studies exist, but there
are major concerns with the evidence base such as unexplained inconsistency, a lack of expected
coherence from a stronger set of studies, very small effect magnitude (i.e., major concerns about
biological significance), or uncertainties or methodological limitations that result in an inability to
discern effects from exposure. It also applies for a single low confidence study in the absence of
factors that increase certainty. A set of largely null studies could be concluded to be indeterminate if
the evidence does not reach the level required for Compelling evidence of no effect.
Compelling evidence
of no effect
(___>
...in human studies
(strong signal for
lack of an effect
with little
uncertainty)
A set of high confidence studies examining a reasonable spectrum of endpoints showing null results
(for example, an odds ratio of 1.0), ruling out alternative explanations including chance, bias, and
confounding) with reasonable confidence. Each of the studies should have used an optimal outcome
and exposure assessment and adequate sample size (specifically for higher exposure groups and for
susceptible populations). The set as a whole should include diverse sampling (across sexes [if
applicable] and different populations) and include the full range of levels of exposures that human
beings are known to encounter, an evaluation of an exposure response gradient, and an examination
of at-risk populations and lifestages.
Mechanistic data in humans that address the above considerations or that provide information
supporting the lack of an association between exposure and effect with reasonable confidence may
provide additional support for this judgment.
Table 8-5. Framework for strength of evidence judgments from studies in
animals
Strength of
evidence
judgment
Description
Robust (ฉฉฉ)
...evidence in
animal studies
(strong signal of
effect with very
little uncertainty)
The set of high or medium confidence, independent experiments (i.e., across laboratories, exposure
routes, experimental designs [for example, a subchronic study and a multigenerational study], or
species) reporting effects of exposure on the health outcome(s). The set of studies is primarily
consistent, with reasonable explanations when results differ (i.e., due to differences in study design,
exposure level, animal model, or study confidence), and the findings are considered adverse (i.e.,
biologically significant and without notable concern for indirectness).
At least two of the following additional factors in the set of experiments increase the strength of
evidence: coherent effects across multiple related endpoints (within or across biologically related
units of analysis and may include mechanistic endpoints); an unusual magnitude of effect, rarity, age
at onset, or severity; a strong dose-response relationship; or consistent observations across animal
lifestages, sexes, or strains. Mechanistic evidence from animals included in the unit of analysis or used
to assess coherence of findings in the animal evidence may raise the strength of evidence to robust for
a set of studies that otherwise would be described as moderate.
Moderate
(ฉฉO)
A set of evidence that does not reach the degree of certainty required for robust, but which includes
at least one high or medium confidence study and additional information increasing the strength of
evidence. For multiple studies or a single study, the evidence is primarily consistent or coherent with
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Strength of
evidence
judgment
Description
...evidence in
animal studies
(signal of effect
with some
uncertainty)
reasonable support for adversity, but there are notable remaining uncertainties (e.g., difficulty
interpreting the findings due to concerns for indirectness of some measures); however, these
uncertainties are not sufficient to reduce or discount the level of concern regarding the positive
findings and any conflicting findings are from a set of experiments of lower confidence.
The set of experiments supporting the effect provide additional information increasing the strength of
evidence, such as consistent effects across laboratories or species; coherent effects across multiple
related endpoints (may include mechanistic endpoints within the unit of analysis); an unusual
magnitude of effect, rarity, age at onset, or severity; a strong dose-response relationship; and/or
consistent observations across exposure scenarios (e.g., route, timing, duration), sexes, or animal
strains.
When available and included in the unit of analysis, mechanistic data in animals that address the
above considerations may raise the strength of evidence to moderate for a set of studies that
otherwise would be described as slight. In exceptional cases, strong biological support from
mechanistic studies may raise the strength of evidence to moderate for evidence that would
otherwise be described as indeterminate.
Slight
(ฉOO)
...evidence in
animal studies
(signal of effect
with large amount
of uncertainty)
One or more studies reporting an effect on an exposure on the health outcome, but considerable
uncertainty exists and supporting coherent evidence is sparse. In general, the evidence is limited to a
set of consistent low confidence studies, or higher confidence studies with significant unexplained
heterogeneity or other serious uncertainties (e.g., concerns about adversity) across studies. It also
applies when one medium or high confidence experiment is available without additional information
increasing the strength of evidence (e.g., coherent findings within the same study or from other
studies).
Biological evidence from mechanistic studies may also be independently interpreted as slight. This
category serves primarily to encourage additional study where evidence does exist that might provide
some support for an association, but for which the evidence does not reach the degree of confidence
required for moderate.
Indeterminate
(OOO)
...evidence in
animal studies
(signal cannot be
determined for or
against an effect)
No studies available in animals or situations when the evidence is inconsistent and primarily of low
confidence. In addition, this may include situations where higher confidence studies exist, but there
are major concerns with the evidence base such as unexplained inconsistency, a lack of expected
coherence from a stronger set of studies, very small effect magnitude (i.e., major concerns about
biological significance), or uncertainties or methodological limitations that result in an inability to
discern effects from exposure. It also applies for a single low confidence study in the absence of
factors that increase certainty. A set of largely null studies could be concluded to be indeterminate if
the evidence does not reach the level required for Compelling evidence of no effect.
Compelling
evidence of no
effect
(___>
...in animal studies
(strong signal for
lack of an effect
A set of high confidence experiments examining a reasonable spectrum of endpoints that
demonstrate a lack of biologically significant effects across multiple species, both sexes, and a broad
range of exposure levels. The data are compelling in that the experiments have examined the range of
scenarios across which health effects in animals could be observed, and an alternative explanation
(e.g., inadequately controlled features of the studies' experimental designs; inadequate sample sizes)
for the observed lack of effects is not available. Each of the studies should have used an optimal
endpoint and exposure assessment and adequate sample size. The evidence base should represent
both sexes and address potentially susceptible populations and lifestages.
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Strength of
evidence
judgment
Description
with little
uncertainty)
Mechanistic data in animals that address the above considerations or that provide information
supporting the lack of an association between exposure and effect with reasonable confidence may
provide additional support for this judgment.
8.2. EVIDENCE INTEGRATION
1 The phase of evidence integration combines animal and human evidence synthesis
2 judgments while also considering information on the human relevance of findings in animal
3 evidence, coherence across evidence streams ("cross-stream coherence"), information on
4 susceptible populations or lifestages, understanding of biological plausibility and MOA, and
5 possibly other critical inferences (e.g., read-across analyses) that generally draw on mechanistic
6 and other supplemental evidence (see Table 8-6). This analysis culminates in an evidence
7 integration judgment and narrative for each potential health effect category (i.e., each noncancer
8 health effect and specific type of cancer, or broader grouping of related outcomes as defined in the
9 evaluation plan). To the extent it can be characterized prior to conducting dose-response analyses,
10 exposure context is also provided.
Table 8-6. Considerations that inform evidence integration judgments
Judgment
Description
Human relevance
of findings
Used to describe and justify the interpretation of the relevance of the animal data to humans.
This can include consideration of mechanistic or other supplemental information. When
human evidence is lacking or has results that differ from animals, analyses of the mechanisms
underlying the animal response in relation to those presumed to operate in humans, and the
chemical's pharmacokinetics, can inform the extent to which the animal response is likely to
be relevant to humans and potentially strengthen overall confidence in the evidence
integration conclusion. Conversely, evidence for a mechanistic pathway that is expected to
only occur in animals and not in humans can provide support for a conclusion that the animal
evidence for an effect is not relevant to humans.
In the absence of chemical-specific evidence informing human relevance, the evidence
integration narrative will briefly describe the interpreted comparability of experimental
animal organs/systems to humans based on underlying biological similarity (e.g., thyroid
signaling processes are well conserved across rodents and humans). Generally, a high-level
systems summary should be possible for most encountered effects. In some cases, however,
it may be appropriate to use a statement such as, 'without evidence to the contrary, [health
effect described in the table] responses in animals are presumed to be relevant to humans.'
As noted in EPA guidelines (U.S. EPA. 2005a), there needs to be evidence or a biological
explanation to support an interpreted lack of human relevance for findings in animals, and
site concordance is neither expected nor required.
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Cross-stream
coherence
Addresses the concordance of findings known to be biologically related across human, animal,
and mechanistic studies, considering factors such as exposure timing and levels. Notably, for
many health effects (e.g., some nervous system and reproductive effects; cancer), it is not
necessary (or expected) that effects manifested in humans are identical to those observed in
animals, although this typically provides stronger evidence. For example, tumors in one
animal species can be predictive of carcinogenic potential in humans or other species, but not
necessarily at the same site. EPA guidelines and other resources (e.g., OECD guidance) are
consulted when drawing these inferences.
Mechanistic support for, or biological understanding of, the relatedness between different
outcomes (and the manner in which they are manifest) in different species can inform an
understanding of coherence across evidence streams. Evidence supporting a biologically
plausible mechanistic pathway across species adds coherence (see below).
Potential
susceptibility
Susceptible
populations and
lifestages
Used to summarize analyses relating to individual and social factors that may increase
susceptibility to exposure-related health effects in certain populations or lifestages, or to
highlight the lack of such information. These analyses are based on knowledge about the
health outcome or organ system affected and focus primarily on the influence of intrinsic
biological factors such as race/ethnicity, genetic variability, sex, lifestage, and pre-existing
health conditions (which can also have an extrinsic basis). Information on extrinsic factors
potentially influencing susceptibility (e.g., proximity to exposure; certain lifestyle factors
including subsistence living) are not considered in evidence integration judgments on
potential susceptibility; these exposure-focused factors are considered by risk managers after
the human health assessment is complete. Evaluation of potential susceptibility can also
include consideration of mechanistic and ADME evidence.
Biological
plausibility and
MOA
considerations
Support for the biological plausibility of an association between exposure and the health
effect increases evidence strength, particularly when observed across species. This may be
provided by data from experimental studies of mechanistic pathways, particularly when
support is provided for key events or is conserved across multiple components of the
pathway. Mechanisms or biological changes with broad scientific acceptance for their
relevance to chemical toxicity or the health effect (e.g., key characteristics, hallmarks of
cancer) may be used to organize the chemical-specific evidence and identify key events
leading from exposure to the health effect. For each key event and key event relationship, the
evidence is considered regarding the consistency of experimental data and the
generalizability, or likelihood of similarities (e.g., in presence or function) across species, as
well as the strength of the support for the biological mechanism.
Mechanistic evidence from well-conducted studies that demonstrates that the health effect is
unlikely to occur (i.e., species specific effects, irrelevant exposure conditions) can support a
judgment that the effects from animal or human studies are not biologically relevant, which
weakens the summary evidence integration judgment. Such a decision depends on an
evaluation of the strength of the information supporting vs. opposing biological plausibility, as
well as the strength of the health effect-specific findings (e.g., stronger health effect data
require more certainty in mechanistic evidence opposing plausibility). Importantly, because
understanding biological plausibility is dependent on expert knowledge and canonical
scientific knowledge, the lack of such understanding does not provide a rationale to decrease
the strength of the evidence for an effect (NTP. 2015; NRC. 2014).
These analyses are typically conducted separately to establish MOA understanding and
referenced in the evidence integration judgment. If sufficiently supported, MOA
understanding can serve to strengthen (e.g., strong support for mutagenicity) or weaken (e.g.,
critical dependence on a key event not likely to be operant in humans) evidence integration
judgments.
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Other critical Consideration of other evidence or non-chemical-specific information that informs evidence
inferences integration judgments (e.g., read across analyses, ADME understanding used to inform other
(optional) considerations; judgments on other health effects expected to be linked to the health effect
under evaluation; read-across analyses or inferences) may be separately described as "other
critical inferences."
Using a structured framework approach, one of five phrases is used to summarize the
evidence integration judgment based on the within evidence stream integration of the human and
animal evidence, and supplemental (mechanistic) evidence: evidence demonstrates, evidence
indicates, evidence suggests, evidence is inadequate, or strong evidence supports no effect (see
Table 8-7). The five integration judgment levels reflect the differences in the amount and quality of
the data that inform the evaluation of whether exposure may cause the health effect(s). As it is
assumed that any identified health hazards will only manifest given exposures of a certain type and
amount (e.g., a specific route; a minimal duration, periodicity, and level), the evidence integration
narrative and summary judgment levels include the generic phrase, "given sufficient exposure
conditions." This highlights that, for those assessment-specific health effects identified as potential
hazards, the exposure conditions associated with those health effects will be defined (as will the
uncertainties in the ability to define those conditions) during dose-response analysis. More than
one descriptor can be used when the evidence base is able to support that a chemical's effects differ
by exposure level or route (U.S. EPA. 2005a). The analyses and judgments are summarized in the
evidence profile table (see Table 8-1).
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Table 8-7. Framework for summary evidence integration judgments in the evidence integration narrative
Summary evidence integration judgment3
in narrative
Evidence integration
judgment level
Explanation and example scenarios'3
The currently available evidence demonstrates
that [chemical] causes [health effect] in
humans0 given sufficient exposure conditions.
This conclusion is based on studies of [humans
or animals] that assessed [exposure or dose]
levels of [range of concentrations or specific
cutoff level concentration01].
Evidence demonstrates
A strong evidence base demonstrating that [chemical] exposure causes [health effect] in humans.
This conclusion level is used if there is robust human evidence supporting an effect.
This conclusion level could also be used with moderate human evidence and robust animal
evidence if there is strong mechanistic evidence that MOAs and key precursors identified in
animals are anticipated to occur and progress in humans.
The currently available evidence indicates that
[chemical] likely causes [health effect] in
humans given sufficient exposure conditions.
This conclusion is based on studies of [humans
or animals] that assessed [exposure or dose]
levels of [range of concentrations or specific
cutoff level concentration].
Evidence indicates
(likelyฎ)
An evidence base that indicates that [chemical] exposure likely causes [health effect] in humans,
although there may be outstanding questions or limitations that remain, and the evidence is
insufficient for the higher conclusion level.
This conclusion level is used if there is robust animal evidence supporting an effect and slight-to-
indeterminate human evidence, or with moderate human evidence when strong mechanistic
evidence is lacking.
This conclusion level could also be used with moderate human evidence supporting an effect
and moderate-to-indeterminate animal evidence, or with moderate animal evidence supporting
an effect and moderate-to-indeterminate human evidence. In these scenarios, any uncertainties
in the moderate evidence are not sufficient to substantially reduce confidence in the reliability of
the evidence, or mechanistic evidence in the slight or indeterminate evidence base
(e.g., precursors) exists to increase confidence in the reliability of the moderate evidence.
The currently available evidence suggests
that [chemical] may cause [health effect] in
humans. This conclusion is based on studies
of [humans or animals] that assessed
[exposure or dose] levels of [range of
concentrations or specific cutoff level
concentration].
Evidence suggests
An evidence base that suggests that [chemical] exposure may cause [health effect] in humans, but
there are very few studies that contributed to the evaluation, the evidence is very weak or
conflicting, and/or the methodological conduct of the studies is poor.
This conclusion level is used if there is slight human evidence and indeterminate-to-slight
animal evidence.
This conclusion level is also used with slight animal evidence and indeterminate-to-slight
human evidence.
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Summary evidence integration judgment3
in narrative
Evidence integration
judgment level
Explanation and example scenarios'3
This conclusion level could also be used with moderate human evidence and sliaht or
indeterminate animal evidence, or with moderate animal evidence and slight or indeterminate
human evidence. In these scenarios, there are outstanding issues or uncertainties regarding the
moderate evidence (i.e., the synthesis judgment was borderline with slight), or mechanistic
evidence in the slight or indeterminate evidence base (e.g., null results in well-conducted
evaluations of precursors) exists to decrease confidence in the reliability of the moderate
evidence.
Exceptionally, when there is general scientific understanding of mechanistic events that result
in a health effect, this conclusion level could also be used if there is strong mechanistic
evidence that is sufficient to highlight potential human toxicity'in the absence of informative
conventional studies in humans or in animals (i.e., indeterminate evidence in both).
The currently available evidence is
inadequate to assess whether [chemical] may
cause [health effect] in humans.
Evidence inadequate
This conveys either a lack of information or an inability to interpret the available evidence for
[health effect]. On an assessment-specific basis, a single use of this "inadequate" conclusion level
might be used to characterize the evidence for multiple health effect categories (i.e., all health
effects that were examined and did not support other conclusion levels).8
This conclusion level is used if there is indeterminate human and animal evidence.
This conclusion level is_also used with slight animal evidence and compelling evidence of no
effect human evidence.
This conclusion level could also be used with sliaht-to-robust animal evidence and
indeterminate human evidence if strong mechanistic information indicated that the animal
evidence is unlikely to be relevant to humans.
A conclusion of inadequate is not a determination that the agent does not cause the indicated
health effect(s). It simply indicates that the available evidence is insufficient to reach
conclusions.
Strong evidence supports no effect in
humans. This conclusion is based on studies
of [humans or animals] that assessed
[exposure or dose] levels of [range of
concentrations].
Strong evidence
supports no effect
This represents a situation in which extensive evidence across a range of populations and exposure
levels has identified no effects/associations. This scenario requires a high degree of confidence in
the conduct of individual studies, including consideration of study sensitivity, and comprehensive
assessments of the endpoints and lifestages of exposure relevant to the heath effect of interest.
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Summary evidence integration judgment3
in narrative
Evidence integration
judgment level
Explanation and example scenarios'3
This conclusion level is used if there is compelling evidence of no effect inhuman studies and
compelling evidence of no effect to indeterminate in animals.
This conclusion level is also used if there is indeterminate human evidence and compelling
evidence of no effect animal evidence in models concluded to be relevant to humans.
This conclusion level could also be used with compelling evidence of no effect in human studies
and moderate to robust animal evidence if strong mechanistic information indicated that the
animal evidence is unlikely to be relevant to humans.
aEvidence integration judgments are typically developed at the level of the health effect when there are sufficient studies on the topic to evaluate the evidence at that level;
this should always be the case for "evidence demonstrates" and "strong evidence supports no effect," and typically for "evidence indicates (likely)." However, some
databases only allow for evaluations at the category of health effects examined; this will more frequently be the case for conclusion levels of "evidence suggests" and
"evidence inadequate." A judgment of "strong evidence supports no effect" is drawn at the health effect level.
terminology of "is" refers to the default option; terminology of "could also be" refers to situational options dependent on mechanistic understanding.
cln some assessments, these conclusions might be based on data specific to a particular lifestage of exposure, sex, or population (or another specific group). In such cases, this
would be specified in the narrative conclusion, with additional detail provided in the narrative text. This applies to all conclusion levels.
dlf concentrations cannot be estimated, an alternative expression of exposure level such as "occupational exposure levels" is provided. This applies to all conclusion levels.
eFor some applications, such as benefit-cost analysis, to better differentiate the categories of "evidence demonstrates" and "evidence indicates," the latter category should be
interpreted as evidence that supports an exposure-effect linkage that is likely to be causal.
'Scientific understanding of adverse outcome pathways (AOPs) and of the human implications of new toxicity testing methods (e.g., from high-throughput screening, from
short-term in vivo testing of alternative species or from new in vitro testing) will continue to increase. This may make possible the development of hazard conclusions when
there are mechanistic or other relevant data that can be interpreted with a similar level of confidence to positive animal results in the absence of conventional studies in
humans or in animals.
Specific narratives for each of these health effects may also be deemed unnecessary.
1
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For evaluations of carcinogenicity, consistent with EPA's cancer guidelines (U.S. EPA.
2005a), one of EPA's standardized cancer descriptors is used to describe the overall potential for
carcinogenicity within the evidence integration narrative for carcinogenicity. These descriptors are:
(1) carcinogenic to humans, (2) likely to be carcinogenic to humans, (3) suggestive evidence of
carcinogenic potential, (4) inadequate information to assess carcinogenic potential, or (5) not
likely to be carcinogenic to humans. The standardized cancer descriptors will often align with the
evidence integration judgements (i.e., "evidence demonstrates" aligns with "carcinogenic to
humans") but not in all cases. For example, the evidence integration judgements are generally used
for individual tumor or cancer types and the standardized EPA descriptors are used to characterize
overall cancer hazard.
For each type of cancer evaluated (e.g., lung cancer, renal cancer) or sets of related cancer
types, an evidence integration narrative and summary judgment level are provided as described
above for noncancer health effects. When considering evidence on carcinogenicity across human
and animal evidence, site concordance is not required (U.S. EPA. 2005a). If a systematic review of
more than one cancer type was conducted, then the strongest evidence integration judgment(s) is
used as the basis for selecting the standardized cancer descriptor in accordance with the EPA
cancer guidelines fU.S. EPA. 2005al.
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9.DOSE-RESPONSE ASSESSMENT: SELECTING
STUDIES AND QUANTITATIVE ANALYSIS
9.1. OVERVIEW
Selection of specific data sets for dose-response assessment and performance of the
dose-response assessment is conducted after hazard identification is complete and involves
database- and chemical-specific biological judgments. A number of EPA guidelines and support
documents detail data requirements and other considerations for dose-response modeling,
especially EPA's Benchmark Dose Technical Guidance fU.S. EPA. 2012bl. EPA's Review of the
Reference Dose and Reference Concentration Processes fU.S. EPA. 2005a. 20021. Guidelines for
Carcinogen Risk Assessment fU.S. EPA. 2005a). and Supplemental Guidance for Assessing
Susceptibility from Early-Life Exposure to Carcinogens fU.S. EPA. 2005b). This section of the protocol
provides an overview of considerations for conducting the dose-response assessment, particularly
statistical considerations specific to dose-response analysis that support quantitative risk
assessment. Importantly, these considerations do not supersede existing EPA guidelines.
