EPA/630/P-03/001A
                                                         NCEA-F-0644A
                                                           February 2003
                                                             Draft Final
                                         www.epa.gov/ncea/raf/canccr2003.htm
                  Draft Final Guidelines for
                Carcinogen Risk Assessment
                           Risk Assessment Forum
                     U.S. Environmental Protection Agency
                             Washington, DC
February 27, 2003                                 DRAFT FINAL - DO NOT CITE OR QUOTE

-------
                                    DISCLAIMER
      This is a draft final document and does not, at this time, constitute U.S. Environmental
Protection Agency policy. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
February 27, 2003                          ii             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
                                   CONTENTS

1.  INTRODUCTION  	1-1
       1.1.  PURPOSE AND SCOPE OF THE GUIDELINES	1-1
       1.2.  ORGANIZATION AND APPLICATION OF THE GUIDELINES	1-2
             1.2.1. Organization	1-2
             1.2.2. Application	1-4
       1.3.  KEY FEATURES OF THE GUIDELINES	1-5
             1.3.1. Use of Default Options	1-5
             1.3.2. Mode of Action	1-7
             1.3.3. Weight of Evidence Narrative  	1-8
             1.3.4. Dose-response Assessment	1-9
             1.3.5. Susceptible Populations and Lifestages 	1-11
             1.3.6. Evaluating Risks from Childhood Exposures	1-11
             1.3.7. Emphasis on Characterization  	1-14

2.  HAZARD ASSESSMENT	2-1
       2.1.  OVERVIEW OF HAZARD ASSESSMENT AND CHARACTERIZATION ... 2-1
             2.1.1. Analyses of Data	2-1
             2.1.2. Presentation of Results	2-1
       2.2.  ANALYSIS OF TUMOR DATA 	2-2
             2.2.1. Human Data  	2-2
                   2.2.1.1.  Types of Studies	2-3
                   2.2.1.2.  Assessing the Quality of Epidemiologic Studies	2-4
                         2.2.1.2.1. Population issues	2-5
                         2.2.1.2.2. Exposure issues	2-5
                         2.2.1.2.3. Confounding factors	2-6
                         2.2.1.2.4. Likelihood of observing an effect	2-6
                         2.2.1.2.5.  Statistical considerations	2-7
                         2.2.1.2.6. Combining statistical evidence across studies 	2-7
                   2.2.1.3.  Evidence for Causality	2-8
                   2.2.1.4.  Assessment of Evidence of Carcinogenicity from Human Data
                           	2-9
             2.2.2. Animal Data  	2-9

February 27,2003                         iii            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
                    2.2.2.1.  Long-term Carcinogenicity Studies	2-10
                          2.2.2.1.1. Dosing issues  	2-11
                          2.2.2.1.2. Statistical considerations	2-13
                          2.2.2.1.3. Concurrent and historical controls 	2-14
                          2.2.2.1.4. Assessment of evidence of carcinogenicity from long-
                                 term animal studies  	2-15
                          2.2.2.1.5. Site concordance	2-16
                    2.2.2.2.  Perinatal Carcinogenicity Studies  	2-16
             2.2.3. Structural Analogue Data	2-18
       2.3. ANALYSIS OF OTHER KEY DATA 	2-18
             2.3.1. Physicochemical Properties 	2-18
             2.3.2. Structure-Activity Relationships	2-19
             2.3.3. Comparative Metabolism and Toxicokinetics  	2-20
             2.3.4. Toxicological and Clinical Findings	2-22
             2.3.5. Events Relevant to Mode of Carcinogenic Action	2-22
                    2.3.5.1.  Direct DNA-Reactive Effects 	2-23
                    2.3.5.2.  Indirect DNA Effects or Other Effects on Genes/Gene Expression
                            	2-24
                    2.3.5.3.  Experimental Considerations in Evaluating Data on Precursor
                          Events	2-25
                    2.3.5.4.  Judging Data	 2-26
       2.4. BIOMARKER INFORMATION	2-26
       2.5.   MODE OF ACTION—GENERAL CONSIDERATIONS AND FRAMEWORK
             FORANALYSIS	2-28
             2.5.1. General Considerations	2-28
             2.5.2. Evaluating a Hypothesized Mode of Action	2-30
                    2.5.2.1.  Peer Review	 2-30
                    2.5.2.2.  Use of the Framework	2-30
             2.5.3. Framework for Evaluating Each Hypothesized Carcinogenic Mode of
                    Action	2-31
                    2.5.3.1.  Description of the Hypothesized Mode of Action	2-33
                    2.5.3.2.  Discussion of the Experimental Support for the Hypothesized
                          Mode of Action  	2-33
                    2.5.3.3.  Consideration of the Possibility of Other Modes of Action  . 2-35

February 27, 2003                          iv             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
                  2.5.3.4. Conclusions About the Hypothesized Mode of Action	2-36
      2.6. WEIGHT OF EVIDENCE NARRATIVE	2-37
      2.7. HAZARD CHARACTERIZATION	2-44

3.  DOSE-RESPONSE ASSESSMENT  	3-1
      3.1. ANALYSIS OF DOSE  	3-2
            3.1.1.  Standardizing Different Experimental Dosing Regimens 	3-3
            3.1.2.  Toxicokinetic Modeling	3-4
            3.1.3.  Cross-species Scaling Procedures	3-5
            3.1.4.  Route Extrapolation 	3-7
      3.2. ANALYSIS IN THE RANGE OF OBSERVATION	3-8
            3.2.1.  Analysis of Epidemiologic Studies	3-8
            3.2.2.  Toxicodynamic ("Biologically Based") Modeling	3-10
            3.2.3.  Empirical Modeling ("Curve Fitting")	3-11
            3.2.4.  Point of Departure	3-12
            3.2.5.  Characterizing the POD: the POD Narrative 	3-13
            3.2.6.  Relative Potency Factors  	3-15
      3.3. EXTRAPOLATION TO LOWER DOSES	3-15
            3.3.1.  Choosing an Extrapolation Approach	3-15
            3.3.2.  Extrapolation Using a Toxicodynamic Model 	3-17
            3.3.3.  Nonlinear Extrapolation to Lower Doses	3-17
            3.3.4.  Extrapolation Using a Low-dose Linear Model	3-18
            3.3.5.  Comparing and Combining Multiple Extrapolations	3-19
      3.4. EXTRAPOLATION TO DIFFERENT HUMAN EXPOSURE SCENARIOS
             	3-20
      3.5. EXTRAPOLATION TO SUSCEPTIBLE POPULATIONS AND LIFESTAGES3-21
      3.6. UNCERTAINTY	3-22
      3.7. DOSE-RESPONSE CHARACTERIZATION 	3-25