For IRIS assessments, dose response- assessments are typically performed for both
noncancer and cancer hazards, and for both oral and inhalation routes of exposure following
chronic exposure9 to the chemical of interest, if supported by existing data. For noncancer hazards,
an inhalation reference concentration (RfC) or oral reference dose (RfD) will be derived, if possible.
A reference value (i.e., RfC or RfD) is an estimate, with uncertainty spanning perhaps an order of
magnitude, of an exposure to the human population (including susceptible populations and
lifestages) that is likely to be without an appreciable risk of deleterious health effects over a lifetime
[fU.S. EPA. 20021 see section 4.2], In addition to an RfC or RfD, this assessment will attempt to
derive organ- or system-specific RfCs (osRfCs) or RfDs (osRfDs) when the data are sufficiently
strong (i.e., with rare exception as described below, noncancer conclusions of evidence
demonstrates or evidence indicates [likely]). In addition to chronic RfCs or chronic RfDs, when
feasible and if the available data are appropriate for doing so, the assessments will derive a less-
than-lifetime toxicity value (a "subchronic" reference value) for noncancer hazards. Both less-than-
lifetime and hazard-specific values may be useful to EPA risk assessors within specific decision
contexts.
9Dose-response assessments may also be conducted for shorter durations, particularly if the evidence base
for a chemical indicates health effects associated with shorter exposures to the chemical fU.S. EPA. 20021.
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When low-dose linear extrapolation for cancer effects is supported, particularly for
chemicals with direct mutagenic activity or those for which the data indicate a linear component
below the point of departure (POD), an inhalation unit risk (IUR) or oral cancer slope factor (CSF)
facilitates estimation of human cancer risks. Low-dose linear extrapolation is also used as a default
when the data are insufficient to establish the mode of action fU.S. EPA. 2005al An IUR is a
plausible upper-bound lifetime cancer risk from chronic inhalation of a chemical per unit of air
concentration (expressed as ppm or ng/m3); a CSF is a plausible upper bound lifetime cancer risk
from chronic oral exposure to a chemical.
The derivation of toxicity values depends on the nature of the hazard conclusion.
Specifically, EPA generally conducts dose-response assessments and derives cancer values for
chemicals that are classified as carcinogenic or likely to be carcinogenic to humans. When there is
suggestive evidence of carcinogenic potential to humans, EPA generally would not conduct a
dose-response assessment and derive a cancer value. Similarly, for noncancer outcomes, dose-
response is conducted based on having stronger evidence of a hazard (generally, "evidence
demonstrates" and "evidence indicates [likely]". When the noncancer outcome is considered evidence
suggests of potential hazard to humans, EPA generally would not conduct a dose-response
assessment and derive a RfC or RfD. Cases where suggestive evidence might be used to develop
cancer risk estimates or a noncancer toxicity value include when the evidence base includes a
well-conducted study (overall medium or high confidence for the outcome) and quantitative
analyses may be useful for some purposes, (e.g., providing a sense of the magnitude and uncertainty
of potential risks, ranking potential hazards, or setting research priorities) (U.S. EPA. 2005a).
9.2. SELECTING STUDIES FOR DOSE-RESPONSE ASSESSMENT
9.2.1. Hazard and MOA Considerations for Dose Response
The assessment presents a summary of hazard identification conclusions to transition to
dose response considerations, highlighting (1) information used to inform the selection of
outcomes or broader health effect categories for which toxicity values will be derived, (2) whether
toxicity values can be derived to protect specific populations or lifestages, (3) how dose response
modeling will be informed by pharmacokinetic information, and (4) the identification of
biologically based BMR levels (where possible and supported by the data). The pool of outcomes
and study-specific endpoints is discussed to identify which categories of effects and study designs
are considered the strongest and most appropriate for quantitative assessment of a given health
effect, particularly among the studies that exemplify the study attributes summarized in Table 9-1.
Also considered is whether there are opportunities for quantitative evidence integration.
Examples of quantitative integration, from simplest to more complex, include (1) combining results
for an outcome across sex (within a study); (2) characterizing overall toxicity, as in combining
effects that comprise a syndrome, or occur on a continuum (e.g., precursors and eventual overt
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toxicity, benign tumors that progress to malignant tumors); and (3) conducting a meta-analysis or
meta-regression of all studies addressing a category of important health effects.
Some studies that are used qualitatively for hazard identification may or may not be useful
quantitatively for dose-response assessment due to such factors as the lack of quantitative
measures of exposure or lack of variability measures for response data. If the needed information
cannot be located, semiquantitative analysis may be feasible (e.g., via NOAEL/LOAEL). In this
assessment, specific datasets considered for dose-response analysis will be summarized in a
tabular format that includes rationales for decisions to proceed (or not) for POD derivation. Table
9-2 presents an example format for how these decisions can be documented, although the specifics
in the naphthalene assessment are likely to differ.
In addition, mechanistic evidence that influences the dose-response analyses will be
highlightedfor example, evidence related to susceptibility or potential shape of the dose-response
curve (i.e., linear, nonlinear, or threshold model). Mode(s) of action summarized as part of hazard
identification will be used to highlight information relevant to understanding overall risk. Biological
considerations relevant to dose-response for cancer are:
Is there evidence for direct mutagenicity?
Does tumor latency decrease with increasing exposure?
If there are multiple tumor types, which cancers have a longer latency period?
Is incidence data available (incidence data are preferred to mortality data)?
Were there different background incidences in different (geographic) populations?
While benign and malignant tumors of the same cell of origin are generally evaluated
together, was there an increase only in malignant tumors?
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Table 9-1. Attributes used to evaluate studies for derivation of toxicity values (in addition to the health effect
category-specific evidence integration judgment)
Considerations
Study attributes
Human studies
Animal studies
Study confidence
High or medium confidence studies are highly preferred over low confidence studies. The available high and medium
confidence studies are further differentiated based on the study attributes below as well as a reconsideration of the specific
limitations identified and their potential impact on dose-response analyses.
Rationale for choice of
species
Human data are preferred over animal data to eliminate
interspecies extrapolation uncertainties (e.g., in
pharmacodynamics, relevance of specific health
outcomes to humans).
Animal studies provide supporting evidence when adequate human
studies are available and are considered principal studies when
adequate human studies are not available. For some hazards, studies
of particular animal species known to respond similarly to humans
would be preferred over studies of other species.
Relevance of
exposure
paradigm
Exposure
route
Studies involving human environmental exposures (oral,
inhalation).
Studies by a route of administration relevant to human
environmental exposure are preferred. A validated pharmacokinetic
or PBPK model can also be used to extrapolate across exposure
routes.
Exposure
durations
When developing a chronic toxicity value, chronic or subchronic studies are preferred over studies of acute exposure durations.
Exceptions exist, such as when a susceptible population or life stage is more sensitive in a particular time window (e.g.,
developmental exposure).
Exposure
levels
Exposures near the range of typical environmental human exposures are preferred. Studies with a broad exposure range and
multiple exposure levels are preferred to the extent that they can provide information about the shape of the
exposure-response relationship (see the EPA Benchmark Dose Technical Guidance, see section 2.1.1) and facilitate
extrapolation to more relevant (generally lower) exposures.
Subject selection
Studies that provide risk estimates in the most susceptible groups are preferred. Attempts are made to highlight where it might
be possible to develop separate risk estimates for a specific population or life stage, or determine whether evidence is available
to select a data-derived uncertainty factor (UF).
Controls for possible
confounding3
Studies with a design (e.g., matching procedures, blocking) or analysis (e.g., covariates or other procedures for statistical
adjustment) that adequately address the relevant sources of potential critical confounding for a given outcome are preferred.
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Study attributes
Considerations
Human studies
Animal studies
Measurement of exposure
Studies that can reliably distinguish between levels of
exposure in a time window considered most relevant
for development of a causal effect are preferred.
Exposure assessment methods that provide
measurements at the level of the individual and that
reduce measurement error are preferred.
Measurements of exposure should not be influenced by
knowledge of health outcome status.
Studies providing actual measurements of exposure (e.g., analytical
inhalation concentrations vs. target concentrations) are preferred.
Relevant internal dose measures may facilitate extrapolation to
humans, as would availability of a suitable animal PBPK model in
conjunction with an animal study reported in terms of administered
exposure.
Measurement of health
outcome(s)
Studies that can reliably distinguish the presence or absence (or degree of severity) of the outcome are preferred. Outcome
ascertainment methods using generally accepted or standardized approaches are preferred.
Studies with individual data are preferred in general. Examples include: to characterize experimental variability more
realistically, to characterize overall incidence of individuals affected by related outcomes (e.g., phthalate syndrome).
Among several relevant health outcomes, preference is generally given to those with greater biological significance. When
there are multiple endpoints for an organ/system, characterizing the overall impact on this organ/system is considered. For
example, if there are multiple histopathological alterations relevant to liver function changes, liver necrosis may be selected as
the most representative endpoint to consider for dose-response analysis. For cancer types, consideration is given to the overall
risk of multiple types of tumors. Multiple tumor types (if applicable) are discussed, and a rationale given for any grouping.
Study size and design
Preference is given to studies using designs reasonably expected to have power to detect responses of suitable magnitude.15
This does not mean that studies with substantial responses but low power would be ignored, but that they should be
interpreted in light of a confidence interval or variance for the response. Studies that address changes in the number at risk
(through decreased survival, loss to follow-up) are preferred.
aAn exposure or other variable that is associated with both exposure and outcome but is not an intermediary between the two.
bPower is an attribute of the design and population parameters, based on a concept of repeatedly sampling a population; it cannot be inferred post hoc using
data from one experiment (Hoenig and Heisev, 2001).
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Table 9-2. Specific example of presenting endpoints considered for dose-response modeling and derivation of
points of departure
Endpoint
Study reference/
confidence
Exposure route
and duration
Human population
or Test species and
strain
Lifestage and Sex
POD
derivation
Rationale
Endocrine Effects (hazard judgment of evidence indicates [likely])
Decreased
serum total
T4
[study 1 author, year, HERO
ID]; high confidence
Oral Gavage,
90 days
S-D rat
Adult female
Yes V
Decreases in total T4 in females were dose-
dependent and of a large magnitude (36-53%
reduction at >3.12 mg/kg-d); effects in males
were not prioritized due to body weight loss at
the doses causing significant decreases in total
T4.
[study 1 author, year, HERO
ID]; high confidence
Oral Gavage,
90 days
S-D rat
Adult male
No, X
Increased
thyroid
follicular
hypertrophy
[study 1 author, year, HERO
ID]; high confidence
Oral Gavage,
90 days
S-D rat
Adult males and
females
Yes S
Increases in thyroid follicular hypertrophy
incidence were dose-dependent in both sexes at
doses that did not affect body weight.
Thyroid
weight
[study 2 author, year, HERO
ID]; medium confidence
Oral Gavage,
90 days
F344 rat
Adult males and
females
No, X
Increased thyroid weights were only observed at
doses over an order of magnitude higher than
those affecting thyroid hormones and
histopathology in the other subchronic study
(note: this study only tested much higher doses)
1
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9.3. CONDUCTING THE DOSE-RESPONSE ASSESSMENT
EPA uses a two-step approach for dose-response assessment that distinguishes analysis of
the dose-response data in the range of observation from any inferences about responses at lower,
generally more environmentally relevant, exposure levels [fU.S. EPA. 2012b. 2005a) see Section 3]:
Within the observed dose range, the preferred approach is to use dose-response modeling
to incorporate as much of the data set as possible into the analysis for the purpose of deriving a
POD; see Section 9.3.1 for more details.
Derivation of cancer risk estimates or reference values nearly always involves extrapolation
to exposures lower than the POD and is described in more detail in Sections 9.3.2 and 9.3.3,
respectively.
When sufficient and appropriate human data and laboratory animal data are both available
for the same outcome, human data are generally preferred for the dose-response assessment
because their use eliminates the need to perform interspecies extrapolations.
For noncancer analyses, IRIS assessments typically derive a candidate value from each
suitable data set, whether for human or animal. Evaluating these candidate values grouped within a
particular organ/system yields a single organ/system-specific reference value for each
organ/system under consideration. Next, evaluation of these organ/system-specific reference
values results in the selection of a single overall reference value to cover all health outcomes across
all organs/systems. While this overall reference value is the focus of the assessment, the
organ/system-specific reference values can be useful for subsequent cumulative risk assessments
that consider the combined effect of multiple agents acting at a common organ/system.
For cancer analyses, if there are multiple tumor types in a study population (human or
animal), final cancer risk estimates will typically address overall cancer risk (i.e., the risk of
developing any combination of modeled tumor types).
9.3.1. Dose-Response Analysis in the Range of Observation
Empirical dose-response modeling is used to fit the data (on the apical outcomes or a key
precursor events) in the ranges of observation. For this purpose of empirical dose-response
modeling, EPA has developed a standard set of models (https://www.epa.gov/bmds) that can be
applied to typical dichotomous and continuous data sets, including those that are nonlinear. In
situations where there are alternative models with significant biological support, the users of the
assessment can be informed by the presentation of these alternatives along with the models'
strengths and uncertainties. EPA has developed guidelines on modeling dose-response data,
assessing model fit, selecting suitable models, and reporting modeling results [see the EPA
Benchmark Dose Technical Guidance (U.S. EPA. 2012b)].
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U.S. EPA Benchmark Dose Software (BMDS) is designed to model dose-response datasets in
accordance with EPA Benchmark Dose Technical Guidance (U.S. EPA. 2012b). For noncancer (and
nonlinear cancer), a benchmark dose lower confidence limit (BMDL) is computed from a model
selected from the BMDS suite of models using statistical and graphical criteria. Linear analysis of
cancer datasets is generally based on the multistage model, with degree selected following a U.S.
EPA Statistical Workgroup technical memo available on the BMDS website
(https://cfpub.epa.gov/ncea/bmds/recordisplay.cfm?deid=308382). Modeling of cancer data may
in some cases involve additional, specialized methods, particularly for multiple tumors or early
removal from observation (due to death or morbidity). Additional judgments or alternative
analyses may be used if initial modeling procedures fail to yield results in reasonable agreement
with the data. For example, modeling may be restricted to the lower doses, especially if there is
competing toxicity at higher doses.
For noncancer (and nonlinear cancer) datasets, EPA recommends (1) application of a
preferred set of models that use maximum likelihood estimation (MLE) methods (default models in
BMDS) and (2) selection of a POD from a single model based on criteria designed to limit model
selection subjectivity (auto-implemented in BMDS version 3 and higher). For the linear analysis of
cancer datasets, EPA recommends (1) application of the Multistage MLE model; (2) selection of a
single Multistage degree; and (3) in cases where tumors are observed in multiple organ systems,
use of a multi-tumor model (i.e., MS-Combo) that appropriately estimates combined tumor risk
(both (2) and (3) are available in BMDS).10
Version 3.0 and higher of BMDS also provides an alternative modeling approach that uses
Bayesian model averaging for dichotomous modeling average (DMA). EPA makes DMA available as
alternative approaches but has not yet finalized guidelines for their use.
For each modeled dataset for an outcome, a POD from the observed data should be
estimated to mark the beginning of extrapolation to lower doses. The POD is an estimated dose
(expressed in human equivalent terms) near the lower end of the observed range without
significant extrapolation to lower doses. For linear extrapolation of cancer risk, the POD is used to
calculate an OSF or IUR, and for nonlinear extrapolation, the POD is used in calculating an RfD or
RfC.
The selection of the response level at which the POD is calculated is guided by the severity
of the endpoint If linear extrapolation is used, selection of a response level corresponding to the
point of departure is not highly influential, so standard values near the low end of the observable
range are generally used (for example, 10% extra risk for cancer bioassay data, 1% for
epidemiologic data, lower for rare cancers). Nonlinear approaches consider both statistical and
10 The Multistage degree selection process outlined in the memo is auto-implemented in the BMDS multi-
tumor model, which can be run on one or more tumor data sets, but only the noncancer model selection
process is auto-implemented for individual Multistage model runs in the current version, BMDS 3.3).
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biologic considerations. For dichotomous data, a response level of 10% extra risk is generally used
for minimally adverse effects, 5% or lower for more severe effects or effects observed in studies
with increased statistical sensitivity. Lower BMRs are often supported for developmental toxicity
studies. For continuous data, a response level is ideally based on an established definition of
biologic significance. In the absence of such definition, one control standard deviation from the
control mean is often used for minimally adverse effects, and one-half standard deviation for more
severe effects. As with dichotomous endpoints, lower BMRs may also be supported for endpoints
observed in studies with greater statistical sensitivity (e.g., developmental toxicity studies). The
point of departure is the 95% lower bound on the dose associated with the selected response level.
EPA has developed standard approaches for determining the relevant dose to be used in the
dose-response modeling in the absence of appropriate pharmacokinetic modeling. These standard
approaches also facilitate comparison across exposure patterns and species:
Intermittent study exposures are standardized to a daily average over the duration of
exposure. For chronic effects, daily exposures are averaged over the lifespan. Exposures
during a critical period, however, are not averaged over a longer duration [fU.S. EPA.
2005a), see section 3.1.1; fU.S. EPA. 19911. see section 3.2], Note that this will typically be
done after modeling because the conversion is linear.
Doses are standardized to equivalent human terms to facilitate comparison of results from
different species. Oral doses are scaled allometrically using mg/kg3/4day as the equivalent
dose metric across species. Allometric scaling pertains to equivalence across species, not
across life stages, and is not used to scale doses from adult humans or mature animals to
infants or children [fU.S. EPA. 2011a. 2005a),see Section 3.1.3], Inhalation exposures are
scaled using dosimetry models that apply species-specific physiologic and anatomic factors
and consider whether the effect occurs at the site of first contact or after systemic
circulation [fU.S. EPA. 2012a. 19941. see Section 3],
It can be informative to convert doses across exposure routes. If this is done, the assessment
describes the underlying data, algorithms, and assumptions [fU.S. EPA. 2005al. see Section
3.1.4],
In the absence of study specific data on, for example, intake rates or body weight, EPA has
developed recommended values for use in dose response analysis fU.S. EPA. 19881.
The preferred approach for dosimetry extrapolation from animals to humans is through
PBPK modeling. As explained in Section 9.3.1 and Appendix C.2. 6.4, EPA has selected the
naphthalene PBPK model of Kapraun etal. (20201 to compute internal dose metrics
relevant to various toxicity studies. The same model will be used to compute human
equivalent doses and/or concentrations.
Briefly, PBPK model simulations will be used to estimate internal dose metrics
corresponding to the applied doses for each experimental animal bioassay. By simulating
the exposure scenario for each toxicity study (e.g., 6 hours/day, 5 day/week inhalation
exposure), the resulting internal dose metric effectively accounts for the difference between
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the actual exposure pattern and a nominal 24 hour/day, 7 day/week exposure. The set of
internal dose metrics for each toxicity study and endpoint can then be used in dose-
response analysis to identify a BMDL or other point-of-departure (POD) for that study. The
human version of the PBPK model can then be used to estimate the exposure concentration
in air which, given continuous (24 hour/day, 7 day/week) inhalation exposure, would result
in a given internal dose POD. Any remaining uncertainty factors, including the factor of 10
for human inter-individual variability (UFH), will then be applied for derivation of the HECs.
If needed, a similar approach can be applied for oral-to-inhalation route extrapolation for
endpoints where toxicity data are available from oral dosimetry studies but not from
inhalation.
9.3.2. Dose Metrics
EPA will use the model of Kapraun et al. f20201 to compute internal dose metrics relevant
to various toxicity studies. In particular, the five-dose metrics listed in Table 9-3 will be considered.
Among the dose metrics described in Table 9-3Error! Reference source not found. DM1, DM2,
and DM3 should be relevant when the health effect of interest occurs in the DO tissue. DM1 and
DM2 reflect an assumption that it is the concentration or delivered dose of naphthalene, itself, that
is most predictive of DO toxicity, while DM3 may be more relevant when the health effect occurs in
the DO tissue but is correlated more directly with metabolite dose rather than dose of the parent
chemical (i.e., naphthalene). DM4 is a general-purpose measure of internal dose and should be
relevant when the health effect correlates with systemic, rather than site-specific, dose. Similarly,
DM5 is a measure of systemic internal dose, but it should be most relevant when the health effect
correlates with metabolite dose rather than dose of the parent chemical. One or more of the five
dose metrics described inTable 9-3. Internal dose metrics considered for use in assessing dose-
response relationships for naphthalene Appendix C.2. will be used to conduct dose-response
analysis for each health effect to obtain a "benchmark dose" or point of departure. Reverse
dosimetry (incorporating % body mass scaling for the rate-of-delivery or rate-of-metabolism dose
metrics DM2, DM3, and DM5) will then be used to compute a human equivalent external
concentration (or oral dose) that corresponds to each benchmark dose.
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Table 9-3. Internal dose metrics considered for use in assessing dose-
response relationships for naphthalene
Abbreviation
Description
DM 1
Average naphthalene concentration in dorsal olfactory (DO) tissue (ng/mL) (i.e., the total
naphthalene mass (ng) in the anterior dorsal olfactory tissue (DOl) and posterior dorsal
olfactory tissue (D02) is computed throughout the simulation and the average concentration
is calculated as the area under the curve divided by the total elapsed time and the total
volume of DOl and D02)
DM 2
Average rate of delivery of naphthalene to DO tissue (ng/cm2/d) (i.e., the total rate of mass
transfer (ng/d) to DOl and D02 is computed throughout the simulation and the average rate
is calculated as the area under the curve divided by the total elapsed time and the total
surface area of DOl and D02)
DM 3
Average rate of metabolite production in DO tissue (ng/mL/d) (i.e., the rate at which
metabolites are produced in DOl and D02 per unit volume are computed throughout the
simulation and the average rate is calculated as the area under the curve divided by the total
elapsed time)
DM4
Average naphthalene concentration in blood (ng/mL) (i.e., the total naphthalene mass (|jg) in
the blood is computed throughout the simulation and the average concentration is calculated
as the area under the curve divided by the total elapsed time and the volume of the blood)
DM 5
Average rate of metabolite production in the whole body (ng/kg-d) (i.e., the total rate at
which metabolites are produced (ng/d) in olfactory tissue, liver, and other regions of the body
are computed throughout the simulation and the average rate is calculated as the area under
the curve divided by the total elapsed time divided by the body mass)
For a given toxicological endpoint, the choice of dose metric will be based primarily on
biological considerations when possible. In particular, the decision will be based on evidence as to
whether the parent (naphthalene) or a metabolite is expected to be the driver of a given toxic effect
Mechanistic data for related toxic effects (e.g., cytotoxicity in hepatocytes vs. respiratory cells) or
structurally similar chemicals may also be considered. When dose-response data from multiple
studies are available, especially when the dosing regimen or route of administration are varied, a
dose metric that explains apparent differences in the response vs. unadjusted dose relationships
will be selected. Thus, the extent to which use of a particular dose metric yields consistency in the
dose-response relationship will be used to select a dose metric for the purposes of this assessment
In the event that no mechanistic data are available to inform the choice of dose metric, if
only a single dose-response study is available for a given endpoint, or if all existing studies are
inherently self-consistent due to similarity of study design, then consistency of the dose metric vs.
exposure relationship predicted by the PBPK model for a given dose metric and the observed
toxicological response vs. exposure relationship can also be evaluated. For example, metabolic
saturation leads to a concave down (negative second derivative) relationship curve for metabolite
dose vs. exposure and a concave up (positive second derivative) relationship curve for parent
chemical concentration vs. exposure. If the resulting nonlinearity is strong and a similar saturation
or concavity occurs in the dose-response curve for a toxic endpoint in the same exposure range, the
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consistency between one dose metric option and the dose-response nonlinearity indicates which
metric is a better predictor of risk.
However, caution is needed in comparing nonlinearity in the dose vs. exposure relationship
with nonlinearity in the response vs. exposure relationship, as nonlinearity in the dose-response
relationship can occur due to pharmacodynamic mechanisms that are not related to dosimetry. A
modest difference in a statistical correlation coefficient or other measure of goodness of fit is not
considered strong evidence for the choice of one dose metric over another. In the absence of
compelling mechanistic or exposure-dose-response evidence, the level of uncertainty in the dose
metric will also be considered. For example, with respect to CFD-PBPK model predictions, there is
less uncertainty in the delivered dose to the olfactory tissue than in the tissue concentration or rate
of metabolism in that tissue. The degree to which modeling involving alternate dose metrics yields
health protective results (e.g., when a dose metric specific human equivalent dose leads to a lower
RfC than does using the nominal dose) will be considered along with the level of uncertainty in each
metric.
9.3.3. Dosimetric Modeling Summary
Existing PBPK and inhalation dosimetry models for naphthalene (which are summarized in
Appendix D) were identified through a literature search. Of these, the model of Kapraun et al.
f20201 was identified as the best for dosimetric applications as it met EPA's quality evaluation
criteria, although other dosimetric models have distinct features which are of potential scientific
value. Five potentially useful dose metrics were presented in the preceding section and methods for
selecting from among them have been proposed. However, as the naphthalene assessment
progresses, new information concerning related biology or toxicity mechanisms may be discovered
and such information may suggest that alternative model choices or dose metrics should be used or
that the proposed methods for estimating human equivalent inhaled concentrations (or oral doses)
should be modified. If this is the case, the dosimetry methods proposed for naphthalene in this
document may be adjusted.
9.3.4. Extrapolation: Slope Factors and Unit Risk
An OSF or IUR facilitates estimation of human cancer risks when low dose linear
extrapolation for cancer effects is supported, particularly for chemicals with direct mutagenic
activity or those for which the data indicate a linear component below the POD. Low-dose linear
extrapolation is also used as a default when the data are insufficient to establish the mode of action
(U.S. EPA. 2005a). If data are sufficient to ascertain one or more modes of action consistent with
low-dose nonlinearity, or to support their biological plausibility, low-dose extrapolation may use
the reference value approach when suitable data are available (U.S. EPA. 2005a): see Section 11.2.3
below.
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9.3.5. Extrapolation: Reference Values
Reference value derivation is EPA's most frequently used type of nonlinear extrapolation
method. Although it is most commonly used for noncancer effects, this approach is also used for
cancer effects if there are sufficient data to ascertain the MOA and conclude that it is not linear at
low doses. For these cases, reference values for each relevant route of exposure are developed
following EPA's established practices [fU.S. EPA. 2005a). see Section 3.3.4],
For each data set selected for reference value derivation, reference values are estimated by
applying relevant adjustments to the PODs to account for the conditions of the reference value
definitionfor human variation, extrapolation from animals to humans, extrapolation to chronic
exposure duration, and extrapolation to a minimal level of risk (if not observed in the data set). The
assessment will discuss the scientific bases for estimating these data-based adjustments and UFs:
Animal-to-human extrapolation (UFa). If animal results are used to make inferences about
humans, the candidate toxicity value incorporates cross-species differences, which may
arise from differences in pharmacokinetics or pharmacodynamics. Typically, the
pharmacokinetic and pharmacodynamic portions are considered to address an equivalent
amount of the total uncertainty factor (i.e., each contributing 10ฐ5 or "3" towards the default
UFa of 10). If the POD is standardized to equivalent human terms or is based on
pharmacokinetic or dosimetry modeling fU.S. EPA. 2014a. 2011al. a factor of 10ฐ5 (rounded
to 3) is applied to account for the remaining uncertainty involving pharmacokinetic and
pharmacodynamic differences. If a biologically based model adjusts fully for
pharmacokinetic and pharmacodynamic differences across species, a factor of 1 is applied.
Similarly, although this is not a common scenario, if chemical-specific information is
sufficient to reasonably conclude that the experimental animal species is less or equally
sensitive as humans, the pharmacodynamic portion of this uncertainty factor (i.e., typically
starting at 10ฐ5 or "3") can be reduced.
Human variation (UFh). This UF accounts for variation in susceptibility across the human
population and the possibility that the available data may not be representative of
individuals who are most susceptible to the effect As with the UFa, this typically considers
potential pharmacokinetic and pharmacodynamic differences that might exist across
individuals, amongst other considerations (see Table 7-1). If population-based data for the
effect or for characterizing the internal dose are available, the potential for data-based
adjustments for pharmacodynamics or pharmacokinetics is considered fU.S. EPA. 2014a!11
Further, "when sufficient data are available, an intraspecies UF either less than or greater
than 10x may be justified (U.S. EPA. 2002). However, a reduction from the default (10) is
only considered in cases when there is dose-response data for the most susceptible
population" fU.S. EPA. 20021. This factor is reduced only if the POD is derived or adjusted
specifically for susceptible individuals [not for a general population that includes both
"Examples of adjusting the pharmacokinetic portion of interhuman variability include the IRIS boron
assessment's use of nonchemical-specific kinetic data [glomerular filtration rate in pregnant humans as a
surrogate for boron clearance fU.S. EPA. 2004)]: and the IRIS trichloroethylene assessment's use of
population variability in trichloroethylene metabolism via a PBPK model to estimate the lower 1st percentile
of the dose metric distribution for each POD fU.S. EPA. 2 Olid
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susceptible and nonsusceptible individuals [fU.S. EPA. 20021. see Section 4.4.5; fU.S. EPA.
1998a), see Section 4.2; (U.S. EPA. 19961. see Section 4; (U.S. EPA. 19941. see Section 4.3.9.1;
(U.S. EPA. 19911. see Section 3.4], Otherwise, a factor of 10 is generally used to account for
this variation. Note that when a PBPK model is available for relating human internal dose to
environmental exposure, relevant portions of this UF may be more usefully applied prior to
animal-to-human extrapolation, depending on the correspondence of any nonlinearities
(e.g., saturation levels) between species (also see Section 13.2.2).
LOAEL to NOAEL (UFi)\ If a POD is based on a LOAEL, the assessment must infer an
exposure level where such effects are not expected. This can be a matter of great
uncertainty if there is no evidence available at lower exposures. The ratio of the doses at the
LOAEL and NOAEL are expected to vary considerably across studies and consideration of
cross-study information may not be informative. A factor of up to 10 is generally applied to
extrapolate to a lower exposure expected to be without appreciable effects. A factor other
than 10 may be used depending on the magnitude and nature of the response and the shape
of the dose-response curve fU.S. EPA. 2002.1998a. 1996.1994.19911. For example, LOAELs
associated with lower response levels or less adverse effects (e.g., a small, minimally
biologically significant level of change at the LOAEL) may warrant smaller uncertainty
factors, whereas higher response levels likely warrant the default value of 10, or in rare
instances, values higher than 10. Regardless, the available data should be carefully
evaluated and any decision to apply a non-default value requires adequate discussion in the
dose-response section.
Subchronic-to-chronic exposure (UFs)ฆ Although not always made explicit, the intent of this
UF is to address the uncertainty associated with extrapolating from studies with exposure
durations shorter than the focus of the toxicity values derived. In IRIS, a lifetime (chronic)
reference value is typically the focus and oftentimes PODs are based on subchronic
evidence, so the assessment needs to consider whether lifetime exposure could have effects
at lower levels of exposure. As a general rule and in the context of subchronic-to-chronic
(lifetime) extrapolation, a factor of up to 10 is applied (after adjustment of intermittent
exposures to continuous) when using subchronic studies to make inferences about lifetime
exposure. A factor other than 10 may be used, depending on the duration and/or timing of
the studies and the nature of the response fU.S. EPA. 2002.1998a. 19941. For example,
studies that occur during a sensitive lifestage typically warrant application of a UFs = 1,
which would generally be applied regardless of the toxicity value type (e.g., a UFs = 1 for
both subchronic and chronic values). A prime example of this is developmental toxicity
studies and effects observed in offspring. Typically, developmental toxicity studies use
exposure durations either encompassing a specific portion of gestation (e.g., organogenesis)
or the entirety of gestation as these are expected to the critical windows of susceptibility for
developmental effects. Thus, there is no concern that a longer duration exposure would
result in more severe effects and an uncertainty factor would not be applied. This factor
may be applied, albeit rarely, for developmental or reproductive effects if exposure covered
less than the full critical period. A value different from 10 may be applied if there exists
sufficient information from the chemical database. For example, if a chemical database
contains subchronic and short-term studies and there is no evidence of an exacerbation of
effect when moving from short-term to subchronic exposure durations, an uncertainty
factor lower than 10 may be warranted. This UF is not necessarily constrained to a
subchronic-to-chronic exposure scenarios: it would also be considered in application to
extrapolating from a short-term study to a subchronic toxicity value and might still apply
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when extrapolating from a chronic duration study to a lifetime toxicity value if the chronic
duration is interpreted as likely to be insensitive. However, no general guidelines exist for
the standard values of short-term-to-subchronic, or chronic-to-lifetime extrapolations and
chemical-specific data would need to inform the value for these extrapolations assessment
to assessment
In addition to the adjustments above, a database UF (UFd) is applied to address any
database deficiencies that raise concern that further studies might identify a more sensitive
effect (e.g., in an organ system or a lifestage that is not well studied) (U.S. EPA. 2002.1998a.
1996.1994.19911. The size of the factor depends on the nature of the database deficiency.
For example, the EPA typically follows the suggestion that a factor of 10 be applied if a
prenatal toxicity study and a two-generation reproduction study is both missing, and a
factor of 10ฐ5 (rounded to 3) if either one or the other is missing [(U.S. EPA. 20021. see
Section 4.4.5], A database UF greater than 1 would still be applied if this type of study were
available but considered to be a low confidence study based on the evaluation process
[described in Chapter 12 of fU.S. EPA. 20221]. However, when deciding what value to apply
for this uncertainty factor, assessors need to consider the data missing and available for
specific organ systems and/or lifestages, meaning a UFd > 1 can still be applied in scenarios
when both developmental and two-generation reproduction studies are available if
sufficient evidence is available to raise a concern that effects could occur in other organ
systems at lower doses. In addition, a UFd > 1 can still be applied even if the POD being
adjusted comes from human data, and information from both human and animal studies
should be considered when selecting the value of this factor. Information on structurally-
related chemicals could be potentially used to select the value of this factor if it suggests
effects in organ systems for which chemical-specific data is missing.
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10. PROTOCOL HISTORY
Release date:
Revisions history:
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This document is a draft for review purposes only and does not constitute Agency policy.
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APPENDICES
APPENDIX A. SURVEY OF EXISTING REFERENCE VALUES FOR
NAPHTHALENE
1 Table A-l lists websites which were searched for relevant human health reference values
2 for naphthalene, along with indications of the results of the search. In addition to these sources, the
3 ToxValDB on EPA's CompTox Chemicals Dashboard
4 fhttps://comptox.epa.gov/dashboard/chemical lists/TOXVAL V5] was also searched for additional
5 reference values that were not captured by other sources. When values were identified for
6 naphthalene, they are shown in Figures 1-2 and described in Tables A-2 and A-3 if details were
7 provided on how the values were derived. When values were identified from sources that did not
8 provide derivation details, they are described in Table A-4 but not shown in Figures 1-2. The values
9 in these tables are current as of August 2022.
Table A-l. Sources searched for naphthalene heath effect reference values
Source
Search Results
Reference
American Conference of Governmental Industrial
Hygienists (ACGIH)
See Appendix Table A2.
ACGIH (2007)
American Industrial Hygiene Association (AIHA)
No search results found.
AIHA (2016)
Agency for Toxic Substances and Disease Registry
(ATSDR)
See Appendix Tables A2 and
A3.
ATSDR (2021)
ATSDR (2017)
California Environmental Protection Agency
(CalEPA)
See Appendix Table A2.
CalEPA (2016)
Connecticut Department of Energy &
Environmental Protection (CT DEEP)
See Appendix Tables A2 and
A3.
CT DEEP (2015)
CT DEEP (2018)
Deutsche Forschungsgemeinschaft, German
Research Foundation (DFG)
No search results found.
DFG(2020)
Drinking Water Standards and Health Advisories
(DWSHA)
See Appendix Table A3.
U.S. EPA (2018a)
Acute Exposure Level Guidelines from the U.S.
Environmental Protection Agency and National
Research Council) (EPA/NRC AEGL)
No search results found.
U.S. EPA (2018b)
Health Canada
See Appendix Table A2.
Government of Canada (2021)
No values found.
Health Canada (2020)
No values found.
Health Canada (1996)
Health and Safety Authority (HSA)
See Appendix Table A2.
HSA (2020)
Health and Safety Laboratory (HSL)
No values found.
HSL (2002)
This document is a draft for review purposes only and does not constitute Agency policy.
135 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Source
Search Results
Reference
Indiana Department of Environmental
Management (IDEM)
See Appendix Table A2.
IDEM (2019)
Idaho Department of Environmental Quality (ID
DEQ)
See Appendix Table A4.
Idaho DEQ (2019)
Institut fur Arbeitsschutz, The Institute for
Occupational Safety and Health (IFA)
See Appendix Table A4.
IFA (2020)
Integrated Risk Information System (IRIS)
See Appendix Tables A2 and
A3.
U.S. EPA (2021a)
International Toxicity Estimates for Risk (ITER)
No unique search results
found.
TERA (2021)
Japan Society for Occupational Health (JSOH)
No values found.
JSOH (2017)
Massachusetts Department of Environmental
Protection (MassDEP)
See Appendix Table A4.
MassDEP (2019)
Minnesota Department of Health (MDH)
See Appendix Table A2.
MDH (2019)
Michigan Department of Environment, Great
Lakes & Energy (Ml EGLE)
See Appendix Tables A2 and
A3.
Michigan DEQ (2016)
National Air Toxics Information Clearinghouse
(NATICH)
See Appendix Tables A2 and
A4.
U.S. EPA (1993)
North Carolina Department of Environmental
Quality (NC DEQ)
No values found.
NC Department of
Environmental Qualitv (2014)
Nevada Division of Environmental Protection
(NDEP)
See Appendix Table A2.
NDEP (2017)
National Institute for Occupational Safety and
Health (NIOSH)
See Appendix Table A2.
NIOSH (2018)
New Jersey Department of Environmental
Protection (NJ DEP)
See Appendix Table A2.
NJ DEP (2020)
New York State Department of Environmental
Conservation (NY DEC)
See Appendix Tables A2 and
A3.
NYSDEC(2006)
Office of Air Quality Planning and Standards
(OAQPS)
No unique search results
found.
U.S. EPA (2020a)
Ontario Ministry of Labour
See Appendix Table A2.
Ontario Ministry of Labour
(2020)
Office of Pesticide Programs (OPP)
See Appendix Table A3.
U.S. EPA (2021b)
Oregon Department of Environmental Quality (OR
DEQ)
See Appendix Table A2.
Oregon DEQ (2018)
Occupational Safety and Health Administration
(OS HA)
See Appendix Table A2.
OSHA (2019)
OSHA (2020a)
OSHA (2020b)
Protective Action Criteria (PAC) Database
See Appendix Table A2.
DOE (2018)
Publications Quebec
See Appendix Table A2.
Quebec(2020)
Rhode Island Department of Environmental
Management (Rl DEM)
See Appendix Table A2.
Rl DEM (2008)
No values found.
Tiesiema and Baars (2009)
This document is a draft for review purposes only and does not constitute Agency policy.
136 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Source
Search Results
Reference
Rijksinstituut voor Volksgezondheid en Milieu
(RIVM), The Netherlands Institute for Public
Health and the Environment
See Appendix Table A2.
Dusseldorp et al. (2011)
No values found.
RIVM (2001)
Safe Work Australia
See Appendix Table A2.
Safe Work Australia (2019)
Southwest Clean Air Association (SWCAA)
See Appendix Table A4.
SWCAA (2021)
Texas Commission on Environmental Quality
(TCEQ)
No values found.
TCEQ (2021)
See Appendix Tables A2 and
A3.
TCEQ (2018)
United States Army Public Health Center
(USAPHC)
See Appendix Table A4.
U.S. APHC (2013)
Vermont Department of Environmental
Conservation (VT DEC)
See Appendix Table A4.
VT ANR (2018)
Washington State Dept. of Ecology
See Appendix Table A4.
Washington State Legislature
(2009)
Worksafe
See Appendix Table A4.
Worksafe (2018)
World Health Organization (WHO)
No values found.
WHO (2017)
WHO (2021)
This document is a draft for review purposes only and does not constitute Agency policy.
137 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Table A-2. Details on derivation of the available health effect reference values for inhalation exposure to naphthalene
(from Figure 2-1 of the main text)
Reference
Value Name
Duration
Reference Value
Health Effect
Point of
Departure
Qualifier
Source
Uncertainty
Factors"
Notes on
Derivation
Review
Status
(mg/m3)
(ppm)
lergency Response
PAC-3
lhr
2,600
500
Adopted
previous IDLH
(NIOSH,
1994)
Adopted
previous
IDLH
Final
(DOE, 2018)
PAC-2
lhr
430
83
Based on PAC-3
Based on
PAC-3"
PAC-1
lhr
79
15
Adopted NIOSH
REL-STEL
Adopted
NIOSH REL-
STEL
This document is a draft for review purposes only and does not constitute Agency policy.
138 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Reference
Duration
Reference Value
Health Effect
Point of
Qualifier
Source
Uncertainty
Notes on
Review
Value Name
(mg/m3)
(ppm)
Departure
Factors"
Derivation
Status
NIOSH REL
10-hr TWA
50
10
NR
NR
NR
NR
Final
(TWA)
(NIOSH,
NIOSH REL-
15 min
75
15
NR
NR
NR
NR
1994)
STEL
NIOSH IDLH
30 min
1,300
250
Acute oral
toxicity
NR
NR
(Gerarde,
1960)
NR
Route-to-
route
extrapolation
applied
ACGIH TLV-
8-hr TWA
52
10
Eye irritation at
NR
NR
(Robbins,
NR
Final
TWA [Skin]c
15 ppm, acute
hemolysis, and
hepatoxicity in
humans
1951);
(Hanssler,
1964);
(Grigor et
(ACGIH,
2001)
al 1966),
(0
c
(Irle, 1964);
o
(Naiman and
+>
(0
Kosov,
Q.
3
1964);
O
o
(Valaes et
O
al 1963);
(Dawson et
al 1958);
(Cock,
1957);
(Schafer,
1951)
ACGIH TLV-
STEL [Skin]d
15 min
79
15
OSHA PEL
8-hr TWA
50
10
NR
NR
NR
NR
Final
(TWA)e
(OSHA,
Cal-OSHA PEL
8-hr TWA
0.5
0.1
NR
NR
NR
NR
2019)
(TWA)
This document is a draft for review purposes only and does not constitute Agency policy.