4.  EXPOSURE ASSESSMENT	4-1
      4.1. DEFINING THE ASSESSMENT QUESTIONS 	4-1
      4.2. SELECTING OR DEVELOPING THE CONCEPTUAL AND MATHEMATICAL
            MODELS	4-2
February 27, 2003                        v            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
      4.3. COLLECTING DATA OR SELECTING AND EVALUATING AVAILABLE
            DATA	4-3
            4.3.1. Adjusting Unit Risks for Highly Exposed Populations and Lifestages  . 4-4
      4.4. EXPOSURE CHARACTERIZATION	4-5

5.  RISK CHARACTERIZATION 	5-1
      5.1. PURPOSE  	5-1
      5.2. APPLICATION	5-2
      5.3. PRESENTATION OF THE RISK CHARACTERIZATION SUMMARY	5-3
      5.4. CONTENT OF THE RISK CHARACTERIZATION SUMMARY	5-3

APPENDIX: MAJOR DEFAULT OPTIONS  	 A-l

REFERENCES  	R-l

                             List of Figures

Figure 1-1. Risk Assessment of Childhood Exposures	1-15
Figure 3-1. Compatibility of Alternative Points of Departure with Observed and Modeled
            Tumor Incidences	3-28
Figure 3-2. Crossing between  10% and 1% Dose-Response Curves for Bladder Carcinomas and
            Liver Carcinomas Induced by 2-AAF	3-28
February 27, 2003                       vi           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1                                       1. INTRODUCTION
 2
 3      1.1. PURPOSE AND SCOPE OF THE GUIDELINES
 4            These guidelines revise and replace the U.S. Environmental Protection Agency's (EPA's,
 5      or the Agency's) Guidelines for Carcinogen Risk Assessment, published in 51 FR 33992,
 6      September 24, 1986 (U.S. EPA, 1986a) and the 1999 draft guidelines (U.S. EPA, 1999a). They
 7      provide EPA staff and decisionmakers with guidance for developing and using risk assessments.
 8      They also provide basic information to the public about the Agency's risk assessment methods.
 9      These guidelines are used with other risk assessment guidelines that the Agency has developed,
10      such as the Guidelines for Mutagenicity Risk Assessment (U.S. EPA,  1986b) and the Guidelines
11     for Exposure Assessment (U.S. EPA, 1992a).  Consideration of other Agency guidance
12      documents is particularly important when procedures for evaluating specific target organ effects
13      have been developed (e.g., assessment of thyroid follicular cell tumors, U.S. EPA, 1998a) or
14      when there is a concern for a particular susceptible subpopulation for which the Agency has
15      developed guidance, for example, Guidelines for Developmental Toxicity Risk Assessment (U.S.
16      EPA, 199la).  These guidelines discuss hazards to children that may result from exposures
17      during preconception and prenatal or postnatal development to sexual maturity. Similar
18      guidelines exist for reproductive toxicant risk assessments (U.S. EPA, 1996a) and for
19      neurotoxicity risk assessment (U.S. EPA, 1998b).
20            All of these guidelines should be consulted when conducting a risk assessment in order to
21      ensure that information from studies on carcinogenesis and other health effects are considered
22      together in the overall characterization of risk. This is particularly true in the case in which a
23      precursor effect to tumor is also a precursor or endpoint of other health effects and is used in
24      dose-response assessment. The overall characterization of risk is the basis for carrying out
25      assessments of instances in which fetuses, infants, or children are at risk or disproportionately
26      affected by economically significant Agency actions.  Characterization for the latter purpose is
27      outlined in the Agency guidance by the Office of Children's Health Protection to carry out
28      Executive Order 13045, "Protection of Children From Environmental Health Risks and Safety
29      Risks," issued on April 21, 1997.
30            The guidelines encourage both regularity in procedures to support consistency in
31      scientific components of Agency decision making and innovation to remain up to date in
32      scientific thinking. In balancing these goals, the Agency relies on established scientific peer
33      review processes (U.S. EPA, 2000a).  The guidelines incorporate basic principles and science
34      policies based on evaluation of the currently available information. As more is discovered about