139 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Reference
Duration
Reference Value
Health Effect
Point of
Qualifier
Source
Uncertainty
Notes on
Review
Value Name
(mg/m3)
(ppm)
Departure
Factors"
Derivation
Status
U.S. EPA
Chronic RfC
(IRIS)f
Chronic
0.003
0.0006
Hyperplasia in
the respiratory
epithelium and
metaplasia in
the olfactory
epithelium of
adult male and
female mice
10 ppm
9.3 mg/m3
9.3 mg/m3
LOAEL
LOAELADJ
LOAELHEC
(NTP, 1992)
Total UF = 3,000
UFa= 10
UFh = 10
UFl= 10
UFdb = 3
Duration
adjusted:
(6-hr/24-hr)
x(5-d/7-d)
HEC
Adjusted8
Final
(U.S. EPA,
1998b)
General Public
ATSDR MRL
Chronic
(>lyr)
0.0036
0.0007
Nonneoplastic
lesions in nasal
olfactory
epithelium and
respiratory
epithelium of
adult male and
female rats and
mice
10 ppm
1.8 ppm
0.2 ppm
LOAEL
LOAELADJ
LOAELHEC
(Abdo et al.,
2001); (NTP,
2000); (NTP,
1992)
Total UF = 300
UFa = 3
UFh = 10
UFl= 10
Duration
adjusted:
(6-hr/24-hr)
x(5-d/7-d)
HEC
Adjustedh
Final
(ATSDR,
2005)
OEHHA RELi
Chronic
0.009
0.002
Nasal
inflammation,
olfactory
epithelial
metaplasia, and
respiratory
epithelial
hyperplasia in
adult male and
female mice
10 ppm
1.8 ppm
LOAEL
LOAELADJ
(NTP, 1992)
Total UF = 1,000
UFa = 10
UFh = 10
UFl= 10
UFs = 1
Duration
adjusted:
(6-hr/24-hr)
x(5-d/7-d)
Final
(OEHHA,
2000)
This document is a draft for review purposes only and does not constitute Agency policy.
140 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Reference
Duration
Reference Value
Health Effect
Point of
Qualifier
Source
Uncertainty
Notes on
Review
Value Name
(mg/m3)
(ppm)
Departure
Factors"
Derivation
Status
MDH HBV
Acute
(lhr)
0.2
0.038
Respiratory cell
swelling and
sloughing in
rats and
nausea,
vomiting,
abdominal pain,
and hemolytic
anemia in
humans
204 mg/m3
NOAEL
(Buckpitt
and Richieri,
1984)
Total UF = 1,000
UFa= 10
UFh = 10
UFdb = 10
Final
(MDH,
2004)
Chronic
(lyr)
0.009
0.002
Nasal effects in
adult rats and
mice
10 ppm
9.3 mg/m3
LOAEL
LOAELADJ
(NTP, 2000);
(NTP, 1992)
Total UF = 1,000
UFa= 10
UFh = 10
UFl= 10
Duration
adjusted:
(6-hr/24-hr)
x(5-d/7-d)
RIVM TCA
Chronic
0.025
0.0048
Local toxic
effect on the
nasal mucous
membrane in
adult rats
exposed for 28
d
5 mg/m3
LOAEL
(Coombs,
1993)
Total UF = 200
UFa= 10
UFh = 10
UFl = 2
No time
extrapolation
Based on EU
Risk
Assessment:
(ECB, 2003)
Final
(Dusseldorp
etal., 2011)
Health
Canada
Residential
Indoor RfC
Chronic
0.01
0.0019
Nasal epithelial
cytotoxicity in
adult rats
52 mg/m3
9.3 mg/m3
LOAEL
LOAELADJ
(NTP, 2000)
Total UF = 1,000
UFa= 10
UFh = 10
UFdb = 10
Duration
adjusted:
(6-hr/24-hr)
x(5-d/7-d)
Final
(Health
Canada,
2013)
This document is a draft for review purposes only and does not constitute Agency policy.
141 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Rl DEM AAL
24 hr
0.003
0.0006
Adopted IRIS
RfC as 24-hr.
AAL
Adopted IRIS
RfC as 24-hr.
AAL
Final
(Rl DEM,
2008)
lyr
0.00003
0.0000056
Cancer
0.000034
(Hg/m3)1
OEHHA
Cancer URF
(OEHHA,
2011)
NA
Calculated^
"3T
a)
OR DEQ ABC
lyr
0.00003
0.0000056
Cancer
0.000034
OEHHA
(OEHHA,
NA
Calculated*
Final
(J
(Hg/m3)1
Cancer URF
2011)
(Oregon
n
3
(0
>
DEQ,2018)
CT DEEP HLV
30 min
5
1
NR
NR
NR
NR
NA
Final
Q.
a)
(CT DEEP,
2015)
15
(0
8 hr
1
0.2
NR
52 mg/m3
ACGIH TLV-
(ACGIH,
Total UF = 50
Details
a)
c
a)
0
-------
Protocol for the Naphthalene IRIS Assessment
d Agencies of Quebec, Australia, Belgium, China, Singapore, South Korea, Spain, Sweden, and the Netherlands report identical values.
e Agencies of Denmark, France, Hungary, Italy, Latvia, China, Romania, South Korea, Sweden, Switzerland, the Netherlands, and Turkey report identical values.
/The EPA IRIS RfC has been adopted as a state value by the Texas Commission on Environmental Quality, Indiana Department of Environmental Management,
Pennsylvania Department of Environmental Protection, Alaska Department of Environmental Conservation, New Jersey Department of Environmental Protection, and
Michigan Department of Environment, Great Lakes & Energy.
9 LOAELhec= LOAEUdj x RGDR = 9.3 mg/m3 x 1 = 9.3 mg/m3
h LOAELhec= LOAELadjx RGDR = 1.8 ppm x 0.132 = 0.2 ppm
' The OEHHA REL value has been adopted by New York DEC
' AAL = 1 / URF / 106 = 1 / 0.000034 (ng/m3)1 / 106 = 0.03 ng/m3
k ABC = 1 / U RF / 10s = 1 / 0.000034 (ng/m3)1 / 106 = 0.03 ng/m3
' BCL = TR x AT / (ET x EF x ED x URF) = (106 x 70 yr x 365 d/yr x 24 hrs/d) / [24 hrs/d x 350 d/yr x 26 yrs x 0.000034 (ng/m3)"1] = 0.0826 ng/m3
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Table A-3. Details on derivation of the available health effect reference values for oral exposure to naphthalene
(from Figure 2-2 of the main text)
Reference
Notes on
Reference
Value
Point of
Uncertainty
Derivatio
Review
Value Name
Duration
(mg/kg-d)
Health Effect
Departure
Qualifier
Source
Factors"
n
Status
U.S. EPA RfD
Chronic
0.02
Decreased body wt.
100 mg/kg-d
NOAEL
(Battelle,
Total UF =
Duration
Final
(IRIS)"
in adult in male rats
1980)
3,000
adjusted:
(U.S. EPA,
exposed 13 wks.
71 mg/kg-d
NOAEUdj
UFa= 10
UFh = 10
UFs= 10
UFdb = 3
5-d/7-d
1998b)
U.S. EPA RfD
Acute
0.4
Neurotoxicity in adult
400 mg/kg-d
LOAEL
(Reynolds,
Total UF =
Final
(OPP)c
male and female
rats, such as head
shaking and reduced
1997)
1,000
UFa= 10
UFh = 10
(U.S. EPA,
2018c)
o
motor activity.
UFl= 10
~
Chronic
0.1
Renal toxicity in adult
100 mg/kg-d
NOAEL
(Battelle,
Total UF =
3
male rats and
1980)
1,000
Q.
decreased body
UFa= 10
(0
i_
weight in males and
UFh = 10
a)
c
females exposed 13
UFs= 10
a)
0
wks.
ATSDR MRL
Acute
(1-14 d)
0.6
Transient clinical
toxicity in pregnant
50 mg/kg-d
LOAEL
(NTP, 1991)
Total UF = 90
UFa= 10
Final
(ATSDR,
Intermediat
0.6
rats exposed on GD
UFh = 3
2005)
e
6-15.
UFl = 3
(15-365 d)
RIVM TDId
Chronic
0.04
Decreased body wt.
and increased kidney
and liver wt. in
laboratory animals
(further details not
provided).
NR
NR
(Edwards et
al 1997);
(Gustafson
etal., 1997)
NR
Based on
TPHCWG
approach
Final
(RIVM,
2001)
1
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
ADJ = adjusted; ATSDR = Agency for Toxic Substances and Disease Registry; GD = Gestation day; IRIS = Integrated Risk Information System; LOAEL = lowest-
observed-adverse-effect level; MRL = Minimal Risk Level; NOAEL = no-observed-adverse-effect level; NR = Not reported; OPP = Office of Pesticide Programs;
RfD = Reference Dose; RIVM = Rijksinstituut voor Volksgezondheid en Milieu; TDI = Tolerable Daily Intake; TPHCWG = Total Petroleum Hydrocarbon Criteria
Working Group; UF = uncertainty factor; UFh = inter-human variability; UFa = animal to human variability; UFl = LOAEL to NOAEL adjustment; UFs = subchronic
to chronic adjustment; UFdb = database uncertainty; U.S. EPA = U.S. Environmental Protection Agency
0 "Uncertainty factors" refer to modifying factors and other adjustment factors used by some organizations or in older EPA assessments.
b The U.S. EPA IRIS RfD has been adopted by the Office of Water, Health Canada, Alaska Department of Environmental Conservation, Pennsylvania Department
of Environmental Protection, Connecticut Department of Energy & Environmental Protection, Nevada Division of Environmental Protection, New York State
Department of Environmental Conservation, and Texas Commission on Environmental Quality.
c The U.S. EPA OPP chronic RfD has been adopted as a state value by Michigan Department of Environment, Great Lakes & Energy.
d The RIVM TDI value applies individually to non-carcinogenic polycyclic aromatic hydrocarbons "with equivalent carbon numbers of >9-16 (i.e., anthracene,
fluorene and naphthalene)."
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Table A-4. Details on additional inhalation values based on another agency's values or lacking derivation
descriptions
Reference Value
Name
Duratio
n
Reference Value
Health
Effect
Point of
Departure
Qualifier
Source
Uncertainty
Factors3
Notes on
Derivation
Review
Status
(mg/m3)
(ppm)
Special Use
USAPHC MEG -
Critical
(MEG-C)
1 hr
1,300
250
Adopted
2009 PAC-3
(DOE,
2009)
Adopted
2009 PAC-3
Final
(U.S. APHC,
2013)
USAPHC MEG -
Marginal
(MEG-M)
1 hr
75
15
Adopted
2009 PAC-2
Adopted
2009 PAC-2
USAPHC MEG -
Negligible
(MEG-N)
1 hr
75
15
Adopted
2009 PAC-1
Adopted
2009 PAC-1
8 hr
52
10
Adopted
ACGIH TLV-
TWA
Adopted
ACGIH TLV-
TWA
14 d
18
3.5
Based on
ACGIH TLV-
TWA
Based on
ACGIH TLV-
TWAb
1 yr
0.0021
0.0004
Based on IRIS
RfC
""
Based on
IRIS RfCc
Finland Limit
Value
15 min
10
2
NR
NR
NR
NR
Final
(IFA, 2020)
8-hr TWA
5
1
Occupationa
(International
Denmark Limit
Value
Short-
term
100
20
NR
NR
NR
NR
Interdepartmenta
1 Commission
MAC (Poland)
15 min
50
10
NR
NR
NR
NR
8-hr TWA
20
3.8
Worksafe WES
(New Zealand)
[Skin]
15 min
10
2
NR
NR
NR
NR
Final
(Worksafe,
2022)
8-hr TWA
2.6
0.5
1
This document is a draft for review purposes only and does not constitute Agency policy.
146 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Reference Value
Name"
Reference Value
Health
Effect"
Point of
Uncertainty
Factors6
Notes on
Derivation
Review
Status
Duration
(mg/m3)
(ppm)
Departure
b
Qualifier6
Source
IDDEQAAC
24 hr
2.5
0.48
NR
NR
NR
NR
Final
(Idaho DEQ,
2019)
VT DEC HAAS
1 yr
0.0003
0.000056
NR
NR
NR
NR
Final
(VTANR,
2018)
1/T
"ซ5
a)
a
Washington State
Dept. of Ecology
ASIL
1 yr
0.0000294
0.0000056
NR
NR
NR
NR
Final
(Washington
State
Legislature,
2009)
T3
a)
E
~
SWCAA ASIL
24 hr
0.17
0.033
NR
NR
NR
NR
Adopted
1998
Washington
State ASIL
Final
(SWCAA,
2019)
o
n
3
a.
15
a)
c
a)
0
MassDEP TEL"
24 hr
0.01425
0.00272
NR
NR
NR
NR
Values
derived in
accordance
with this
Final
(MassDEP,
2019)
MassDEP AAL"
1 yr
0.01425
0.00272
NR
NR
NR
NR
protocol:
(MassDEP,
2011)
ADEQAQG
1 hr
0.63
0.12
Based on
ACGIHTLV-
STEL
Based on
ACGIH TLV-
STELe
Final
(U.S. EPA,
1993)9
24 hr
0.4
0.077
Based on
ACGIHTLV-
TWA
Based on
ACGIH TLV-
TWAf
Broward County
ONRP AACh
8 hr
0.5
0.096
NR
52 mg/m3
ACGIHTLV-
TWA
(ACGIH,
1992)
Total UF' = 100
This document is a draft for review purposes only and does not constitute Agency policy.
147 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Reference Value
Name"
Reference Value
Health
Effect"
Point of
Uncertainty
Factors6
Notes on
Derivation
Review
Status
Duration
(mg/m3)
(ppm)
Departure
b
Qualifier6
Source
Pinellas County
24 hr
0.12
0.023
NR
NR
NR
NR
Air Pollution
Control Board
AAC
ME DEPAAL
15 min
7.9
1.52
NR
NR
NR
NR
24 hr
0.87
0.17
1 yr
0.014
0.0027
ND Dept. of
1 hr
0.79
0.15
NR
79 mg/m3
ACGIH TLV-
(ACGIH,
Total UF= 100
Health ACG
STEL
1992)
8 hr
0.52
0.1
NR
52 mg/m3
ACGIH TLV-
TWA
NDEPAAC
8 hr
1.19
0.23
NR
52 mg/m3
ACGIH TLV-
TWA
(ACGIH,
1992)
Total UF = 42
NY DEC AAL
1 yr
0.167
0.032
NR
52 mg/m3
ACGIH TLV-
TWA
(ACGIH,
1992)
Total UF = 300
OK Dept. of
24 hr
50
10
NR
NR
NR
Total UP = 50
Based on
Health AAC
occupational
values
SC DHEC AAL
24 hr
1.25
0.24
NR
52 mg/m3
ACGIH TLV-
TWA
(ACGIH,
1992)
Total UF = 40
TX Air Control
30 min
0.44
0.085
NR
NR
NR
NR
Board AAC
1 yr
0.05
0.01
VA Air Pollution
24 hr
0.87
0.17
NR
52 mg/m3
ACGIH TLV-
(ACGIH,
Total UF* = 60
Control AAC
TWA
1992)
Wl DNR Bureau of
24 hr
1.2
0.23
Based on
-
-
-
Based on
Air Management
ACGIH TLV-
ACGIH TLV-
AQG
TWA
TWA'
1
AAC = Acceptable Ambient Concentration; AAL = Allowable Ambient Limit; ACG = Ambient Concentration Guideline; ACGIH = American Conference of
Governmental Industrial Hygienists; ADEQ = Arizona Department of Environmental Quality; AQG = Air Quality Guideline; ASIL = Acceptable Source Impact
Level; HAAS = Hazardous Ambient Air Standard; ID DEQ = Idaho Department of Environmental Quality; IRIS = Integrated Risk Information System; MAC =
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Maximum Admissible Concentration; MassDEP = Massachusetts Department of Environmental Protection; ME DEP = Maine Department of Environmental
Protection; MEG = Military Exposure Guidelines; ND = North Dakota; NDEP = Nevada Division of Environmental Protection; NR = Not reported; NY DEC = New
York Department of Environmental Conservation; OK = Oklahoma; ONRP = Office of Natural Resource Protection; PAC = Protective Action Criteria; RfC =
Reference Concentration ; SC DHEC = South Carolina Department of Health and Environmental Control; STEL = Short-term Exposure Limit; SWCAA =
Southwest Clean Air Agency; TEL = Threshold Effects Exposure Limit; TLV = Threshold Limit Value; TWA = Time-weighted average; TX = Texas; UF = uncertainty
factor; USAPHC = United States Army Public Health Center; VA = Virginia; VT DEC = Vermont Department of Environmental Conservation; WES = workplace
exposure standard; Wl DNR = Wisconsin Department of Natural Resources
0 "Uncertainty factors" refer to modifying factors and other adjustment factors used by some organizations or in older EPA assessments.
b MEG = TLV X (IRoccupationai/ IRMiiitary) = 52 x (10 m3/d / 29.2 m3/d) = 18 mg/m3
c MEG = RfC x (IRGenerai pop./ IRMiiitary) = 0.003 mg/m3x (20 m3/d / 29.2 m3/d) = 0.0021 mg/m3
d MassDEP TEL and AAL values apply to the sum of naphthalene and 2-methylnaphthalene.
e 1-hr. AQG = TLV / 120 = 79 mg/m3/ 120 = 0.63 mg/m3
/24-hr. AQG = TLV/ 126 = 52 mg/m3/ 126 = 0.4 mg/m3
9 This document was compiled by the U.S. Environmental Protection Agency in 1993. Values from this document may have since been archived or updated by
the state agencies which reported them.
h The Hillsborough Co. Environmental Protection Commission and Pinellas County Air Control Board report the same value.
' A factor of 100 is applied "for category A substances."
J A factor of 50 is applied for category B substances.
k A factor of 60 is applied for non-carcinogens.
' 24-hr. AQG = TLV x 0.024 = 52 mg/m3 x 0.024 = 1.2 mg/m3
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
APPENDIX B. ELECTRONIC DATABASE SEARCH STRATEGIES
Table B-l. Core database search strategy
Database
Search Date
Query String
PubMed
1/11/2022
("naphthalene"[nm] AND 2021/01/01:2022/01/ll[mhda]) OR (("naphthalene"[tw] OR
"albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR
"naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth
balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
"Naphthalenes"[mh:noexp] AND 2021/01/01:2022/01/ll[mhda]) OR ((("naphthalene"[tw] OR
"albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR
"naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth
balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
(2021/01/01:2022/01/ll[edat] OR 2021/01/01:2022/01/ll[crdt])) NOT medline[sb])
1/28/2021
("naphthalene"[nm] AND 2018/12/01: 2021/01/31[mhda]) OR (("naphthalene"[tw] OR
"albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR
"naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth
balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
"Naphthalenes"[mh:noexp] AND 2018/12/01: 2021/01/31 [mhda]) OR ((("naphthalene"[tw] OR
"albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR
"naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth
balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
(2018/12/01: 2021/01/31[edat] OR 2018/12/01 2021/01/31[crdt])) NOT medline[sb])
2/8/2019
("naphthalene"[nm] AND 2017/10/01: 2019/01/01[mhda]) OR (("naphthalene"[tw] OR
"albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR
"naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth
balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
"Naphthalenes"[mh:noexp] AND 2017/10/01: 2019/01/01[mhda]) OR ((("naphthalene"[tw] OR
"albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR
"naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth
balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
(2017/10/01: 2019/01/01[edat] OR 2017/10/01: 2019/01/01[crdt])) NOT medline[sb])
9/29/2017
("naphthalene"[nm] AND 2017/02/01: 3000[mhda]) OR (("naphthalene"[tw] OR "albocarbon"[tw]
OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR "naphtalene"[tw] OR
"camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth
flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR "Naphthalinum"[tw] OR
"Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND "Naphthalenes"[mh:noexp]
AND 2017/02/01: 3000[mhda]) OR ((("naphthalene"[tw] OR "albocarbon"[tw] OR
"naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR "naphtalene"[tw] OR "camphor
tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
"mothballs"[tw] OR "Naphtalinum"[tw] OR "Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty
150"[tw] OR "Mighty RDl"[tw]) AND (2014/10/01: 3000[edat] OR 2017/02/01: 3000[crdt])) NOT
medline[sb])
01/04/2017
ซ524-42-5[rn] OR 130-15-4[rn] OR 7234-04-0[rn] OR 277-50-9[rn]) OR (("l,2-Dihydro-l,2-diketo-
naphthalene"[tw] OR "l,2-Naphthalenedione"[tw] OR "l,2-Naphthaquinone"[tw] OR "beta-
Naphthoquinone"[tw] OR "o-Naphthoquinone"[tw] OR "l,4-Dihydro-l,4-diketonaphthalene"[tw]
OR "l,4-Naphthalenedione"[tw] OR "l,4-Naphthoquinone"[tw] OR "l,4-Naphthylquinone"[tw] OR
"alpha-Naphthoquinone"[tw] OR "p-Naphthoquinone"[tw] OR "l,2-Dihydronaphthalene-l,2-
diol"[tw] OR "l,2-Dihydroxy-l,2-dihydronaphthalene"[tw] OR "l,2-dihydro-l,2-
Naphthalenediol"[tw] OR "Naphthalene-l,2-dihydrodiol"[tw] OR "trans- 1,2-Dihydroxy-1,2-
dihydronaphthalene"[tw] OR "Naphthalene l,2-oxide"[tw] OR "Naphthalene oxide"[tw] OR
"Naphth(l,2-b)oxirene"[tw]) NOT medline[sb])) OR (("naphthalene"[nm] AND 2015/10/01:
3000[mhda]) OR (("naphthalene"[tw] OR "albocarbon"[tw] OR "naphthalin"[tw] OR
"naphthaline"[tw] OR "naphthene"[tw] OR "naphtalene"[tw] OR "camphor tar"[tw] OR "tar
camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw]
OR "Naphtalinum"[tw] OR "Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR
"Mighty RDl"[tw]) AND "Naphthalenes"[mh:noexp] AND 2015/10/01: 3000[mhda]) OR
((("naphthalene"[tw] OR "albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR
"naphthene"[tw] OR "naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white
tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
(2015/10/01: 3000[edat] OR 2015/10/01: 3000[crdt])) NOT medline[sb]))
11/06/2015
("naphthalene"[nm] AND 2014/10/01: 3000[mhda]) OR (("naphthalene"[tw] OR "albocarbon"[tw]
OR "naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR "naphtalene"[tw] OR
"camphor tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth
flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR "Naphthalinum"[tw] OR
"Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND "Naphthalenes"[mh:noexp]
AND 2014/10/01: 3000[mhda]) OR ((("naphthalene"[tw] OR "albocarbon"[tw] OR
"naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR "naphtalene"[tw] OR "camphor
tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR
"mothballs"[tw] OR "Naphtalinum"[tw] OR "Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty
150"[tw] OR "Mighty RDl"[tw]) AND (2014/10/01: 3000[edat] OR 2014/10/01: 3000[crdt])) NOT
medline[sb])
12/16/2014
("naphthalene"[nm] AND 2012/12/01: 3000[mhda]) OR ("Naphthalenes"[mh:noexp] AND ("91-20-
3"[tw] OR "naphthalene"[tw] OR "albocarbon"[tw] OR "naphthalin"[tw] OR "naphthaline"[tw] OR
"naphthene"[tw] OR "naphtalene"[tw] OR "camphor tar"[tw] OR "tar camphor"[tw] OR "white
tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR "mothballs"[tw] OR "Naphtalinum"[tw] OR
"Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty 150"[tw] OR "Mighty RDl"[tw]) AND
2012/12/01: 3000[mhda]) OR ((("91-20-3"[tw] OR "naphthalene"[tw] OR "albocarbon"[tw] OR
"naphthalin"[tw] OR "naphthaline"[tw] OR "naphthene"[tw] OR "naphtalene"[tw] OR "camphor
tar"[tw] OR "tar camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR
"mothballs"[tw] OR "Naphtalinum"[tw] OR "Naphthalinum"[tw] OR "Dezodorator"[tw] OR "Mighty
150"[tw] OR "Mighty RDl"[tw]) AND (2012/12/01: 3000[crdat] OR 2012/12/01: 3000[edat])) NOT
medline[sb])
02/17/2013
(((91-20-3[rn]) OR (("91-20-3"[tw] OR naphthalene[tw] OR albocarbon[tw] OR naphthalin[tw] OR
naphthaline[tw] OR naphthene[tw] OR naphtalene[tw] OR "camph[tw] OR tar"[tw] OR "tar
camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR mothballs[tw])
AND ("naphthalenes"[mh:noexp]))) AND (("naphthalenes/toxicity"[MeSH Terms] OR
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
"naphthalenes/adverse effects"[MeSH Terms] OR "naphthalenes/poisoning"[MeSH Terms] OR
"naphthalenes/pharmacokinetics"[MeSH Terms]) OR ("naphthalenes/blood"[MeSH Terms] OR
"naphthalenes/cerebrospinal fluid"[MeSH Terms] OR "naphthalenes/urine"[MeSH Terms]) OR
("naphthalenes/metabolism"[MeSH Terms] AND ("humans"[MeSH Terms] OR "animals"[MeSH
Terms])) OR ("naphthalenes/antagonists and inhibitors"[MeSH Terms]) OR ("chemically
induced"[MeSH Subheading] OR "environmental exposure"[MeSH Terms]) OR ("endocrine
system"[mh] OR "hormones, hormone substitutes, and hormone antagonists"[mh] OR "endocrine
disruptors"[mh]) OR (cancer[sb]) OR ("Computational biology"[mh] OR "Medical lnformatics"[mh]
OR Genomics[mh] OR Genome[mh] OR Proteomics[mh] OR Proteome[mh] OR Metabolomics[mh]
OR Metabolome[mh] OR Genes[mh] OR "Gene expression"[mh] OR Phenotype[mh] OR
genetics[mh] ORgenotype[mh] ORTranscriptome[mh] OR ("Systems Biology"[mh] AND
("Environmental Exposure"[mh] OR "Epidemiological Monitoring"[mh] OR analysis[sh])) OR
"Transcription, Genetic "[mh] OR "Reverse transcription"[mh] OR "Transcriptional activation"[mh]
OR "Transcription factors"[mh] OR ("biosynthesis"[sh] AND (RNA[mh] OR DNA[mh])) OR "RNA,
Messenger "[mh] OR "RNA, Transfer"[mh] OR "peptide biosynthesis"[mh] OR "protein
biosynthesis"[mh] OR "Reverse Transcriptase Polymerase Chain Reaction"[mh] OR "Base
Sequence"[mh] OR "Trans-activators"[mh] OR "Gene Expression Profiling"[mh]) OR (rat[tw] OR
rats[tw] OR mouse[tw] OR mice[tw] OR muridae[tw] OR rabbit[tw] OR rabbits[tw] OR hamster[tw]
OR hamsters[tw] OR ferret[tw] OR ferrets[tw] OR gerbil[tw] OR gerbils[tw] OR rodent[tw] OR
rodents[tw] OR rodentia[tw] OR dog[tw] OR dogs[tw] OR beagle[tw] OR beagles[tw] OR canine[tw]
OR cats[tw] OR feline[tw] OR pig[tw] OR pigs[tw] OR swine[tw] OR porcine[tw] OR monkey[tw] OR
monkeys[tw] OR macaque[tw] OR macaques[tw] OR baboon[tw] OR baboons[tw] OR
marmoset[tw] OR marmosets[tw] OR "animals, laboratory"[mh]) OR (((pharmacokinetics[mh] OR
metabolism[mh]) AND (humans[mh] OR animals[mh])) OR "dose-response relationship, drug"[mh]
OR risk[mh]))) OR (("91-20-3"[tw] OR naphthalene[tw] OR albocarbon[tw] OR naphthalin[tw] OR
naphthaline[tw] OR naphthene[tw] OR naphtalene[tw] OR "camph[tw] OR tar"[tw] OR "tar
camphor"[tw] OR "white tar"[tw] OR "moth balls"[tw] OR "moth flakes"[tw] OR mothballs[tw])
NOT medline[sb])
Web of Science
1/11/2022
(TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS="mothballs" ORTS="Naphtalinum" OR
TS="Naphthalinum" ORTS="Dezodorator" ORTS="Mighty 150" ORTS="Mighty RD1") AND
((WC=("Toxicology" OR "Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Neurosciences" OR "Obstetrics &
Gynecology" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Respiratory System" OR
"Urology & Nephrology" OR "Anatomy & Morphology" OR "Andrology" OR "Pathology" OR
"Veterinary Sciences" OR "Otorhinolaryngology" OR "Ophthalmology" OR "Pediatrics" OR
"Oncology" OR "Reproductive Biology" OR "Developmental Biology" OR "Biology" OR
"Dermatology" OR "Allergy" OR "Public, Environmental & Occupational Health") OR SU=("Anatomy
& Morphology" OR "Cardiovascular System & Cardiology" OR "Developmental Biology" OR
"Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR "Hematology" OR
"Immunology" OR "Neurosciences & Neurology" OR "Obstetrics & Gynecology" OR "Oncology" OR
"Ophthalmology" OR "Pathology" OR "Pediatrics" OR "Pharmacology & Pharmacy" OR "Physiology"
OR "Public, Environmental & Occupational Health" OR "Respiratory System" OR "Toxicology" OR
"Urology & Nephrology" OR "Reproductive Biology" OR "Dermatology" OR "Allergy")) AND
(TS="rat" ORTS="rats" ORTS="mouse" ORTS="murine" ORTS="mice" ORTS="guinea" OR
TS="muridae" ORTS=rabbit* ORTS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* OR
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
TS=rodent* OR TS="dog" OR TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR
TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine" OR TS="porcine" OR TS=monkey* OR
TS=macaque* ORTS=baboon* ORTS=marmoset* ORTS=toxic*) AND (TS="rat" ORTS="rats" OR
TS="mouse" OR TS="murine" OR TS="mice" OR TS="guinea" OR TS="muridae" OR TS=rabbit* OR
TS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog"OR
TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs"
ORTS="swine" ORTS="porcine" ORTS=monkey* ORTS=macaque* ORTS=baboon* OR
TS=marmoset*) OR (TS="child" ORTS="children" ORTS=adolescen* ORTS=infant* OR
TS="WORKER" OR TS="WORKERS" ORTS="HUMAN" OR TS=patient* ORTS="mother" OR
TS="fetal" OR TS="fetus" ORTS="citizens" ORTS="milk" ORTS="formula")) AND PY=(2021-2022)
1/28/2021
(TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS="mothballs" ORTS="Naphtalinum" OR
TS="Naphthalinum" ORTS="Dezodorator" ORTS="Mighty 150" ORTS="Mighty RD1") AND
((WC=("Toxicology" OR "Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Neurosciences" OR "Obstetrics &
Gynecology" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Respiratory System" OR
"Urology & Nephrology" OR "Anatomy & Morphology" OR "Andrology" OR "Pathology" OR
"Veterinary Sciences" OR "Otorhinolaryngology" OR "Ophthalmology" OR "Pediatrics" OR
"Oncology" OR "Reproductive Biology" OR "Developmental Biology" OR "Biology" OR
"Dermatology" OR "Allergy" OR "Public, Environmental & Occupational Health") OR SU=("Anatomy
& Morphology" OR "Cardiovascular System & Cardiology" OR "Developmental Biology" OR
"Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR "Hematology" OR
"Immunology" OR "Neurosciences & Neurology" OR "Obstetrics & Gynecology" OR "Oncology" OR
"Ophthalmology" OR "Pathology" OR "Pediatrics" OR "Pharmacology & Pharmacy" OR "Physiology"
OR "Public, Environmental & Occupational Health" OR "Respiratory System" OR "Toxicology" OR
"Urology & Nephrology" OR "Reproductive Biology" OR "Dermatology" OR "Allergy")) AND
(TS="rat" ORTS="rats" ORTS="mouse" ORTS="murine" ORTS="mice" ORTS="guinea" OR
TS="muridae" ORTS=rabbit* ORTS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* OR
TS=rodent* OR TS="dog" OR TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR
TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine" OR TS="porcine" OR TS=monkey* OR
TS=macaque* ORTS=baboon* ORTS=marmoset* ORTS=toxic*) AND (TS="rat" ORTS="rats" OR
TS="mouse" OR TS="murine" OR TS="mice" OR TS="guinea" OR TS="muridae" OR TS=rabbit* OR
TS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog"OR
TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs"
ORTS="swine" ORTS="porcine" ORTS=monkey* OR TS=macaque* ORTS=baboon* OR
TS=marmoset*) OR (TS="child" ORTS="children" ORTS=adolescen* ORTS=infant* OR
TS="WORKER" OR TS="WORKERS" ORTS="HUMAN" OR TS=patient* ORTS="mother" OR
TS="fetal" OR TS="fetus" ORTS="citizens" ORTS="milk" ORTS="formula")) AND PY=(2019-2021)
2/8/2019
(TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS="mothballs" ORTS="Naphtalinum" OR
TS="Naphthalinum" ORTS="Dezodorator" ORTS="Mighty 150" ORTS="Mighty RD1") AND
((WC="Toxicology" OR WC="Endocrinology & Metabolism" OR WC="Gastroenterology &
Hepatology" OR WC="Gastroenterology & Hepatology" OR WC="Hematology" OR
WC="Neurosciences" OR WC="Obstetrics & Gynecology" OR WC="Pharmacology & Pharmacy" OR
WC="Physiology" OR WC="Respiratory System" OR WC="Urology & Nephrology" OR
WC="Anatomy & Morphology" OR WC="Andrology" OR WC="Pathology" OR
This document is a draft for review purposes only and does not constitute Agency policy.
153 DRAFT-DO NOT CITE OR QUOTE
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Database
Search Date
Query String
WC="Otorhinolaryngology" OR WC="Ophthalmology" OR WC="Pediatrics" OR WC="Oncology" OR
WC="Reproductive Biology" OR WC="Developmental Biology" OR WC="Biology" OR
WC="Dermatology" OR WC="Allergy" OR WC="Public, Environmental & Occupational Health" OR
SU="Anatomy & Morphology" OR SU="Cardiovascular System & Cardiology" OR
SU="Developmental Biology" OR SU="Endocrinology & Metabolism" OR SU="Gastroenterology &
Hepatology" OR SU="Hematology" OR SU="lmmunology" OR SU="Neurosciences & Neurology" OR
SU="Obstetrics & Gynecology" OR SU="Oncology" OR SU="Ophthalmology" OR SU="Pathology" OR
SU="Pediatrics" OR SU="Pharmacology & Pharmacy" OR SU="Physiology" OR SU="Public,
Environmental & Occupational Health" OR SU="Respiratory System" OR SU="Toxicology" OR
SU="Urology & Nephrology" OR SU="Reproductive Biology" OR SU="Dermatology" OR
SU="Allergy") OR (WC="veterinary sciences" AND (TS="rat" ORTS="rats" ORTS="mouse" OR
TS="murine" ORTS="mice" ORTS="guinea" ORTS="muridae" ORTS=rabbit* ORTS=lagomorph*
ORTS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog" ORTS="dogs" OR
TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine"
ORTS="porcine" ORTS=monkey* ORTS=macaque* ORTS=baboon* ORTS=marmoset*)) OR
(TS=toxic* AND (TS="rat" ORTS="rats" ORTS="mouse" ORTS="murine" ORTS="mice" OR
TS="guinea" ORTS="muridae" ORTS=rabbit* ORTS=lagomorph* ORTS=hamster* ORTS=ferret*
OR TS=gerbil* OR TS=rodent* OR TS="dog" OR TS="dogs" OR TS=beagle* OR TS="canine" OR
TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine" OR TS="porcine" OR
TS=monkey* ORTS=macaque* ORTS=baboon* ORTS=marmoset*) OR (TS="child" OR
TS="children" ORTS=adolescen* ORTS=infant* ORTS="WORKER" OR TS="WORKERS" OR
TS="HUMAN" ORTS=patient* ORTS=mother ORTS=fetal ORTS=fetus OR TS=citizens ORTS=milk
OR TS=formula)) OR TI=toxic*) AND PY=(2017-2019)
9/29/2017
(TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS="mothballs" ORTS="Naphtalinum" OR
TS="Naphthalinum" ORTS="Dezodorator" ORTS="Mighty 150" ORTS="Mighty RD1") AND
((WC=("Toxicology" OR "Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Neurosciences" OR "Obstetrics &
Gynecology" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Respiratory System" OR
"Urology & Nephrology" OR "Anatomy & Morphology" OR "Andrology" OR "Pathology" OR
"Otorhinolaryngology" OR "Ophthalmology" OR "Pediatrics" OR "Oncology" OR "Reproductive
Biology" OR "Developmental Biology" OR "Biology" OR "Dermatology" OR "Allergy" OR "Public,
Environmental & Occupational Health") OR SU=("Anatomy & Morphology" OR "Cardiovascular
System & Cardiology" OR "Developmental Biology" OR "Endocrinology & Metabolism" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Immunology" OR "Neurosciences &
Neurology" OR "Obstetrics & Gynecology" OR "Oncology" OR "Ophthalmology" OR "Pathology" OR
"Pediatrics" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Public, Environmental &
Occupational Health" OR "Respiratory System" OR "Toxicology" OR "Urology & Nephrology" OR
"Reproductive Biology" OR "Dermatology" OR "Allergy")) OR (WC="veterinary sciences" AND
(TS="rat" ORTS="rats" ORTS="mouse" ORTS="murine" ORTS="mice" ORTS="guinea" OR
TS="muridae" ORTS=rabbit* ORTS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* OR
TS=rodent* OR TS="dog" OR TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR
TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine" OR TS="porcine" OR TS=monkey* OR
TS=macaque* ORTS=baboon* ORTS=marmoset*)) OR (TS=toxic* AND (TS="rat" ORTS="rats" OR
TS="mouse" OR TS="murine" OR TS="mice" OR TS="guinea" OR TS="muridae" OR TS=rabbit* OR
TS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog"OR
TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs"
This document is a draft for review purposes only and does not constitute Agency policy.
154 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
ORTS="swine" ORTS="porcine" ORTS=monkey* ORTS=macaque* ORTS=baboon* OR
TS=marmoset*) OR (TS="child" ORTS="children" ORTS=adolescen* ORTS=infant* OR
TS="WORKER" OR TS="WORKERS" ORTS="HUMAN" OR TS=patient* OR TS=mother OR TS=fetal OR
TS=fetus OR TS=citizens OR TS=milk OR TS=formula)) OR TI=toxic*) AND PY=(2017-2017)
01/04/2017
(TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS="mothballs" ORTS="Naphtalinum" OR
TS="Naphthalinum" ORTS="Dezodorator" ORTS="Mighty 150" ORTS="Mighty RD1") AND
((WC=("Toxicology" OR "Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Neurosciences" OR "Obstetrics &
Gynecology" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Respiratory System" OR
"Urology & Nephrology" OR "Anatomy & Morphology" OR "Andrology" OR "Pathology" OR
"Otorhinolaryngology" OR "Ophthalmology" OR "Pediatrics" OR "Oncology" OR "Reproductive
Biology" OR "Developmental Biology" OR "Biology" OR "Dermatology" OR "Allergy" OR "Public,
Environmental & Occupational Health") OR SU=("Anatomy & Morphology" OR "Cardiovascular
System & Cardiology" OR "Developmental Biology" OR "Endocrinology & Metabolism" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Immunology" OR "Neurosciences &
Neurology" OR "Obstetrics & Gynecology" OR "Oncology" OR "Ophthalmology" OR "Pathology" OR
"Pediatrics" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Public, Environmental &
Occupational Health" OR "Respiratory System" OR "Toxicology" OR "Urology & Nephrology" OR
"Reproductive Biology" OR "Dermatology" OR "Allergy")) OR (WC="veterinary sciences" AND
(TS="rat" ORTS="rats" ORTS="mouse" ORTS="murine" ORTS="mice" ORTS="guinea" OR
TS="muridae" ORTS=rabbit* ORTS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* OR
TS=rodent* OR TS="dog" OR TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR
TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine" OR TS="porcine" OR TS=monkey* OR
TS=macaque* ORTS=baboon* ORTS=marmoset*)) OR (TS=toxic* AND (TS="rat" ORTS="rats" OR
TS="mouse" OR TS="murine" OR TS="mice" OR TS="guinea" OR TS="muridae" OR TS=rabbit* OR
TS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog"OR
TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs"
ORTS="swine" ORTS="porcine" ORTS=monkey* ORTS=macaque* ORTS=baboon* OR
TS=marmoset*) OR (TS="child" OR TS="children" OR TS=adolescen* OR TS=infant* OR
TS="WORKER" OR TS="WORKERS" ORTS="HUMAN" OR TS=patient* OR TS=mother OR TS=fetal OR
TS=fetus OR TS=citizens OR TS=milk OR TS=formula)) OR TI=toxic*) AND PY=(2015-2017)
11/04/2015
(TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS="mothballs" ORTS="Naphtalinum" OR
TS="Naphthalinum" ORTS="Dezodorator" ORTS="Mighty 150" ORTS="Mighty RD1") AND
((WC=("Toxicology" OR "Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Neurosciences" OR "Obstetrics &
Gynecology" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Respiratory System" OR
"Urology & Nephrology" OR "Anatomy & Morphology" OR "Andrology" OR "Pathology" OR
"Otorhinolaryngology" OR "Ophthalmology" OR "Pediatrics" OR "Oncology" OR "Reproductive
Biology" OR "Developmental Biology" OR "Biology" OR "Dermatology" OR "Allergy" OR "Public,
Environmental & Occupational Health") OR SU=("Anatomy & Morphology" OR "Cardiovascular
System & Cardiology" OR "Developmental Biology" OR "Endocrinology & Metabolism" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Immunology" OR "Neurosciences &
Neurology" OR "Obstetrics & Gynecology" OR "Oncology" OR "Ophthalmology" OR "Pathology" OR
"Pediatrics" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Public, Environmental &
This document is a draft for review purposes only and does not constitute Agency policy.