        February 27, 2003                  ,       1-1             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1      carcinogenesis, the need will arise to make appropriate changes in risk assessment guidance.
  2      The Agency intends to revise these guidelines when extensive changes are due. In the interim,
  3      the Agency intends to issue special reports, after appropriate peer review, to supplement and
  4      update guidance on single topics (e.g., U.S. EPA, 1991b).  The consideration of new, peer-
  5      reviewed scientific understanding and data in an assessment is always consistent with the
  6      purposes of these guidelines.
  7            These guidelines are intended as guidance only. They do not establish any substantive
  8      "rules" under the Administrative Procedure Act or any other law and will have no binding effect
  9      on EPA  or any regulated entity, but instead represent a non-binding statement of policy. EPA
10      believes that the guidelines represent a sound and up-to-date approach to cancer risk assessment,
11      and the guidelines enhance the application of the best available science in EPA's risk
12      assessments. However, EPA cancer risk assessments may be conducted differently than
13      envisioned in the guidelines for many reasons, including (but not limited to) new information,
14      new scientific understanding, or new science policy judgment.  The science of risk assessment
15      continues to develop rapidly, and specific components of the guidelines may become outdated or
16      may otherwise require modification in individual settings.  Use of the guidelines in future risk
17      assessments will be based on decisions by EPA that approaches are suitable  and appropriate in
18      the context of those particular risk assessments. These judgments will be tested through peer
19      review, and risk assessments will be modified to use different approaches if appropriate.
20
21      1.2. ORGANIZATION AND APPLICATION OF THE GUIDELINES
22      1.2.1.  Organization
23            Publications by the Office of Science and Technology (OSTP, 1985) and the National
24      Research Council (NRC) (NRC, 1983, 1994) provide information and general principles about
25      risk assessment. Risk assessment uses available scientific  information  on the properties of an
26      agent1 and its effects in biological systems to provide an evaluation of the potential for harm as a
27      consequence of environmental exposure.  The 1983 and 1994 NRC documents organize risk
28      assessment information into four areas: hazard identification, dose-response assessment,
29      exposure assessment, and risk characterization. This structure appears  in these guidelines, which
30      additionally emphasize characterization of evidence and conclusions in each part of the
31      assessment. In particular, the guidelines adopt the approach of the NRC's 1994 report in adding
32      a dimension of characterization to the hazard identification step. Added to the identification of
              1 The term "agent" refers generally to any chemical substance, mixture, or physical or biological entity
        being assessed, unless otherwise noted (See Section 1.2.2 for a note on radiation.).

        February 27, 2003                          1 -2            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      hazard is an evaluation of the conditions under which its expression is anticipated. The risk
  2      assessment questions addressed in these guidelines are:
  3
  4            •    For hazard—Can the agent present a carcinogenic hazard to humans and, if so,
  5                 under what circumstances?
  6
  7            •    For dose response—At what levels of exposure might effects occur?
  8
  9            •    For exposure—What are the conditions of human exposure?
10
11            •    For risk—What is the character of the risk?  How well do data support conclusions
12                 about the nature and extent of the risk?
13
14            The risk characterization process first summarizes findings on hazard, dose response, and
15      exposure characterizations and then develops an integrative analysis of the whole risk case. It
16      ends in a nontechnical risk characterization summary. The summary is a presentation for risk
17      managers who may or may not be familiar with the scientific details of cancer assessment. It
18      also provides information for other interested readers. The initial steps in the risk
19      characterization process are to make building blocks in the form of characterizations of the
20      assessments of hazard, dose response, and exposure. The individual assessments and
21      characterizations are then integrated to arrive at risk estimates for exposure scenarios of interest.
22      As part of the characterization process, explicit evaluations are made of the hazard and risk
23      potential for susceptible populations, including children (U.S. EPA, 1995, 2000b).
24            There are two reasons for individually characterizing the hazard, dose response, and
25      exposure assessments. One is that they are often done by different people than those who do the
26      integrative analyses. The second is that there is very often a lapse of time between the conduct
27      of hazard and dose-response analyses and the conduct of exposure assessment and integrative
28      analysis. Thus, it is important to capture characterizations of assessments as the assessments are
29      done to avoid the need to go back and reconstruct them.  Finally, frequently a single hazard
30      assessment is used by several programs for several different exposure scenarios. There may be
31      one or several documents involved.  "Integrative analysis" is a generic term. At EPA, the
32      documents of various programs that contain integrative analyses have other names, such as the
33      "Staff Paper," which discusses air quality criteria issues.  In the following sections, the elements
34      of these  characterizations are discussed.

        February 27, 2003                          1 -3            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      1.2.2. Application
  2            The guidelines apply within the framework of policies provided by applicable EPA
  3      statutes and do not alter such policies. The guidelines cover assessment of available data. They
  4      do not imply that one kind of data or another is prerequisite for regulatory action concerning any
  5      agent. It is important to remember that when judging and considering the use of any data, the
  6      basic standard of quality, as defined by the EPA Information Quality Guidelines (U.S. EPA,
  7      2002a), should be satisfied. It is very important that all analyses adhere to the basic standards of
  8      quality, including objectivity, utility, and integrity.  Risk management applies directives in
  9      statutes, which may require consideration of potential risk or solely hazard or exposure potential,
10      along with social, economic, technical, and other factors in decision making.  Risk assessments
11      may be used to support decisions, but in  order to maintain their integrity as decision-making
12      tools, they are not influenced by consideration of the social or economic consequences of
13      regulatory action.
14            The assessment of risk from radiation sources is based on continuing examination of
15      human data by the National Academy of Sciences/NRC in its series of numbered reports:
16      "Biological Effects of Ionizing Radiation." Although the general principles of these guidelines
17      apply to radiation risk assessments, their details are most  focused on other kinds of agents. They
18      do not attempt to guide the ongoing conduct of radiation risk assessment.
19            Not every EPA assessment has the same scope or  depth. When a cancer risk assessment
20      is influential information as defined in OMB and EPA information-quality guidelines (OMB,
21      2002; U.S. EPA, 2002a), EPA staff and decision makers should make sure that information-
22      quality performance goals are satisfied. On the other hand, Agency staff often conduct
23      screening-level assessments for priority setting or separate assessments of hazard or exposure for
24      ranking purposes or to decide whether to invest resources in collecting data for a full assessment.
25      Moreover, a given assessment of hazard  and dose response may be used with more than one
26      exposure assessment that may be conducted separately and at different times as the need arises in
27      studying environmental problems  in various media. The guidelines apply to these various
28      situations in appropriate detail, given the scope and depth of the particular assessment. For
29      example, a screening assessment may be based almost entirely on structure-activity relationships
30      (SARs) and default options. As more data become available, assessments can replace or modify
31      default options accordingly. These guidelines do not suggest that all of the kinds of data covered
32      here be available for either assessment or decision making.  The level of detail of an assessment
33      is a matter of Agency management discretion regarding applicable decision making needs.
34