155 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
Occupational Health" OR "Respiratory System" OR "Toxicology" OR "Urology & Nephrology" OR
"Reproductive Biology" OR "Dermatology" OR "Allergy")) OR (WC="veterinary sciences" AND
(TS="rat" ORTS="rats" ORTS="mouse" ORTS="murine" ORTS="mice" ORTS="guinea" OR
TS="muridae" ORTS=rabbit* ORTS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* OR
TS=rodent* OR TS="dog" OR TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR
TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine" OR TS="porcine" OR TS=monkey* OR
TS=macaque* ORTS=baboon* ORTS=marmoset*)) OR (TS=toxic* AND (TS="rat" ORTS="rats" OR
TS="mouse" OR TS="murine" OR TS="mice" OR TS="guinea" OR TS="muridae" OR TS=rabbit* OR
TS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog"OR
TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs"
ORTS="swine" ORTS="porcine" ORTS=monkey* ORTS=macaque* ORTS=baboon* OR
TS=marmoset*) OR (TS="child" ORTS="children" ORTS=adolescen* ORTS=infant* OR
TS="WORKER" OR TS="WORKERS" ORTS="HUMAN" OR TS=patient* OR TS=mother OR TS=fetal OR
TS=fetus OR TS=citizens OR TS=milk OR TS=formula)) OR TI=toxic*) AND PY=(2014-2016)
12/16/2014
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS="mothballs" ORTS="Naphtalinum" OR
TS="Naphthalinum" ORTS="Dezodorator" ORTS="Mighty 150" ORTS="Mighty RD1") AND
((WC=("Toxicology" OR "Endocrinology & Metabolism" OR "Gastroenterology & Hepatology" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Neurosciences" OR "Obstetrics &
Gynecology" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Respiratory System" OR
"Urology & Nephrology" OR "Anatomy & Morphology" OR "Andrology" OR "Pathology" OR
"Otorhinolaryngology" OR "Ophthalmology" OR "Pediatrics" OR "Oncology" OR "Reproductive
Biology" OR "Developmental Biology" OR "Biology" OR "Dermatology" OR "Allergy" OR "Public,
Environmental & Occupational Health") OR SU=("Anatomy & Morphology" OR "Cardiovascular
System & Cardiology" OR "Developmental Biology" OR "Endocrinology & Metabolism" OR
"Gastroenterology & Hepatology" OR "Hematology" OR "Immunology" OR "Neurosciences &
Neurology" OR "Obstetrics & Gynecology" OR "Oncology" OR "Ophthalmology" OR "Pathology" OR
"Pediatrics" OR "Pharmacology & Pharmacy" OR "Physiology" OR "Public, Environmental &
Occupational Health" OR "Respiratory System" OR "Toxicology" OR "Urology & Nephrology" OR
"Reproductive Biology" OR "Dermatology" OR "Allergy")) OR (WC="veterinary sciences" AND
(TS="rat" ORTS="rats" ORTS="mouse" ORTS="murine" ORTS="mice" ORTS="guinea" OR
TS="muridae" ORTS=rabbit* ORTS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* OR
TS=rodent* OR TS="dog" OR TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR
TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine" OR TS="porcine" OR TS=monkey* OR
TS=macaque* ORTS=baboon* ORTS=marmoset*)) OR (TS=toxic* AND (TS="rat" ORTS="rats" OR
TS="mouse" OR TS="murine" OR TS="mice" OR TS="guinea" OR TS="muridae" OR TS=rabbit* OR
TS=lagomorph* ORTS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog"OR
TS="dogs" OR TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs"
ORTS="swine" ORTS="porcine" ORTS=monkey* ORTS=macaque* ORTS=baboon* OR
TS=marmoset*) OR (TS="child" ORTS="children" ORTS=adolescen* ORTS=infant* OR
TS="WORKER" OR TS="WORKERS" ORTS="HUMAN" OR TS=patient* OR TS=mother OR TS=fetal OR
TS=fetus ORTS=citizens ORTS=milk OR TS=formula)) OR TI=toxic*)) AND PY=2012-2015
02/21/2013
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" OR TS=mothballs) NOTTS="naphthalene acetic
acid") AND (TS="chronic" OR TS=immun* OR TS=lymph* OR TS=neurotox* OR TS=toxicokin* OR
This document is a draft for review purposes only and does not constitute Agency policy.
156 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
TS=pharmacokin* OR TS=biomarker* ORTS=neurolog* OR TS="subchronic" ORTS="pbpk" OR
TS=epidemiolog* ORTS="acute" OR TS="subacute" ORTS="ld50")
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS=mothballs) NOTTS-'naphthalene acetic
acid") AND (TS="lc50" OR TS=inhal* OR TS=pulmon* OR TS="nasal" OR TS=lung* OR TS=respir* OR
TS=occupation* ORTS="workplace" ORTS=worker* ORTS="oral" OR TS="orally" ORTS=ingest* OR
TS="gavage" ORTS="diet" ORTS="diets" OR TS="dietary" ORTS="drinking" ORTS=gastr* OR
TS=intestin* ORTS=liver* ORTS=hepat* ORTS=kidney* ORTS=nephr*)
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" OR TS=mothballs) NOTTS="naphthalene acetic
acid") AND (TS="gut" OR TS=sensitiz* OR TS=abort* OR TS=abnormalit* OR TS=embryo* OR
TS=cleft* OR TS=fetus* ORTS=foetus* ORTS=fetal* ORTS=foetal* ORTS=fertilit* ORTS=infertil*
ORTS-'fertilization" ORTS="fertilisation" ORTS=malform* ORTS="ovum" ORTS="ova" OR
TS="ovary" ORTS="ovaries" ORTS="ovarian" ORTS=placenta* ORTS=pregnan*)
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" OR TS=mothballs) NOTTS="naphthalene acetic
acid") AND (TS=dermal* OR TS="dermis" OR TS="skin" OR TS=epiderm* OR TS="cutaneous" OR
TS=carcinog* ORTS=cocarcinog* ORTS="cancer" ORTS="precancer" ORTS=neoplas* OR
TS=tumor* ORTS=tumour* ORTS=oncogen* ORTS=lymphoma* ORTS=carcinom* OR
TS=genetox* ORTS=genotox* ORTS=mutagen* ORTS=nephrotox* ORTS=hepatotox* OR
TS=endocrin* ORTS=estrogen* ORTS=androgen*)
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS=mothballs) NOTTS-'naphthalene acetic
acid") AND (TS=hormon* ORTS="blood" ORTS="serum" ORTS="urine" ORTS="bone" OR
TS="bones" OR TS=skelet* OR TS="rat" OR TS="rats" OR TS="mouse")
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS=mothballs) NOTTS-'naphthalene acetic
acid") AND (TS="mice" ORTS="guinea" ORTS="muridae" ORTS=rabbit* ORTS=lagomorph* OR
TS=hamster* ORTS=ferret* ORTS=gerbil* ORTS=rodent* ORTS="dog" ORTS="dogs" OR
TS=beagle* OR TS="canine" OR TS="cats" OR TS="feline" OR TS="pig" OR TS="pigs" OR TS="swine"
ORTS="porcine" ORTS=monkey* ORTS=macaque* ORTS=baboon* ORTS=marmoset* OR
TS=toxic* ORTS="adverse" ORTS="poisoning")
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS=mothballs) NOTTS-'naphthalene acetic
acid") AND (TS="prenatal" OR TS="perinatal" OR TS="postnatal" OR TS="reproduce" OR
TS=reproduct* ORTS=steril* ORTS=teratogen* ORTS=sperm* ORTS=neonat* OR TS=newborn*
ORTS=development* ORTS=zygote* ORTS="child" OR TS="children" ORTS=adolescen* OR
TS=infant* OR TS=wean* OR TS="offspring" OR TS="age factor" OR TS="age factors")
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" OR TS=mothballs) NOTTS="naphthalene acetic
This document is a draft for review purposes only and does not constitute Agency policy.
157 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
acid") AND (TS="Genomics" ORTS="Proteomics" ORTS="Metabolic Profile" ORTS="Metabolome"
OR TS="Metabolomics" ORTS="Microarray" ORTS="Nanoarray")
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS=mothballs) NOTTS="naphthalene acetic
acid") AND (TS="Gene expression" ORTS="Transcript expression" ORTS="transcriptomes" OR
TS="transcriptome" ORTS="Phenotype" ORTS="Transcription" ORTS="Trans-act*" OR
TS="transact*" OR TS="trans act*" OR TS=genetic OR TS="genetics" OR TS="genotype")
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS=mothballs) NOTTS-'naphthalene acetic
acid") AND (TS="lnformatics" OR (TS="lnformation Science" AND TS=Medical ORTS="Systems
biology" OR (TS="Biological systems" AND (TS=monit* OR TS=data OR TS=analysis))))
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" ORTS=mothballs) NOTTS-'naphthalene acetic
acid") AND (TS="Genetic transcription" ORTS="Gene transcription" ORTS="Gene Activation" OR
TS="Genetic induction" OR TS="Reverse transcription" ORTS='Transcriptional activation" OR
TS="Transcription factors" OR (TS="Biosynthesis" AND (TS=RNA OR TS=DNA)) ORTS="mRNA")
((TS="naphthalene" ORTS="albocarbon" ORTS="naphthalin" ORTS="naphthaline" OR
TS="naphthene" OR TS="naphtalene" OR TS="camphor tar" OR TS="tar camphor" OR TS="white
tar" ORTS="moth balls" ORTS="moth flakes" OR TS=mothballs) NOT TS="naphthalene acetic
acid") AND (TS="messenger RNA" ORTS="transfer RNA" OR TS="peptide biosynthesis" OR
TS="protein biosynthesis" ORTS="protein synthesis" ORTS="RT-PCR" ORTS="RTPCR" OR
TS="Reverse Transcriptase Polymerase Chain Reaction" OR TS="DNA sequence")
ToxLine
2/8/2019
@synO+@AND+@OR+(naphthalene+albocarbon+naphthalin+naphthaline+
naphthene+naphtalene+""camphor+tar"+"tar+camphor"+"white+tar"+"moth+balls"
+"moth+flakes"+mothballs+Naphtalinum+Naphthalinum+Dezodorator+
"Mighty+150"+"Mighty+RDl"+@term+@rn+91+20+3)
+@and+@range+yr+2017+2019+@not+@org+pubmed
9/29/2017
@synO+@AND+@OR+(naphthalene+albocarbon+naphthalin+naphthaline+naphthene+naphtalene
+"camphor+tar"+"tar+camphor"+"white+tar"+"moth+balls"+"moth+flakes"+mothballs+Naphtalinu
m+Naphthalinum+Dezodorator+"Mighty+150"+"Mighty+RDl"+@term+@rn+91+20+3)+@and+@r
ange+yr+2017+@not+@org+pubmed
01/04/2017
@synO+@OR+(piscesqcorrection+naphthalene+albocarbon+naphthalin+naphthaline+naphthene+
naphtalene+"camphor tar"+"tar camphor"+"white tar"+"moth balls"+"moth
flakes"+mothballs+Naphtalinum+Naphthalinum+Dezodorator+"Mighty 150"+"Mighty
RDl"+@term+@ rn+91-20-
3)+@and+@range+yr+2015+2017+@not+@org+pubmed+pubdart+"nih+reporter"+tscats
11/09/2015
@synO+@OR+(piscesqcorrection+naphthalene+albocarbon+naphthalin+naphthaline+naphthene+
naphtalene+"camphor tar"+"tar camphor"+"white tar"+"moth balls"+"moth
flakes"+mothballs+Naphtalinum+Naphthalinum+Dezodorator+"Mighty 150"+"Mighty
RDl"+@term+@ rn+91-20-
3)+@and+@range+yr+2014+2016+@not+@org+pubmed+pubdart+"nih+reporter"+tscats
This document is a draft for review purposes only and does not constitute Agency policy.
158 DRAFT-DO NOT CITE OR QUOTE
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
12/16/2014
@OR+(naphthalene+albocarbon+naphthalin+naphthaline+naphthene+naphtalene+mothballs+@te
rm+@rn+91-20-
3)+@AND+@range+yr+2012+2015+@NOT+@org+pubmed+pubdart+"nih+reporter"+tscats
@OR+("camphor+tar"+"tar+camphor"+"white+tar"+"moth+balls"+"moth+flakes")+@AND+@rang
e+yr+2012+2015+@NOT+@org+pubmed+pubdart+"nih+reporter"+tscats
02/18/2013
@OR+(naphthalene+albocarbon+naphthalin+naphthaline+naphthene+naphtalene+mothballs+@te
rm+@rn+91-20-3)+@NOT+@org+pubmed+pubdart+crisp+tscats
@OR+("camphor+tar"+"tar+camphor"+"white+tar"+"moth+balls"+"moth+flakes")+@NOT+@org+
pubmed+pubdart+crisp+tscats
Table B-2. Targeted database search for PBPK models for naphthalene
Database
Search Date
Query String
PubMed
8/17/2022
(pbpk[tiab] OR "pb-pk"[tiab] OR pbtk[tiab] OR "pb-tk"[tiab] OR pbk[tiab] OR httk[tiab] OR pk-
model*[tiab] OR tk-model*[tiab] OR (("physiologically based"[tiab] OR "biologically based"[tiab])
AND (pharmacokinetic*[tiab] OR toxicokinetic*[tiab] OR kinetic[tiab] OR model*[tiab] OR
pharmacokinetics[mh] OR toxicokinetics[mh:noexp] OR pharmacokinetics[sh]))) AND naphthalene
Table B-3. Toxic Substances Control Act Test Submissions (TSCATS) search
strategy
Database
Search Date
Query String
TSCATS via CDATฐ
01/04/2017
91-20-3
Mail Received Date Range 10/01/2015 to 01/04/2017
11/04/2015
91-20-3
Mail Received Date Range 01/01/2014 to 11/04/2015
TSCATS 2"
01/04/2017
91-20-3
EPA receipt date 10/01/2015 to date of search
12/16/2014
91-20-3
EPA receipt date 02/01/2013 to date of search
05/01/2013
91-20-3 date limited, 2000 to date of search
TSCATS lc
02/18/2013
@term+@rn+91-20-3+@AND+@org+tscats
TSCA section 8e/FYI recent submissions*
01/04/2017
Google: 91-20-3 (8e or fyi) tsca
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
Database
Search Date
Query String
12/16/2014
Google: 91-20-3 (8e or fyi) tsca
05/01/2013
Google: 91-20-3 (8e or fyi) tsca
0 CDAT (Chemical Data Access Tool); formerly available at http://iava.epa.gov/oppt chemical search/.
Information from CDAT has since been incorporated into EPA's ChemView database at
https://chemview.epa.gov/chemview.
bTSCATS 2 was searched via the following database URL: https://catalog.data.gov/dataset/toxic-substances-
control-act-test-submissions-2-0-tscats-2-01
c TSCATS 1 was searched via Toxline
d TSCA section 8e/FYI recent submissions were searched via Google
Table B-4. Processes used to augment the search of core databases for
naphthalene
System Used
Selected Reference(s) or Sources
Date
Additional
References
Identified
Toxic
Substances
Control Act Test
Submissions
(TSCATS)
CDAT (Chemical Data Access Tool)
91-20-3
Mail Received Date Range 10/01/2015 to 01/04/2017
91-20-3
Mail Received Date Range 01/01/2014 to 11/04/2015
01/2017
Manual search
of citations
from published
Bailey et al. (2015). "Hypothesis-based weight-of-evidence
evaluation and risk assessment for naphthalene carcinogenesis."
Critical Reviews in Toxicology: 1-42
12/2015
12 citations
added
reviews
Lewis (2012). "Naphthalene animal carcinogenicity and human
relevancy: overview of industries with naphthalene-containing
streams." Regulatory Toxicology and Pharmacology 62(1): 131-
137
12/2015
1 citations added
Piccirillo et al. (2012). "Preliminary evaluation of the human
relevance of respiratory tumors observed in rodents exposed to
naphthalene." Regulatory Toxicology and Pharmacology 62(3):
433-440.
12/2015
0 citations added
Magee et al. (2010). "Screening-level population risk assessment
of nasal tumors in the US due to naphthalene exposure."
Regulatory Toxicology and Pharmacology 57(2-3): 168-180.
12/2015
0 citations added
Rhomberg et al. (2010). "Hypothesis-based weight of evidence: a
tool for evaluating and communicating uncertainties and
inconsistencies in the large body of evidence in proposing a
carcinogenic mode of action-naphthalene as an example."
Critical Reviews in Toxicology 40(8): 671-696.
12/2015
0 citations added
Manual search
of citations
NTP (2021). Naphthalene. In Report on Carcinogens, 15th
Edition. National Toxicology Program.
8/2022
2 citations added
from national
and
international
NTP (2016). Naphthalene (14th ed.). Research Triangle Park, NC:
National Toxicology Program, https://ntp.niehs.nih.gov/ntp/
roc/content/profiles/naphthalene.pdf
1/2017
0 citations added
This document is a draft for review purposes only and does not constitute Agency policy.
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System Used
Selected Reference(s) or Sources
Date
Additional
References
Identified
health agency
documents
ACGIH (2001). Naphthalene. Documentation of the threshold
limit values and biological exposure indices. Cincinnati, OH:
American Conference of Industrial Hygienists.
5/2013
4 citations added
ATSDR (2005). Toxicological Profile for Naphthalene, 1-
Methylnaphthalene, and 2-Methylnaphthalene. Atlanta, GA:
Agency for Toxic Substances and Disease Registry.
5/2013
7 citations added
IARC (2002). IARC Monographs on the evaluation of the
carcinogenic risk of chemicals to humans: Some traditional
herbal medicines, some mycotoxins, naphthalene, and styrene
[IARC Monograph], Lyon, France.
http://monographs.iarc.fr/ENG/Monographs/vol82/mono82.pdf
5/2013
3 citations added
NTP (2011). Naphthalene. In Report on Carcinogens, 12th
Edition. National Toxicology Program.
5/2013
0 citations added
WHO (1998). Selected non-heterocyclic polycyclic aromatic
hydrocarbons. Environmental Health Criteria, 202. Geneva,
Switzerland, World Health Organization.
5/2013
2 citations added
Web of Science,
"forward"
searcha
Abdo et al. (2001). Toxicity and carcinogenicity study in F344 rats
following 2 years of whole-body exposure to naphthalene
vapors. Inhalation Toxicology 13:931-950.
1/2017
5/2013
0 citations added
0 citations added
Dodd et al. (2012). Nasal epithelial lesions in F344 rats following
a 90-day inhalation exposure to naphthalene. Inhalation
Toxicology 24:70-79.
1/2017
5/2013
0 citations added
0 citations added
Shopp et al. (1984). Naphthalene toxicity in CD-I mice: general
toxicology and immunotoxicology. Toxicological Sciences 4:406-
419.
1/2017
5/2013
0 citations added
0 citations added
Web of Science,
"backward"
searchb
Abdo et al. (2001). Toxicity and carcinogenicity study in F344 rats
following 2 years of whole-body exposure to naphthalene
vapors. Inhalation Toxicology 13:931-950.
5/2013
2 citations added
Dodd et al. (2012). Nasal epithelial lesions in F344 rats following
a 90-day inhalation exposure to naphthalene. Inhalation
Toxicology 24:70-79.
5/2013
0 citations added
Shopp et al. (1984). Naphthalene toxicity in CD-I mice: general
toxicology and immunotoxicology. Toxicological Sciences 4:406-
419.
5/2013
5 citations added
References
obtained during
References that had been previously added to the HERO project
page for the naphthalene assessment during the development of
3/2017
2 citations added
the assessment
process
earlier draft materials.
1/2017
9 citations added
12/2015
22 citations
added
This document is a draft for review purposes only and does not constitute Agency policy.
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System Used
Selected Reference(s) or Sources
Date
Additional
References
Identified
5/2013
36 citations
added
Search of Online
Chemical
Assessment-
Related
Websites
Searched a combination of CASRNs and synonyms on the
following databases:
American Conference of Governmental Industrial Hygienists
(ACGIH): https://www.acgih.org/
American Industrial Hygiene Association (AIHA):
Workplace Environmental Exposure Levels (WEELs)
(https://www.tera.org/OARS/PDF_documents/OARS_WEEL_Tabl
e.pdf)
Emergency Response Planning Guidelines (ERPGs)
(https://www.aiha.org/get-
involved/AIHAGuidelineFoundation/EmergencyResponsePlannin
gGuidelines/Pages/default.aspx)
Agency for Toxic Substances and Disease Registry (ATSDR):
https://wwwn.cdc.gov/TSP/index.aspx
CalEPA Office of Environmental Health Hazard Assessment
(OEHHA): http://www.oehha.ca.gov/risk.html
OEHHAToxicity Criteria Database
(http://www.oehha.ca.gov/tcdb/index.asp)
Biomonitoring California-Priority Chemicals
(https://biomonitoring.ca.gov/chemicals/priority-chemicals)
Biomonitoring California-Designated Chemicals
(https://biomonitoring.ca.gov/chemicals/designated-chemicals)
Cal/Ecotox Database (https://ecotox.oehha.ca.gov/)
OEHHA Fact Sheets
(http://www.oehha.ca.gov/public_info/facts/index.html)
Non-cancer health effects [reference exposure levels (RELs)]
(http://www.oehha.ca.gov/air/allrels.html)
Cancer Potency Factors (Appendix A and B)
(http://www.oehha.ca.gov/air/hot_spots/tsd052909.html)
Consumer Product Safety Commission (CPSC):
http://www.cpsc.gov
Centre for Chemical Safety Assessment (ECETOC):
http://www.ecetoc.org/publications
European Chemicals Agency (ECHA):
General site (http://echa.europa.eu/information-on-chemicals)
Registered Substances (https://echa.europa.eu/information-on-
chemicals/registered-substances)
Existing Substances Regulation (ESR)
(http://echa.europa.eu/information-on-chemicals/information-
from-existing-substances-regulation)
Environment Canada:
Toxic Substances Managed Under Canadian Environmental
Protection Act (http://www.ec.gc.ca/toxiques-
toxics/Default.asp?lang=En&n=98E80CC6-l)
8/2022
23 citations
added
1/2017
1 citation added
12/2015
13 citations
added
4/2012
19 citations
added
This document is a draft for review purposes only and does not constitute Agency policy.