        February 27, 2003                          1 -4             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      1.3. KEY FEATURES OF THE GUIDELINES
  2      1.3.1. Use of Default Options
  3             NRC (1994) reaffirmed the use of default options as "a reasonable way to cope with
  4      uncertainty about the choice of appropriate models or theory" (p. 104). It saw the need to treat
  5      uncertainty in a predictable way that is "scientifically defensible, consistent with the agency's
  6      statutory mission, and responsive to the needs of decision-makers" (p. 86). Accordingly, default
  7      options have a science component and a policy component.
  8             Encouraging risk assessors to be receptive to new scientific information, NRC discussed
  9      the need for departures from default options when a "sufficient showing" is made. It called on
10      EPA to articulate clearly its criteria for a departure so that decisions to depart from default
11      options would be "scientifically credible and receive public acceptance" (p. 91). It was
12      concerned that ad hoc departures would undercut the scientific credibility of a risk assessment.
13      NRC envisioned that principles for choosing and departing from default options would balance
14      several conflicting objectives, including "protecting the public health, ensuring scientific
15      validity, minimizing serious errors in estimating risks, maximizing incentives for research,
16      creating an orderly and predictable process, and fostering openness and trustworthiness" (p. 81).
17            NRC discussed two opposing principles for governing departures from default options.
18      One suggested principle would evaluate a departure in terms of whether "it is scientifically
19      plausible" and whether it "tends to protect public health in the face of scientific uncertainty" (p.
20      601).  An opposing principle "emphasizes scientific plausibility with regard to the use of
21      alternative models" (p.631). Reaching no consensus on a single  approach, NRC recognized that
22      developing criteria for departures is an EPA policy matter.
23            With increasing  understanding becoming available, these guidelines adopt a view of
24      default options that is consistent with EPA's mission to protect human health. Rather than
25      viewing default options as the starting point from which departures may be justified by new
26      scientific information, these guidelines view a critical analysis of the available information as the
27      starting point from which a default option may be invoked if needed to address uncertainty or the
28      absence of critical information. The primary goal of EPA actions is public health protection;
29      accordingly, as an Agency policy, any default options used in the absence of scientific data to the
30      contrary should be health protective (U.S. EPA, 1999b).
31            The basis for invoking a default option depends  on the circumstances. Generally, if a gap
32      in basic understanding exists or if agent-specific information is missing, a default option can be
33      used.  If agent-specific information is present but critical analysis reveals inadequacies, a default
34      option can also be used.  If critical analysis of agent-specific information is consistent with one

        February 27,2003                           1-5             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1      or more alternative models and with the default option, the alternative models and the default
 2      option are carried through the assessment and characterized for the risk manager.  This latter
 3      case highlights the importance of extensive experimentation to support a conclusion about mode
 4      of action, including addressing the issue of whether alternative modes of action are also
 5      plausible.  Section 2.5 provides a framework for critical analysis of mode of action information
 6      to address the extent to which the available information supports the hypothesized mode of
 7      action, whether alternative modes of action are also plausible, and whether there is confidence
 8      that the same inferences can be extended to populations and lifestages that are not represented
 9      among the experimental data.
10            Generally, these decisions strive to be "scientifically defensible, consistent with the
11      agency's statutory mission, and responsive to the needs of decision-makers" (NRC, 1994, p. 86).
12      Scientific defensibility would be evaluated through use of EPA's Science Advisory Board or
13      other independent expert peer review panels to determine whether a consensus among
14      knowledgeable scientists exists.  Consistency with the Agency's statutory mission would
15      consider whether the risk assessment overall supports EPA's mission to protect human health and
16      safeguard the natural environment. Responsiveness to the needs of decisionmakers would take
17      into account pragmatic considerations such as the nature of the decision; the required depth of
18      analysis; the utility, time, and cost of generating new scientific data; and the time, personnel, and
19      resources allotted to the risk assessment.
20            With a multitude of types of risk assessments and potential default options, it is neither
21      possible nor desirable to specify step-by-step criteria for decisions to invoke a default option. A
22      discussion of major default options appears in the Appendix. Screening-level assessments may
23      more readily use default options, even worst-case assumptions, that would not be appropriate in
24      a full-scale assessment. Some default options are conveniences that allow an analysis to proceed
25      and may be easily used with minimal explanation. For example, a cross-species scaling factor is
26      readily available as a default option if a toxicokinetic model is not used, and standard animal
27      body weights are a further default option-if actual body weights are not available.
28            When toxicokinetic or toxicodynamic models are developed, a quantitative uncertainty
29      analysis would be useful for determining whether the model is sufficiently robust to support a
30      decision. If insufficient data or understanding limit development of a robust model, an
31      appropriate policy choice is to have a single preferred curve-fitting model for each type of data
32      set.  Many different curve-fitting models have been developed, and those that fit the observed
33      data reasonably well may lead to several-fold differences in estimated risk at the lower end of the
34      observed range. This presents a problem in providing assurance that risk estimates were not