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Protocol for the Naphthalene IRIS Assessment
System Used
Selected Reference(s) or Sources
Date
Additional
References
Identified
Final Assessments (http://www.ec.gc.ca/lcpe-
cepa/default.asp?lang=En&xml=09F567A7-BlEE-lFEE-73DB-
8AE6C1EB7658)
Draft Assessments (http://www.ec.gc.ca/lcpe-
cepa/default.asp?lang=En&xml=6892C255-5597-C162-95FC-
4B905320F8C9)
Federal Docket: www.regulations.gov
Health Canada:
Health Canada Drinking Water Documents (http://www.hc-
sc.gc.ca/ewh-semt/pubs/water-eau/index-eng.php#tech_doc)
Health Canada First Priority List Assessments (http://www.hc-
sc.gc.ca/ewh-semt/pubs/contaminants/psll-lspl/index-eng.php)
Health Canada Second Priority List Assessments (http://www.hc-
sc.gc.ca/ewh-semt/pubs/contaminants/psl2-lsp2/index-eng.php)
International Agency for Research on Cancer (IARC):
http://monographs.iarc.fr/ENG/Monographs/voll01/monol01-
B02-B03.pdf
International Toxicity Estimates for Risk (ITER):
https://iter.tera.org/
Japan Existing Chemical Data Base:
http://dra4.nihs.go.jp/mhlw_data/jsp/SearchPageENG.jsp
National Academies of Sciences, Engineering, and Medicine
(NASEM): http://www.nap.edu/
National Cancer Institute (NCI): http://www.cancer.gov
National Industrial Chemicals Notification and Assessment
Scheme (NICNAS) (Australia):
Australian Inventory of Chemical Substances (AICS)
(http://www.cirs-
reach.com/lnventory/Australian_lnventory_of_Chemical_Substa
nces_AICS.html)
National Institute of Environmental Health Sciences (NIEHS):
http://www.niehs.nih.gov/
National Institute of Occupational Safety and Health (NIOSH):
All Workplace Safety & Health Topics
(http://www.cdc.gov/niosh/topics/)
NIOSHTIC 2 Publications Search: http://www2a.cdc.gov/nioshtic-
2/
Registry of Toxic Effects of Chemical Substances
(https://www.cdc.gov/niosh/rtecs/default.html)
National Institute of Technology and Evaluation Chemical Risk
Information Platform (NITE-CHIRP) (Japan):
http://www.safe.nite.go.jp/english/db.html
National Toxicology Program (NTP):
Report on Carcinogens (RoC)
(https://ntp.niehs.nih.gov/whatwestudy/assessments/cancer/ro
c/index.html)
NTP Site Search (https://ntpsearch.niehs.nih.gov/)
This document is a draft for review purposes only and does not constitute Agency policy.
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System Used
Selected Reference(s) or Sources
Date
Additional
References
Identified
Occupational Safety and Health Administration (OSHA):
http://www.osha.gov/dts/chemicalsampling/toc/toc_chemsamp
.html
Organisation for Economic Cooperation and Development
(OECD)c:
eChemPortal
(https://www.echemportal.org/echemportal/substance-search)
OECD Existing Chemicals Database
(https://hpvchemicals.oecd.org/ui/Search.aspx)
U.S. Environmental Protection Agency (EPA):
Acute Exposure Guideline Levels
(https://www.epa.gov/aegl/access-acute-exposure-guideline-
levels-aegls-values#chemicals)
Integrated Risk Information System (IRIS)
(http://www.epa.gov/iris/)
National Service Center for Environmental Publications (NSCEP)
(https://www.epa.gov/nscep)
RfD/RfC and Carcinogen Risk Assessment Verification Endeavor
(CRAVE) meeting notes
Science Inventory (http://cfpub.epa.gov/si/)
High Production Volume Information System (HPVIS)
(https://ofmpub.epa.gov/oppthpv/metadata.html)
Chemical Data Access Tool (formerly available at
http://java.epa.gov/oppt_chemical_search/; information from
CDAT has been incorporated into EPA's ChemView database at
https://chemview.epa.gov/chemview)
Office of Pesticide Programs
(http://iaspub.epa.gov/apex/pesticides/f?p=chemicalsearch:l)
U.S. Food and Drug Administration (FDA): http://www.fda.gov/
National Center for Toxicological Research (NCTR)
(http://www.fda.gov/AboutFDA/CentersOffices/OC/OfficeofScie
ntificandMedicalPrograms/NCTR/default.htm)
0 "Forward" search for records that cite included studies
b "Backward" search for records cited by included studies
c Searched for OECD High Production Volume (HPV) chemicals, Screening Information Dataset (SIDS) International
Uniform Chemicals Information Database (IUCUD), and SIDS United Nations Environment Programme (UNEP).
This document is a draft for review purposes only and does not constitute Agency policy.
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Protocol for the Naphthalene IRIS Assessment
B.l. ELECTRONIC SCREENING
For literature searches conducted through November 2015, all identified records were first
electronically screened with a set of terms intended to prioritize "on-topic" references for title and
abstract review. The electronic screening process creates two broad categories: one comprising all
records that contain (in title, abstract, or keywords) at least one inclusion/exclusion term (listed in
Table A-3) related to health outcomes, epidemiological or toxicological study design, toxicokinetics,
or mechanistic information, and one that does not contain any of the terms. Some of the electronic
inclusion/exclusion terms are generic (i.e., not chemical specific) and are intended to capture
health effect studies of any type. Other terms are specific to naphthalene and are based on previous
knowledge of health effects and possible mechanisms of toxicity. Records that contained at least
one inclusion/exclusion term were moved forward for title and abstract screening.
Citations that did not contain at least one inclusion/exclusion term in Table A-3 were
subjected to a quality control check to verify that relevant references are not missed. Specifically, a
random sample (~10%) of the electronically excluded citations were subjected to title/abstract
review by a scientist (toxicologist or epidemiologist) to confirm that the electronic screening
process produced acceptable results (i.e., no relevant citations were inadvertently missed). If the
random sample contained at least one potentially relevant citation, the list of electronic screening
terms was revised to add terms pertaining to the missing citation, and the electronic screening
process was repeated. This quality control and revision process was repeated as many times as
necessary to ensure that relevant studies are retained for title/abstract screening. Citations that did
not contain at least one term inclusion/exclusion term were excluded from further review.
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Table B-5. Electronic screening inclusion terms for naphthalene (listed alphabetically within each organ/system
category)
Category
Terms
Organ/System Specific Terms
Cardiovascular
angio
blood AND vessel
endotheli
thrombus
aort
capillar
heart
valve
arrhythm
cardiac, cardio, cardium
hypertens
vascular, vaso
artery, arteri
circulat
infarct
vein, venous
blood AND pressure
coronary
myocardi
ventricle
Dermal/
blister
epiderm, epidermal
nail
sweat, perspiration
Integumentary
bulla, bullous
erythema
pruritus
tooth, teeth
system
cutaneous
hair
sebaceous
dermal, dermis
keratin, kerato
skin
Developmental
abnormalit
fetal, fetus, foetal, foetus
parturition
terato
abort
gestation
perinatal
uterus, uterine
cleft
implantation
postnatal
viable, viabil
congenital
malform
puberty
visceral
defect
neonat
pregnan
wean
development
newborn
prenatal
zygote
embryo
neural AND tube
resorption
Endocrine
adipokine
hypothalamus
pituitary
thyro
adipocyt
insulin
triiodo
adrenal
pancreas, pancreat
tetraiodo
hormone
pineal
thymus, thymic
Gastrointestinal
abdomen
constipation
gastrointestinal
peptic
anus, anal
diarrhea
ileum, ileal, ileus
rectum, rectal
bucca
digestive
intestin
salivary
bowel
duoden
jejunum, jejunal
stomach
cecum, cecal
esophagus
mouth
tongue
colon
gastric
oral AND cavity
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Category
Terms
Organ/System Specific Terms
Hematologic
albumin
cytopenia
histamine
RBC (red blood cell)
anemia, anemic, anaemia, anaemic
erythro
hypoxemi
reticulocyt
blood
hemoly, haemoly
granulocyt
serum
cholesterol
hemat
plasma
thrombo
clot
hemocoagulat
platelet
coagulat
hemoglobin
polycythemia
Hepatic
alkaline AND phosphatase
cholesta
glutamyltransferase
liver
aminotransferase
cholangio
hepat
peroxisome
bile, biliary
cirrho
hydropic
portal, periportal
bilirubin
gall AND bladder
Ito
steatosis
centrilobular
glycogen
Kuppfer
stellate
Immune
adenopath
complement
inflamm
monocyt
allerg
dendrocyt, dendritic
interferon
natural AND killer
anaphyla
eosinophil, eosinopenia
leukocyt
neutrophil, neutropenia
antibod
epitope
lymph
phagocyt
antigen
globulin
macrophag
polymorphonuclear
asthma
granuloma
major histocompatibility complex,
sensitize, sensitis
basophil, basopenia
hapten
MHC
sensitivity
B-cell
humoral
marrow
spleen, splenous
cytokine
hypersensit
mast AND cell
WBC (white blood cell)
chemokine
immun
macroglobulin
T-cell
Musculoskeletal
articular
cartilage
muscle, muscul
tendon
bone
collagen
osteo
vertebra
bursa
connective
pyridinoline
calcitonin
ligament
skelet
Nervous
autonomic
efferent
memory
PNS (peripheral nervous system)
axon
electrophysiol
myelin AND sheath
Ranvier
behavior, behaviour
encephalo
locomotor
Schwann
brain
fatigue
nerve
sensory, sensori
CNS (central nervous system)
FOB (functional observational battery) nervous AND system
spinal AND cord
Cognitive
ganglia, ganglio
neuro
sympathetic
dendrite
parasympathetic
synap
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Category
Terms
Organ/System Specific Terms
Ocular
cataract
harderian
ocular
cornea
lachrymal, lacrimal
ophthalm
eye
lens, lenticular
retina
Reproductive
androgen
fertilit
ova, ovum
seminiferous
breast
follicle
penis
sexual
cervical, cervix
FSH
placenta
sperm
coagulating AND gland
gamete
primordial
sterility
corpora lutea, corpus luteum
gonad
progesterone
testes, testic, testis
endometrium
infertility
prolactin
testosterone
epididym
lacto, la eta
prostate
urogenital
estrogen, estradiol
LH (luteinizing hormone)
reproduct
vagina
estrus, estrous
lordosis
scrotum
vulva
fallopian
mammar
seminal AND vesicle
Respiratory
airway
cough
intratrach
pharyn
alveolar
crackle
laryn
pneumon
BAL (bronchoalveolar lavage)
diffusing AND capacity
lung
pulmonary
bleb
dyspnea
nasal
rale
bronch
FEV, forced AND expiratory
nose
respir
chest
FVC, forced AND vital
olfactory
trach
Urinary
alpha 2u globulin
creatinine
kidney
urethra
anion AND gap
dilation, dilatation
nephro
uria
BUN
genitourinary
proximal AND tubule, distal AND
urinalysis
bladder
glomerul
tubule
urinary
Bowman's
Henle
renal
urine
Nonspecific Terms
Epidemiology
case-control, case AND control
cohort
occupation
survey
case AND report, case AND series
epidemiol
Animal
animals
dog, dogs, canine
macaque
primate
baboon
ferret
marmoset
rabbit
beagle
gerbil
monkey
rat, rats
cat, cats, feline
guinea
mouse, mice, murine
rodent
chimp
hamster
pig, pigs, porcine, swine
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Cell lines, single-
Bacillus
Escher
Saccharomyces
celled organisms,
Drosophila
Explant
Salmonella
and other in vitro
E. Coli
photobacterium
V79
and ex vivo terms
Survival and
anorexi
weight AND loss
poison
general toxicity
body AND weight
death, mortality, survival
General cancer
adenoma
cancer
malignan
oncogen
terms
hemangioma
carcino
metasta
sarcoma
biops
CDC2
neoplas
tumor, tumour
General gross and
apoptosis, apoptotic
edema
hyperplas
necrosis, necrotic
microscopic
amyloid
endoplasmic
hypertroph
nodul
pathology terms
atrophy
epitheli
hypoxi
parenchyma
atypic, atypia
fibros, fibrotic
infiltrat
phenotyp
biometr
hemorrhag
lesion
radiographic
congest
histiocytic
medulla
tubul
cyst
histometr
metaplas
vacuol
degenerat
histolog,
microdissected
vesicul
dysplas
histopatholog
mitochondria
dystroph
hyaline
mucosa
Nonspecific clinical
calcium
clinical AND chemistry
glucos
chemistry
Inflammation/oxida
buthionine AND sulfoximine, BSO
lipid AND peroxidation
ROS
tive stress
diethyl AND maleate, DEM
oxidative AND stress
thiobarbituric, TBARS
glutathione, GSH
reactive AND oxygen AND species,
TNF
Genotox/mutageni
aber
chromati, chromosom
genom
mutagen
city
ames assay
clastogen
genotox
mutat
ames test
cytogen
hyperploid
polyploid
aneuploid
DNA
karyo
recessive AND lethal
anisokaryo, anisonucleo
dominant AND lethal
micronucle
sister AND chromatid, SCE, SCEs
binuclea
gene, genes, genetic
mitotic
ADME/TK
absorb, absorp
excret
PBTK
tolerance
cytochrome, CYP
metabol
pharmacokinetic
toxicokinetic
deposit
microsom
protein AND binding
distribut
PBPK
stereo
Naphthalene-specific Terms
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Toxicity terms
Clara
club AND cell
clubbing (of the nail)
ADME/TK
aldoketo
dihydrodiol
epoxide
naphthoquinone
oxide
Mechanistic terms
CC10 (Clara cell 10-kDa protein)
CC16 (Clara cell 16-kDa protein)
CCSP (Clara cell 10 kDa secretory
protein)
CGRP (calcitonin gene-related
peptide)
cyclin dependent kinase 1, CDK1
EGF (epidermal growth factor)
metalloproteinase, MMP
NEB, NEBs (neuroepithelial body)
nerve growth factor, NGF
Neurotrophic tyrosine kinase
PNEC (pulmonary neuroendocrine
cell)
signal transducer and activator of
transcription 3, STAT3
SCGB1A1 (Secretoglobin 1A1)
sulfhydryl
TFF, trefoil (trefoil factor)
trkl (Neurotrophic tyrosine kinase
receptor 1)
TrkA (tropomyosin receptor kinase A)
1
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APPENDIX C. INITIAL LITERATURE INVENTORY FOR NAPHTHALENE
(SYSTEMATIC EVIDENCE MAP)
1 An SEM for naphthalene was conducted according to the methods for literature search,
2 screening, and inventory described in Section 4 and was used to develop a literature inventory of
3 human and animal health effect studies and PBPK models meeting the problem formulation PECO
4 criteria described in Section 4.1. A literature flow diagram summarizing the literature search and
5 screening results is shown in Figure C-l. Literature search and screening results can also be viewed
6 on the HERO project page for this assessment
7 fhttps://hero.epa.gov/hero/index.cfm/proiect/page/project id/3671.
This document is a draft for review purposes only and does not constitute Agency policy.
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Core Database Searches (2013 to 2022)
PubMed
(n = 8,625)
WOS
{n = 6,714)
ToxLine
(n = 4,961)
Targeted PBPK Model
Search (2022)
( \
PubMed
{n = 109)
^ J
Studies Meeting PECO Criteria
{n = 120 records)
Human health effects studies (n = 39 records
(38 distinct references))
Animal health effect studies [n = 73 records
(64 distinct references)]
PBPK models (n = 9)
Tagged as Supplemental (n= 942)
Mechanistic (n = 443)
ADME/Toxicokinetics (n = 229)
PBPK model application (n = 8)
Non-PECO route of exposure (n = 113)
Human case reports/case series (n = 73)
JP-8 health effect studies (n = 7)
Non-English studies (n = 60)
Abstract only/full text not available (n =
166)
Figure C-l. Literature flow diagram for naphthalene.
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C.l. HUMAN AND ANIMAL HEALTH EFFECT STUDIES
A survey of study designs and health systems assessed in the human studies that met the
problem formulation PECO criteria is provided in Figure C-2. A total of 38 epidemiological studies
were identified that evaluated effects in several population types (occupational, general population,
pregnant women/infants, and children). Studies classified as "inhalation" exposure quantified
naphthalene levels in air, whereas studies classified as "nonspecific" exposure used biomonitoring
to assess naphthalene or naphthalene metabolites in blood or urine. The epidemiological studies
that evaluated pulmonary, nasal, hematological, immune, reproductive, or developmental effects
meet the assessment PECO criteria (see Section 5.1) and therefore will be included in the
assessment-specific approach as described in Section 5 (29 studies total).
A survey of study designs and health systems evaluated in the 64 animal studies that met
the problem formulation PECO criteria is provided in Figure C-3. Studies with inhalation and oral
routes of exposure were identified. Durations of exposure ranged from acute to chronic, and there
were several oral exposure studies that exposed animals during gestation. Inhalation exposure
studies were conducted in rats and mice, and oral exposure studies were conducted in rats, mice,
and rabbits. Seventeen of these studies met assessment PECO criteria based on the considerations
described in Section 5.1 and will be included in the assessment-specific approach.
Interactive versions of these literature inventory figures that include a more detailed
description of study designs and results are available on a Tableau Public dashboard, which also
allows users to filter for the subset of studies that are included under the assessment PECO criteria
(see Section 5).
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Inhalation
Nonspecific
Health system
Occupational
General
population
Children Occupational
General
population
Pregnant
women/infants
Children
Grand Total
Cardiometabolic
2
2
4
Developmental
4
1
5
Endocrine/Exocrine
3
3
Gastrointestinal
1
1
Hematological
1
1
1
3
Hepatic
2
2
Immunological
1
2
1
5
9
Nasal
1
1
Neurological
1
1
Pulmonary
1
1
1
3
Reproductive
6
2
8
Grand Total
4
1
2 1
13
8
9
38
# references
1 6
Figure C-2. Survey of human studies that met PECO criteria by study design and health systems assessed. The
numbers indicate the number of studies that investigated a particular health system, not the number of studies that
observed an association with naphthalene exposure. If a study evaluated multiple health outcomes, it is shown here
multiple times. An interactive version of this figure that includes a more detailed description of study designs and results is
available at the following URL:
https://public.tableau.com/app/profile/literature.inventory/viz/NaphthaleneEvidenceMapUSEPAIRISSystematicReviewP
rotocol2 02 2 /ReadMe?publish=ves
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Health system
Acute
Inhalation
Short term Subchronic
Chronic
Acute
Short term
Oral
Subchronic
Chronic
Gestational
Grand Total
Cardiometabolic
2
2
3
Cardiovascular
1
2
3
6
Developmental
5
5
Endocrine/Exocrine
1
2
2
5
Gastrointestinal
2
2
4
Hematological
1
1
4
5
Hepatic
1
2
2
3
7
2
16
Immunological
1
2
2
1
3
8
Musculoskeletal
2
2
4
Nasal
4
1
2
2
8
Neurological
1
2
1
3
6
Ocular
2
14
23
2
40
Pulmonary
6
3
3
1
4
16
Renal/Urinary
1
2
3
6
11
Reproductive
2
2
1
3
5
12
Whole body
1
1
1
3
1
2
9
1
4
21
Grand Total
9
1
3
3
5
14
24
2
5
64
# references
1 23
Figure C-3. Survey of animal studies that met PECO criteria by exposure duration, species, and health systems
assessed. The numbers indicate the number of studies that investigated a particular health system, not the number of
studies that observed an association with naphthalene exposure. If a study evaluated multiple species, study designs, or
heal th outcomes, it is shown here multiple times. An interactive version of this figure that includes a more detailed
description of study designs and results is available at the following URL:
https://public.tableau.com/app/profile/literature.inventorv/viz/NapthaleneEvidenceMapUSEPAIRISSystematicReviewPr
otocol2022/ReadMe?publish=yeshttps://public.tableau.com/app/profile/literature.inventorv/viz/NapthaleneEvidenceM
apUSEPAIRISSystematicReviewProtocol2022/ReadMe?publish=ves
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C.2. PHARMACOKINETIC (PK)/PHYSIOLOGICALLY BASED
PHARMACOKINETIC (PBPK) MODELS
The literature search identified nine peer-reviewed publications that describe novel, whole-
organism PBPK models for naphthalene fKapraun etal.. 2020: Celsie etal.. 2016: Campbell etal..
2014: Morris. 2013: Kim etal.. 2007: Willems etal.. 2001: NTP. 2000: Quick and Shuler. 1999:
Sweeney et al.. 19961 and eight additional peer-reviewed publications that describe applications of
PBPK models for naphthalene fBailev and Rhomberg. 2020: Clewell etal.. 2014: Viravaidva etal..
2004: Viravaidva and Shuler. 2004: Ghanem and Shuler. 2000a. b; Shuler etal.. 1996: Sweeney et al..
19951. Of the publications describing the application of PBPK models, six describe cell culture
analogs (CCAs) of PBPK models fViravaidva etal.. 2004: Viravaidva and Shuler. 2004: Ghanem and
Shuler. 2000a. b; Shuler etal.. 1996: Sweeney et al.. 19951. CCA models are constructed as in vitro
cell culture systems rather than in silico mathematical descriptions of whole organisms; thus, CCA
models cannot be efficiently utilized for risk assessment dosimetry calculations. The two remaining
publications involving applications of PBPK models describe studies that made use of existing PBPK
models.