        February 27,2003                           1-6             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1      obtained by choosing to present only those models that gave the most desired result.  Another
  2      problem occurs when a multitude of alternatives are presented without sufficient context to make
  3      a reasoned judgment about the alternatives. This form of model uncertainty reflects primarily
  4      the availability of different computer models and not biological information about the agent
  5      being assessed or about carcinogenesis in general. In cases where curve-fitting models are used
  6      because the data are not adequate to support a toxicodynamic model, there generally would be no
  7      biological basis to choose among alternative curve-fitting models. In addition, goodness-of-fit to
  8      the experimental observations is not by itself an effective means of discriminating among models
  9      that adequately fit the data (OSTP,  1985).  To provide some measure of consistency across
10      different carcinogen assessments, EPA uses a standard curve-fitting procedure for tumor
11      incidence data. Assessments that include a different approach should provide an adequate
12      justification and compare their results with those  from the standard procedure. Application of
13      models to data should be conducted in an open and transparent manner.
14
15      1.3.2.  Mode of Action
16             The use of mode of action2 in the assessment of potential carcinogens is the main thrust
17      of these guidelines. This area of emphasis arose because of the significant scientific
18      breakthroughs that have developed  concerning the causes of cancer induction. In the absence of
19      mode of action information, EPA generally takes conservative (public health-protective) default
20      positions regarding the interpretation of toxicologic and epidemiologic data: animal tumor
21      findings are judged to be relevant to humans, and cancer risks are assumed to conform with low
22      dose linearity. Elucidation of a mode of action for a particular  cancer response in animals or
23      humans is a data-rich determination. Significant  information should be developed to ensure that
24      a mode of action underlies the process leading to  cancer at a given site.
25             Understanding of mode of action can be a key to identifying processes that may cause
26      chemical exposures to differentially affect a particular population segment or lifestage.  Some
27      modes of action are anticipated to be mutagenic and are assessed with a linear approach for most,
28      if not all, parts of the population. This is the mode of action of radiation and several other agents
                The term "mode of action" is defined as a sequence of key events and processes, starting with interaction
        of an agent with a cell, proceeding through operational and anatomical changes, and resulting in cancer formation.
        A "key event" is an empirically observable precursor step that is itself a necessary element of the mode of action or
        is a marker for such an element. Mode of action is contrasted with "mechanism of action," which implies a more
        detailed understanding and description of events, often at the molecular level, than is meant by mode of action.  The
        toxicokinetic processes that lead to formation or distribution of the active agent to the target tissue are considered in
        estimating dose but are not part of the mode of action as the term is used here. There are many examples of possible
        modes of carcinogenic action, such as mutagenicity, mitogenesis, inhibition of cell death, cytotoxicity with
        reparative cell proliferation, and immune suppression.

        February 27, 2003                           1 -7             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      that are known carcinogens. Several mutagenic carcinogens are also in utero carcinogens. Other
  2      modes of action may be assessed with either linear or nonlinear3 approaches after a rigorous
  3      analysis of available data under the guidance provided in the framework for mode of action
  4      analysis (see Section 2.5.3).
  5
  6      1.3.3.  Weight of Evidence Narrative
  7             The guidelines emphasize the importance of weighing all of the evidence in reaching
  8      conclusions about the human carcinogenic potential of agents. This is accomplished in a single
  9      step after assessing all of the individual lines of evidence, which is in contrast to the  step-wise
10      approach in the 1986 guidelines. Evidence considered includes tumor findings in humans and
11      laboratory  animals, an agent's chemical and physical properties, its SARs with other
12      carcinogenic agents, and its activities in studies of carcinogenic processes. Data from human
13      studies are generally preferred for characterizing human cancer hazard. However, all of the
14      information discussed above could provide valuable insights into the possible mode(s) of action
15      and likelihood of human cancer hazard and risk. The guidelines recognize the growing
16      sophistication of research methods, particularly in their ability to reveal the modes of action of
17      carcinogenic agents at cellular and subcellular levels as well as toxicokinetic processes.
18             Weighing of the evidence includes addressing not only the likelihood of human
19      carcinogenic effects of the agent but also the conditions under which such effects may  be
20      expressed,  to the extent that these are revealed in the toxicological and other biologically
21      important features of the agent.
22             The weight of evidence narrative to characterize hazard summarizes the results of the
23      hazard assessment and provides a conclusion with regard to human carcinogenic potential. The
24      narrative explains the kinds of evidence available and how they fit together in drawing
25      conclusions, and it points out significant issues/strengths/limitations of the data and conclusions.
26      Because the narrative also summarizes the mode of action information, it sets the stage for the
27      discussion  of the rationale underlying a recommended approach to dose-response assessment.
                The term "nonlinear" is used here in a narrower sense than its usual meaning in the field of mathematical
        modeling. In these guidelines, the term "nonlinear" refers to threshold models (which show no response over a
        range of low doses that include zero) and some nonthreshold models (e.g., a quadractic model, which shows some
        response at all doses above zero). In these guidelines, a nonlinear model is one whose slope is zero at (and perhaps
        above) a dose of zero. A low-dose-linear model is one whose slope is greater than zero at a dose of zero. A low-
        dose-linear model approximates a straight line only at very low doses; at higher doses near the observed data, a low-
        dose-linear model can display curvature. The term "low-dose-linear" is often abbreviated "linear," although a low-
        dose-linear model is not linear at all doses. Use of nonlinear approaches does not imply a biological threshold dose
        below which the response is zero. Estimating thresholds can be problematic; for example, a response that is not
        statistically significant can be consistent with  a small risk that falls below an experiment's power of detection.

        February 27, 2003                            1 -8             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             In order to provide some measure of clarity and consistency in an otherwise free-form,
  2      narrative characterization, standard descriptors are used as part of the hazard narrative to express
  3      the conclusion regarding the weight of evidence for carcinogenic hazard potential. There are
  4      five recommended standard hazard descriptors: "carcinogenic to humans," "likely to be
  5      carcinogenic to humans" "suggestive evidence of carcinogenic potential" "inadequate
  6      information to assess carcinogenic potential'," and "not likely to be carcinogenic to humans."
  1      Each standard descriptor may be applicable to a wide variety of data sets and weights of
  8      evidence and is presented only in the context of a weight of evidence narrative.  Furthermore,
  9      more than one conclusion may be reached for an agent. For instance, using a descriptor in
10      context, a narrative could say that an agent is likely to be carcinogenic by inhalation exposure
11      and not likely to be carcinogenic by oral exposure.
12
13      1.3.4. Dose-response Assessment
14             Dose-response assessment evaluates potential risks to humans at particular exposure
15      levels.  The approach to dose-response assessment for a particular agent is based on the
16      conclusion reached as to its potential mode(s) of action for each tumor type.  Because an agent
17      may induce multiple tumor types, the dose-response assessment includes an analysis of all tumor
18      types, followed by an overall synthesis that includes the consistency of risk estimates across
19      tumor types, the strength of the mode of action information of each tumor type, and the
20      anticipated relevance of each tumor type to humans, including susceptible populations and
21      lifestages (e.g., childhood).
22             Dose-response assessment for each tumor type is performed in two steps: assessment of
23      observed data to derive a point of departure (POD),4 followed by extrapolation to lower
24      exposures to the extent that is necessary. Data from human studies, of sufficient quality, are
25      generally preferred for estimating risks. When animal studies are the basis of the analysis, the
26      estimation of a human-equivalent dose should utilize toxicokinetic data to inform cross-species
27      dose scaling if appropriate and if adequate data are available.  Otherwise, default procedures
28      should be applied.  For oral dose, based on current science, an appropriate default option is to
29      scale daily applied doses experienced for a lifetime in proportion to body weight raised to the 3/4
30      power. For inhalation dose, based on current science, an appropriate default methodology
31      estimates respiratory deposition of particles and gases and estimates internal doses of gases with
              4 A "point of departure" (POD) marks 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.