The paragraphs that follow provide details of the nine publications that describe novel,
whole-organism PBPK models for naphthalene, as well as two publications fCorlev etal.. 2012:
Zhang and Kleinstreuer. 20111 that describe computational fluid dynamics (CFD) models that
inform naphthalene dosimetry. Table C-l provides summary information for these eleven models.
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Table C-l. Summary of Novel PBPK and Airway Dosimetry Models for Naphthalene
Citation
Species
Exposure routes
Metabolism3
Respiratory tract details
(Sweenev et al
1996)
Mouse
Rat
Oral
Intraperitoneal
Liver
Lung
Naphthalene oxidation
Naphthalene oxide:
o Hydrolysis
o GSH conjugation
o Rearrangement
o Covalent binding
None: A "lung" compartment is included
in the model as a site of metabolism, but
the model does not describe inhalation
exposure.
(Quick and
Shuler, 1999)
Mouse
Rat
Oral
Intraperitoneal
Intravenous
Inhalation
Liver
Lung
Naphthalene oxidation
Naphthalene oxide:
o Hydrolysis
o GSH conjugation
o Rearrangement
o Covalent binding
Pulmonary gas exchange
(NTP, 2000)
Mouse
Rat
Inhalation
Liver:
o Michaelis-Menten
o Hill
Lung:
o Michaelis-Menten
Naphthalene oxidation
Pulmonary gas exchange
(Willems et al.,
2001)
Mouse
Rat
Inhalation
Intravenous
Liver
Lung
Naphthalene oxidation
Naphthalene oxide:
o Hydrolysis
o GSH conjugation
Pulmonary gas exchange
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Citation
Species
Exposure routes
Metabolism3
Respiratory tract details
(Kim etal.. 2007)
Human
Inhalation
Dermal
Liver
Naphthalene oxidation
Pulmonary gas exchange
(Morris, 2013)
Mouse
Inhalation
Nasal
Naphthalene oxidation
Nasal airway compartments with air-
tissue mass transfer based on
computational fluid dynamics (CFD)
(Zhang and
Kleinstreuer,
2011)
Human
Inhalation
Noneb
Full CFD model of airways through the
upper tracheobronchial region
(Corlev et al
2012)c
Rat
Monkey
Human
Inhalation
Nasal
Conducting airways
Secondary bronchi
Bronchioles
Full CFD model of airways through the
secondary bronchi and bronchioles
(Celsie et al.,
2016)
Fish
Gills
Liver:
o First orderd
Naphthalene oxidation
None: Exchange of naphthalene
exchange between aqueous environment
and blood in gills similar to pulmonary
gas exchange in mammals.
(Campbell et al.,
2014)
Rat
Human
Inhalation
Liver
Lung
Nasal
Naphthalene oxidation
Nasal airway compartments with air-
tissue mass transfer based on CFD
Pulmonary gas exchange
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Citation
Species
Exposure routes
Metabolism3
Respiratory tract details
(Kaoraun et al.,
2020)
Rat
Human
Inhalation
Dermal
Intravenous
Liver
Lung
Nasal
Naphthalene oxidation
Nasal airway compartments with air-
tissue mass transfer based on CFD
Pulmonary gas exchange
aUnless otherwise indicated, metabolism is described using Michaelis-Menten rate equations.
bZhang and Kleinstreuer (2011) only described the concentration distribution in the airways but assumed that uptake by airway tissues is proportional to air
concentration. Thus, there is an implicit assumption of ongoing first-order removal of naphthalene from the airway lining and that metabolism may contribute
to that removal.
cThe model of Corlev et al. (2012) was not parameterized for naphthalene, but it is included in this summary because it is the most advanced air-phase vapor
deposition model for the rat, monkey, and human respiratory tracts, and as such, it could potentially inform naphthalene inhalation dosimetry.
dCelsie et al. (2016) included a term for first-order elimination of naphthalene in a liver compartment but no value for the parameter was given and a later
statement indicates that it was set to zero for the analysis of short duration exposures.
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The first naphthalene PBPK model published in the peer reviewed literature (Sweeney etal..
19961 describes the kinetics of naphthalene and naphthalene oxide in mice and rats. This model
was subsequently revised and extended by Quick and Shuler f!9991. The original model of Sweeney
etal. f!9961 contained five compartments (lung, fat, kidney, liver, and combined "other tissues"),
with saturable metabolism of naphthalene to the enantiomers of naphthalene oxide, as well as
subsequent hydrolysis to the 1,2-dihyrodiol, conjugation to GSH, non-enzymatic rearrangement to
1-naphthol, and covalent binding to intracellular protein occurring in lung and liver compartments.
Kinetic parameters for these processes were selected based on optimal fit to published in vitro
reaction data. The model facilitated predictions of internal doses following oral and intraperitoneal
(IP) exposures; however, rates of oral uptake were estimated in the absence of sufficient data. The
model was used to simulate available pharmacokinetic data for naphthalene, including GSH
conjugation and re-synthesis, covalent binding in lung and liver, and GSH concentration in lung and
liver; however, the simulation results were not evaluated against pharmacokinetic data for
naphthalene or its metabolites in blood or tissues.
The updated model published by Quick and Shuler (1999) has a structure similar to the
Sweeney et al. (1996) model, but it includes explicit arterial and venous blood compartments with
added intravenous (IV) and inhalation exposure routes. Kinetic parameters for metabolism of
naphthalene as well as metabolism, protein binding, and non-enzymatic rearrangement of
naphthalene oxide in mouse were updated using a separate whole cell model describing Club
(formerly Clara) cells and hepatocytes. Kinetic parameters in rat were fit to microsomal data and, in
the case of liver kinetics, adjusted based on data from the mouse whole cell model. The Quick and
Shuler (1999) model has several notable shortcomings. Though equations are given, the inhalation
route of exposure is not described in the methods, and a blood-to-air partition coefficient is not
stated in the text or in tables. Also, while the motivation for using whole cell rather than cellular
fraction (e.g., microsomal) kinetic data in the PBPK model is conceptually sound, particularly given
the heterogeneity of lung tissue and its potential role in the site- and species-specificity of
naphthalene toxicity, the description of how this was done is not sufficiently clear. Following IV
exposure, model simulation of naphthalene in blood by the mouse model over-predicted alpha
phase elimination and under-predicted beta phase elimination; predictions generated using the rat
model were more comparable to observed data during the beta phase, but still over-predicted alpha
phase elimination. Predictions of GSH and protein binding are reasonably accurate when compared
to available data, and improve upon the Sweeney etal. f 19961 model simulations, while the revised
model did not accurately predict GSH depletion and re-synthesis. Ultimately, though the authors'
approach to describing naphthalene metabolism has conceptual merit, the model is not robust or
accurate enough for use.
A novel PBPK model for naphthalene is described in the National Toxicology Program
Report on the Toxicology and Carcinogenesis Studies of Naphthalene in F344/N Rats (Inhalation
Studies) fNTP. 20001. The authors of the NTP f20001 report claimed, "this model was the best
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fitting product [for the data analyzed in the report] after testing several alternative models." The
"alternative models" included the models of Sweeney etal. (19961 and Quick and Shuler (19991.
The NTP f20001 model included a second metabolic rate term "in the form of a Hill equation" into
the equation describing the amount of naphthalene in the liver. This second Hill term for
metabolism was not included in any of the other identified PBPK models for naphthalene. Notably
the NTP f20001 model was constructed based on an assumption of diffusion-limited, rather than
perfusion-limited kinetics. That is, for each of the five tissues represented in the model (lung, liver,
kidney, fat, and "other"), the model includes one state variable for amount in the tissue and another
for amount in the capillary blood of that tissue. In the model, diffusion between capillary blood and
tissue depends on the difference in concentrations in those two compartments as well as a
parameter describing capillary permeability.
The rat and mouse model of Willems etal. f20011 uses parallel sub-models for naphthalene
(parent) and naphthalene oxide (metabolite) as described by Sweeney etal. (19961 and Quick and
Shuler (19991. but incorporates diffusion-limited compartments in the parent sub-model as was
done in the NTP (20001 model. As in the model of Quick and Shuler (19991. each sub-model
includes compartments for lung, fat, kidney, liver, and "other" tissues, as well as explicit arterial and
venous blood compartments. Saturable metabolism of naphthalene was included in lung and liver
compartments. Metabolic rate and tissue permeability constants were optimized from blood time-
course data from inhalation exposures. Performance of the rat model was evaluated against
naphthalene (but not naphthalene oxide) blood time course concentration data following IV
exposure; the mouse model was not evaluated against independent pharmacokinetic data. The
predictions of IV rat data are reasonably accurate, though the data suggest naphthalene may be
eliminated more slowly from blood than model predictions indicate. The authors state that the
model as written does not explain the apparent interspecies differences in naphthalene toxicity in
the lung, nor does it address nasal toxicity in either species.
The human model of Kim etal. f20071 describes the PK behavior of naphthalene as a
surrogate for jet propulsion fuel 8 (JP-8). The model contains five compartments two
representing layers of skin (the exposed portion of the stratum corneum, and viable epidermis
directly beneath this) and three representing the rest of the body (blood, fat, and combined other
tissues) and simulates dermal and inhalation exposures. First order metabolism of naphthalene
to naphthalene-oxide by the liver is included in the blood compartment. Notably, the authors report
measurement of a human blood-to-air partition coefficient of 10.3, which is considerably lower
than the rodent value of 571 reported by Willems etal. f20011. Rate constants describing uptake
and diffusion in the skin compartments and partition coefficients for fat-to-blood and other-tissues-
to-blood were optimized to fit time course blood concentration data for each of 10 subjects
included in a controlled dermal exposure study (Kim etal.. 20061. Average parameter values were
then used to define an "optimal" overall parameter set. The optimized model was used to predict
concentrations of naphthalene in exhaled breath of 53 U.S. Air Force personnel exposed to
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naphthalene via inhalation (without dermal contact), as well as 3 U.S. Air Force personnel exposed
via inhalation and dermal contact These predictions consistently overestimated observed data by 1
to 2 orders of magnitude unless inhalation concentrations were adjusted; while some rationale for
this adjustment was provided, details of the adjustment were not described. Inadequate model
validation and a limited treatment of respiratory tissues relevant to naphthalene toxicity reduce the
utility of the Kim etal. f20071 model for the purposes of this assessment
A hybrid computational fluid dynamic (CFD) and PBPK model (i.e., a "hybrid CFD-PBPK
model") for nasal dosimetry of naphthalene in the upper respiratory tract (URT) of mice was
described by Morris (2013). (Note that while the terms "CFD-PBPK model" and "hybrid CFD-PBPK
model" are commonly used to describe PBPK models that have been informed by CFD models of
airways [e.g., to determine parameters that describe rates and proportions of deposition for PBPK
model compartments representing parts of the respiratory tract], these "hybrid" models do not
actually incorporate CFD partial differential equations.) The model structure was based on that of
the Gloede etal. (2011) CFD-PBPK model for diacetyl: stacks of compartments corresponding to the
airspace, mucus, epithelium, and sub mucosa are described for relevant portions of the URT
(including dorsal and ventral respiratory regions and a dorsal olfactory region). Other body tissues
are not explicitly described, only the nasal epithelium and sub-mucosa. The model assumes
saturable rates of metabolism in the epithelial and submucosal sub-compartments, with maximal
rates specified for each region of the respiratory tract Model prediction of uptake efficiency by the
entire URT (i.e., all compartments representing components of the URT) was accurate when
compared to observed data on vapor uptake in isolated URTs of mice; however, dosimetry
predictions for the described individual portions of the URT could not be evaluated since PK data
specific to the URT sub-regions is not available, and therefore the validity of the model's complex
nasal structure cannot be confirmed.
Zhang and Kleinstreuer f20111 developed a full CFD model that predicts deposition of
naphthalene in the human respiratory tract Note that the Zhang and Kleinstreuer f20111 model is
not a PBPK model, but a type of dosimetry model. The model uses a geometrically accurate model of
the airways through the upper tracheobronchial region, with a level of resolution that is lost in the
development of hybrid CFD-PBPK models. However, the model of Zhang and Kleinstreuer (2011)
does not have airway tissue compartments and assumes a rate of uptake by the airway lining that is
simply proportional to the concentration of naphthalene in the adjacent air, i.e., it does not account
for metabolic saturation but implicitly assumes ongoing elimination of naphthalene such that it
does not accumulate in the airway lining. Results from this model might still be valid at low
exposure levels, below saturation, but could only be used in extrapolation of naphthalene
deposition or tissue flux predicted by a rodent CFD-PBPK model. Further, tabulated results
reported by the authors only give uptake by major anatomical region; the nasal cavity is not sub-
divided into olfactory and respiratory tissues. Thus, the model is limited in utility and does not
incorporate the human vs. rodent differences in metabolic rate observed in vitro.
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More recently, Corley and colleagues developed fCorlev etal.. 20121 and applied fCorlev et
al.. 2015] a full CFD model for rats, monkeys, and humans, which includes two tissue layers (mucus
+ epithelium and sub-epithelium) and which allows for removal by a first-order pathway and a
saturable metabolic pathway in each layer, plus blood perfusion in the sub-epithelium. The model
defines separate areas for respiratory and olfactory epithelia in the nose. While the models of
Corley etal. f20121 might not include compartments for the rest of the body, they otherwise
represent the most anatomically accurate representation of airway geometry and vapor disposition
in rats, monkeys, and humans, with a good level of detail for the airway tissues. The primary barrier
to further consideration of these CFD models is that they have not been parameterized for
naphthalene, which would require setting the metabolic parameters in each airway region
appropriately. The Corley etal. f20121 model is not a whole-body PBPK model but includes
compartments for respiratory tissues with parameters set based on anatomical and physiological
data, like the model of Morris (2013). While it was not parameterized for naphthalene, it is
described here because it is the most advanced model of air-phase vapor deposition for the rat,
monkey, and human airways, with high anatomical accuracy and the capacity to incorporate first-
order and saturable metabolism in the tissues.
Celsie etal. f20161 developed a PBPK model for narcotic organic chemicals in fish and
parameterized the model for describing naphthalene concentrations in fathead minnows. This
model includes compartments for gills, blood, liver, rapidly perfused tissue, and slowly perfused
tissue, as well as a compartment for "membrane," which is the assumed target site of toxicity. The
Celsie etal. (2016) model allows for simulations of aquatic exposures via the gills, which are
analogous to but anatomically and physiologically different from mammalian lungs. Furthermore,
the Celsie etal. (2016) model equations are constructed in the "fugacity format," making them quite
different from PBPK model equations typically used for mammalian species. The state variables of
the model are time-varying fugacities (Pascals), and these can be used along with constant "fugacity
capacities" (moles per cubic meter per Pascal) to calculate concentrations in the various model
compartments. While the Celsie etal. (2016) model could potentially be adapted to create a PBPK
model for mammalian dosimetry, the resulting model would need to be evaluated using
naphthalene PK data in the species of interest. Also, the Celsie etal. (2016) model lacks URT
compartments which allow for tissue- and site-specific dosimetry in the URT. Thus, this model is
not ideal for the current human health assessment application.
Campbell et al. f20141 published a CFD-PBPK model for naphthalene in rats and humans.
Unlike the model of Morris f20131. this model includes compartments representative of the entire
body rather than just the URT. The URT components were based on published inhalation-route
models for vinyl acetate (Bogdanffv et al.. 1999) and acetaldehyde (Teeguarden etal.. 2008) and are
organized into two parallel airways: (1) the dorsal path, comprising sequential compartments for
respiratory epithelium and one or two olfactory compartments; and (2) the ventral path,
comprising two respiratory epithelium compartments. One dorsal olfactory compartment was used
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for the human model, whereas two dorsal olfactory compartments were used for the rat model.
Similar to the Morris (20131 CFD-PBPK model for mice, the Campbell etal. (20141 model
represents each of the URT compartments with multiple layers. In the case of the Campbell et al.
f20141 model, each URT compartment consists of lumen, epithelial cell layer, and submucosal
tissue sub-compartments. In addition to the URT compartments, the model includes compartments
for lung, fat, liver, slowly perfused, and rapidly perfused tissues. Time-course data for naphthalene
concentrations in rat blood after single IV doses (Quick and Shuler. 19991 and 6-hour inhalation
exposures (NTP. 20001. as well as rat upper respiratory tract extraction data at fixed inspiratory
flow rates (Morris and Buckpitt. 20091. were used to evaluate the accuracy of rat model predictions.
As was the case for the Morris and Buckpitt f2 0091 model, dosimetry predictions for distinct sub-
regions of the URT could not be evaluated since PK data specific to the represented URT sub-
regions is not available. Also, while Campbell etal. f20141 showed that their rat model simulations
generally reproduced observed rat data to within a factor of 2 (and in the worst case, to within a
factor of 3), time-course data for humans exposed to naphthalene via the inhalation route were not
available to evaluate the human model predictions.
Kapraun et al. (20201 revised the PBPK model of Campbell etal. (20141 by adding
compartments that allow one to simulate skin exposure. (See Table C-2 for descriptive summary.)
This enhancement allowed Kapraun etal. f20201 to evaluate their PBPK model using data from a
controlled skin exposure study in human subjects fKim etal.. 20061 and demonstrate that model
predictions of time-course blood concentrations of naphthalene generally agree with observed
human in vivo data to within a factor of two. Such agreement supports the general practice that
PBPK model dosimetry, rather than allometric scaling or other default approaches, are preferred
for dosimetry calculations (U.S. EPA. 2020c: IPCS. 20101. Kapraun etal. (20201 implemented the
model using R version 3.6.1 fR Core Team. 20191 and MCSim fBois. 20091 and applied the quality
assurance guidelines of U.S. EPA f2018dl to verify parameter values and various other aspects of
the software implementation of the model. A complete set of model implementation files for the
Kapraun et al. (20201 PBPK model are available through the U.S. EPA Environmental Dataset
Gateway (https: / /doi.org/10.23719 /15190441. When the skin compartments of the Kapraun et al.
(20201 model are turned "off" (by setting the volumes and blood flow rates for those compartments
to zero), that PBPK model is functionally equivalent to the PBPK model of Campbell etal. (20141.
The Kapraun et al. f20201 model will be used for this assessment. Further details of this model can
be found in Table C-2.
As discussed in the preceding paragraphs, the validity of the Morris (2013). Campbell
et al. (2014) and Kapraun et al. (2020) models' complex nasal structures cannot be
confirmed. The lack of validation data for URT sub-regions is an issue common to most
CFD-PBPK models since measurement of regional tissue samples is technically challenging
and ongoing metabolism or volatilization of an inhaled gas from the tissue during collection
and initial processing of tissue would confound any attempt to make such measurements.
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Protocol for the Naphthalene IRIS Assessment
Whenever model predictions of total URT uptake have been validated (as is the case for the
Campbell et al. (2014) and Morris (2013) models), the primary remaining question is
whether or not the model correctly predicts the fraction of uptake (and removal) assigned
to each sub-region. As long as the regional model structures and parameters are consistent,
or varied according to anatomical, biochemical, and physiological data, one can have
reasonable confidence in the model predictions. If the model under-predicts uptake in one
URT sub-region, it must over-predict uptake in another region in order to achieve the
overall mass balance. It should be noted, however, that if the predicted differences in
uptake between sub-regions are based on conservation of mass, anatomical features, and
CFD predictions based on the anatomy, it is unlikely that predictions for two different
regions would have significant errors in opposite directions. Thus, whenever total URT
uptake has been validated using experimental data, CFD-PBPK model predictions for sub-
regions of the URT can be assumed to be reasonably accurate. In some cases, Monte Carlo
simulations have been performed with PBPK models to assess uncertainty and variability
in dose metrics [e.g., in the IRIS Toxicological Review of Dichloromethane (TJ.S. EPA.
2011b)"|. However, performing a Monte Carlo (MC) analysis with the Campbell et al. (2014)
and Kapraun et al. (2020) PBPK models for naphthalene would be because the values used
for parameters that describe the respiratory tract have only been defined for humans and
rats of specific sizes (i.e., body masses) the way these parameters vary for animals and
humans with different body sizes has not been characterized.
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Protocol for the Naphthalene IRIS Assessment
Table C-2. Descriptive summary for the Kapraun etal. (2020) CFD-PBPK
model
Study detail
Description/notes
Author
Kapraun et al. (2020)
Contact email
mkapraun.dustin@epa.gov
Contact phone
919-541-4045
Sponsor
U.S. EPA
Model summary
Species
Rat
Human
Strain
F433
N/A
Sex
Male and female
Life stage
Adult
Exposure routes
Inhalation
IV
Skin
Tissue dosimetry
Blood
URT tissues
Model evaluation
Language
R and MCSim
Code available
YES
Effort to recreate model
COMPLETE
Code received
YES
Effort to migrate to open software (R/MCSim)
COMPLETE
Structure evaluated
YES
Math evaluated
YES
Code evaluated
YES
Available PK data
Time-course data for naphthalene concentrations in rat blood after single intravenous
doses (Quick and Shuler, 1999); time-course data for naphthalene concentrations in rat
blood following 6-hour inhalation exposures (NTP, 2000); rat upper respiratory tract
extraction data at fixed inspiratory flow rates (Morris and Buckpitt, 2009); and time-
course dermal penetration (tape strip) and blood concentration data following
controlled dermal exposure in humans (Kim et al., 2006).
This document is a draft for review purposes only and does not constitute Agency policy.
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