        February 27, 2003                          1 -9            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      different absorption characteristics.  When toxicokinetic modeling (see Section 3.1.2) is used
  2      without toxicodynamic modeling (see Section 3.2.2), the dose-response assessment develops and
  3      supports an approach for addressing toxicodynamic equivalence, perhaps by retaining some of
  4      the cross-species scaling factor (see Section 3.1.3).  Guidance is also provided for adjustment of
  5      dose from adults to children (see Section 4.3.1).
  6             Response data on effects of the agent on carcinogenic processes are analyzed (nontumor
  7      data) in addition to data on tumor incidence.  If appropriate, the analyses of data on tumor
  8      incidence and on precursor effects may be combined, using precursor data to extend the dose-
  9      response curve below the tumor data. Even if combining data is not appropriate, study of the
10      dose response for effects believed to be part of the carcinogenic process influenced by the agent
11      may assist in evaluating the relationship of exposure and response in the range of observation
12      and at exposure levels below the range of observation.
13             The first step of dose-response assessment is evaluation within the range of observation.
14      Approaches to analysis of the range of observation of human studies are determined by the type
15      of study and how dose and  response are measured in the study. In the absence of adequate
16      human data for dose-response analysis, animal data are generally used.  If there are sufficient
17      quantitative data and adequate understanding of the carcinogenic process, a biologically based
18      model may be developed to relate dose and response data on an agent-specific basis.  Otherwise,
19      as a default procedure, a standard model can be used to curve-fit the data.
20             The POD for extrapolating the relationship to environmental exposure levels of interest
21      when the latter are outside the range of observed data is the lower 95% confidence limit on the
22      lowest level that can be supported by the data.  Other PODs may be more appropriate for certain
23      data sets and, as described in the guidance, may be used instead.  A lower limit rather than a
24      central estimate is appropriate for several reasons. One considers the relative consequences of
25      overestimating or underestimating risk and the Agency's choice to use methods that are not
26      likely to underestimate risk. Another is that use of a bound, as opposed to a central estimate,
27      accounts for the variability (i.e., the sampling error) in the experimental data. In addition, use of
28      the lower bound is consistent with the goal of harmonization with the current practice for
29      assessing effects other than cancer—also based on the lower limit on dose.
30             The second step of dose-response assessment is extrapolation to lower dose levels, if
31      needed. This extrapolation is based on extension of a biologically based model if supported by
32      substantial data (see Section 3.3.2).  Otherwise, default approaches can be applied that are
33      consistent with current understanding of mode(s) of action of the agent, including approaches
34      that assume linearity or nonlinearity of the dose-response relationship, or both.  A default

        February 27,2003                          1-10            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      approach for linearity can be to extend a straight line to zero dose/zero response (see Section
  2      3.3.4). The linear approach is used when there is an absence of sufficient information on modes
  3      of action or the mode of action information indicates that the dose-response curve at low dose is
  4      or is expected to be linear. A default approach for nonlinearity can be to use a reference dose or
  5      a reference concentration (see Section 3.3.3).
  6
  7      1.3.5. Susceptible Populations and Lifestages
  8             An important use of mode of action information is to identify susceptible populations and
  9      lifestages. It is rare to have epidemiologic studies or animal bioassays conducted in susceptible
10      individuals. This information need can be filled by  identifying the key events of the mode of
11      action and then identifying risk factors, such as differences due to genetic polymorphisms,
12      disease, altered organ function, lifestyle, and lifestage, that can augment these key events. To do
13      this, the information about the key precursor events is reviewed to identify particular populations
14      or lifestages that can be particularly susceptible to their occurrence (see Section 2.5.3.4). Any
15      information suggesting quantitative differences between populations or lifestages is flagged for
16      consideration in the dose-response assessment (see Section 3.5).
17
18      1.3.6. Evaluating Risks from Childhood Exposures
19             NRC (1994) recommended that "EPA should assess risks to infants and children
20      whenever it appears that their risks might be greater than those of adults."  Executive Order
21      13045 (1997) requires that "each Federal Agency shall make it a high priority to identify and
22      assess environmental health and safety risks that may disproportionately affect children, and
23      shall ensure that their policies, programs, and standards address disproportionate risks that result
24      from environmental health risks or  safety risks." In assessing risks to children, EPA considers
25      both effects manifest during childhood and early-life exposures that can contribute to effects at
26      any time later in life.
27             These guidelines view childhood as a sequence of lifestages rather than viewing children
28      as a subpopulation, the distinction being that a subpopulation refers to a portion of the
29      population, whereas a lifestage is inclusive of the entire population. Exposures that are of
30      concern extend from  conception through adolescence and also include pre-conception exposures
31      of both parents. These guidelines use the term "childhood" in this more inclusive sense.
32             There are usually no studies that directly evaluate risks following early-life  exposure.
33      Epidemiologic studies of early-life exposure to environmental agents are seldom available.
34      Standard animal bioassays generally begin dosing after the animals are several weeks old, when

        February 27, 2003                           1-11            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      many systems are mature. This could lead to an understatement of risk, because an accepted
  2      concept in the science of carcinogenesis is that young animals are usually more susceptible to the
  3      carcinogenic activity of a chemical than are mature animals (McConnell, 1992).
  4             At this time, there is some evidence of higher cancer risks following early-life exposure.
  5      For radiation carcinogenesis, it is clear that risks for several forms of cancer are highest
  6      following childhood exposure  (NRC, 1990; Miller, 1995; U.S. EPA, 1999c). These human
  7      results are supported by the few animal bioassays that include perinatal (prenatal or early
  8      postnatal) exposure. Perinatal exposure to some agents can induce higher incidences of the
  9      tumors seen in standard bioassays; some examples include vinyl chloride (Maltoni et al., 1981),
10      diethylnitrosamine (Peto  et al., 1984), benzidine, DDT, dieldrin, and safrole (Vesselinovitch
11      et al., 1979). Moreover, perinatal exposure to some agents, including vinyl chloride (Maltoni
12      et al., 1981) and saccharin (Cohen, 1995; Whysner and Williams, 1996), can induce different
13      tumors that are not seen in standard bioassays. Surveys comparing perinatal carcinogenesis
14      bioassays with standard bioassays for a limited number of chemicals (McConnell, 1992; U.S.
15      EPA, 1996b) have concluded that
16
17             'the same tumor sites are usually observed following either perinatal or adult
18                exposure, and
19
20             •   perinatal exposure in conjunction with adult exposure usually increases the incidence
21                of tumors or reduces the latent period before tumors are observed.
22
23             The risk attributable to early-life exposure often appears modest compared with the risk
24      from lifetime exposure, but it can be about 10-fold higher than the risk from an exposure of
25      similar duration occurring later in life (Ginsberg, 2003). Further research is warranted to
26      investigate the extent to which these findings apply to specific agents, chemical classes, and
27      modes of action or in general.
28             These empirical results are consistent with current understanding of the biological
29      processes involved in carcinogenesis, which leads to a reasonable expectation that children can
30      be more susceptible to many carcinogenic agents.  Some aspects potentially leading to childhood
31      susceptibility are:
32
33             •    Differences  in the capacity to metabolize and clear chemicals can result in larger or
34                 smaller internal doses of the active agent(s).

        February  27,2003                          1-12           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1
  2             •     More frequent cell division during development can result in enhanced expression
  3                  of mutations due to the reduced time available for repair of DNA lesions.
  4
  5             •     Some embryonic cells, such as brain cells, lack key DNA repair enzymes.
  6
  7             •     More frequent cell division during development can result in clonal expansion of
  8                  cells with mutations from prior unrepaired DNA damage.
  9
10             •     Some components of the immune system are not fully functional during
11                  development.
12
13             •     Hormonal systems operate at different levels during different lifestages.
14
15             •     Induction of developmental abnormalities can result in a predisposition to
16                  carcinogenic effects later in life.
17
18             To evaluate risks from early-life exposure, these guidelines emphasize the role of
19      toxicokinetic information to estimate levels of the active agent in children and toxicodynamic
20      information to identify whether any key events of the mode of action are of increased concern
21      early in life.  Developmental toxicity studies can provide information on critical periods of
22      exposure for particular targets of toxicity.
23             An approach to assessing risks from early-life exposure is presented in Figure 1-1. In the
24      hazard assessment, when there are mode of action data, the assessment considers whether these
25      data have special relevance during childhood, considering the various aspects of development
26      listed above. Examples of such data include toxicokinetics that predict a sufficiently large
27      internal dose in children or a mode of action where a key precursor event is more likely to occur
28      during childhood. There is no recommended default to settle the question of whether tumors
29      arising through the hypothesized mode of action are relevant during childhood; understanding
30      the mode of action implies that there are sufficient data (on either the specific agent or the
31      general mode of action) to form a confident conclusion about relevance during childhood (see
32      Section 2.5.3.4).
33             In the dose-response assessment, the potential for susceptibility during childhood
34      warrants explicit consideration in each assessment.  These guidelines encourage developing

        February 27,2003                          1-13             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1      separate risk estimates for children according to a tiered approach that considers what pertinent
  2      data are available (see Section 3.5). Although childhood may be a susceptible period, exposures
  3      during childhood generally are not equivalent to exposures at other times and may be treated
  4      differently from exposures occurring later in life (see Section 3.5). In addition, adjustment of
  5      unit risk estimates can be warranted when used to estimate risks from childhood exposure (see
  6      Section 4.4).
  7            At this time, several limitations preclude a full assessment of children's risk. There are
  8      no generally used testing protocols to identify potential environmental causes of cancers that are
  9      unique to children, including several forms of childhood cancer and cancers that develop from
10      parental exposures, and cases where developmental exposure may alter susceptibility to
11      carcinogen exposure in the adult (Birnbaum and Fenton, 2003). Dose-response assessment is
12      limited by an inability to observe how developmental exposure can modify incidence and latency
13      and an inability to estimate the ultimate tumor response resulting from induced susceptibility to
14      later carcinogen exposures.
15
16      1.3.7. Emphasis on Characterization
17            The guidelines provide greater emphasis on characterization discussions for hazard, dose
18      response, and exposure assessment. These characterizations summarize the assessments to
19      explain the extent and weight of evidence, major points of interpretation and rationale for their
20      selection, and strengths and weaknesses of the evidence and the analysis and discuss alternative
21      conclusions and uncertainties that deserve serious consideration (U.S. EPA, 2000b). They serve
22      as starting materials for the overall risk characterization process that completes the risk
23      assessment.
        February 27,2003                          1-14            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
                Figure 1-1.  Risk assessment of childhood exposures
         Can MOA be
         Determined?
           62.5.3.4
       Can TK or MOA
       differences make
         children more
         susceptible?
      (higher internal dose
       or occurrence of
      key event in MOA)
           §2.5.3.4
               N
                                    Tumor data
                                    on children
                                 or young animals?
                                       63.5
        Note differences in
       lose-response between
        children and adults.
         Choose linear or
        nonlinear approach
      Conclude whether
      MOA is relevant
         to humans
          62.5.3.4
                      Relevant
  Data to quantify
differences between
adults and children?
       63.5
Not
relevant
February 27, 2003
                         1-15
                                           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1                                   2.  HAZARD ASSESSMENT
 2
 3      2.1. OVERVIEW OF HAZARD ASSESSMENT AND CHARACTERIZATION
 4      2.1.1.  Analyses of Data
 5            The purpose of hazard assessment is to review and evaluate data pertinent to two
 6      questions:  (1) whether an agent may pose a carcinogenic hazard to human beings, and (2) under
 7      what circumstances an identified hazard may be expressed (NRC, 1994). Hazard assessment is
 8      composed of analyses of a variety of data that may range from observations of tumor responses
 9      to analysis of SARs. The purpose of the assessment is not simply to assemble these separate
10      evaluations; its purpose is to construct a total case analysis examining the biological story the
11      data reveal as a whole about carcinogenic effects and mode of action and their implications for
12      human hazard and dose-response evaluation. Weight of evidence conclusions come from the
13      combined strength and coherence of inferences appropriately drawn from all of the available
14      evidence. To the extent that data permit, hazard assessment addresses the question of mode of
15      action as both  an initial step in identifying human hazard potential and a component in
16      considering appropriate approaches  to dose-response assessment.
17            The topics in this chapter include analysis of tumor data, both animal and human, and
18      analysis of other key information about properties and effects that relate to carcinogenic
19      potential. The chapter addresses how information can be used to evaluate potential modes of
20      action. It also provides guidance on performing a weight of evidence evaluation.
21
22      2.1.2.  Presentation of Results
23            Presentation of the results of hazard assessment should be informed by Agency guidance
24      as discussed in Section 2.7.  The results are presented in a technical hazard characterization that
25      serves as a support to later risk characterization. It includes
26
27            •     a summary of the evaluations of hazard data,
28            •     the rationales for its conclusions, and
29            •     an explanation of the significant strengths or limitations of the conclusions.
30
31            Another presentation feature is the use of a weight of evidence narrative that includes
32      both a conclusion about the  weight of evidence of carcinogenic potential and a summary of the
33      data on which the conclusion rests.  This narrative is a brief summary that replaces the
34      alphanumerical classification system used in EPA's 1986 guidelines (U.S. EPA, 1986a).

        February 27, 2003                         2-1            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      2.2. ANALYSIS OF TUMOR DATA
  2            Evidence of carcinogenicity comes from finding tumor increases in humans or laboratory
  3      animals exposed to a given agent or from finding tumors .following exposure to structural
  4      analogues to the compound under review.  The significance of observed or anticipated tumor
  5      effects is evaluated in reference to all the other key data on the agent. This section contains
  6      guidance for analyzing human and animal studies to decide whether there is an association
  7      between exposure to an agent or a structural analogue and occurrence of tumors. Note that the
  8      use of the term "tumor" here is generic, meaning malignant neoplasms or a combination of
  9      malignant and corresponding benign neoplasms.
10            Observation of only benign neoplasia may or may not have significance. Benign tumors
11      that are not observed to progress to malignancy are assessed on a case-by-case basis. There is a
12      range of possibilities for their overall significance. They may deserve attention because they are
13      serious health problems even though they are not malignant; for instance, benign tumors may be
14      a health risk because of their effect on the function of a target tissue such as the brain. They may
15      be significant indicators of the need for further testing of an agent if they are observed in a short-
16      term test protocol,  or such an observation may add to the overall weight of evidence if the same
17      agent causes malignancies in a long-term study. Knowledge of the mode of action associated
18      with a benign tumor response may aid in the interpretation of other tumor responses associated
19      with the same agent.  In other cases, observation of a benign tumor response alone may have no
20      significant health hazard implications when other sources of evidence show no suggestion of
21      carcinogenicity.
22
23      2.2.1. Human Data
24            Human data may come from epidemiologic studies or case reports. Clinical human
25      studies, which involve intentional exposures to substances, may provide data on acute health
26      effects, but not on cancer.  The most common sources of human data for cancer risk assessment
27      are epidemiological investigations. Epidemiology is the study of the distribution of disease in
28      human populations and the factors that may influence that distribution.  The goals of cancer
29      epidemiology are to identify  distribution of cancer risk and determine the extent to which the
30      risk can be attributed causally to specific exposures to exogenous or endogenous factors.
31      Epidemiologic data are extremely valuable in risk assessment because they provide direct
32      evidence on whether a substance is likely to produce cancer in humans, thereby avoiding the
33      problem of species-to-species inference. Thus, when available human data of high quality and
34      adequate statistical power are available, they are generally preferable over animal data and

        February 27, 2003                          2-2            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      should be given greater weight in hazard characterization and dose-response assessment,
  2      although both are utilized.
  3            Null results from epidemiologic studies generally do not prove the absence of
  4      carcinogenic effects because such results can arise either from being truly negative or from
  5      inadequate statistical power, inadequate design, imprecise estimates, or confounding factors.
  6      However, null results from a well-designed and well-conducted epidemiologic study that
  7      contains usable exposure data can help to define upper limits for the estimated dose of concern
  8      for human exposure if the overall weight of the evidence indicates that the agent is potentially
  9      carcinogenic in humans.
10            Epidemiology can also complement experimental evidence in corroborating or clarifying
11      the carcinogenic potential of the agent in question. For example, epidemiologic studies that
12      show elevated cancer risk for tumor sites corresponding to those at which laboratory animals
1.3      experience increased tumor incidence can strengthen the weight of evidence of human
14      carcinogenicity. On the other hand, strong nonpositive epidemiologic data in conjunction with
15      compelling mechanistic information can lend support to a conclusion that animal responses may
16      not be predictive of a  human cancer hazard. Furthermore, biochemical or molecular
17      epidemiology may help improve understanding of the mechanisms of human carcinogenesis.
18
19      2.2.1.1.  Types of Studies
20            The major types of cancer epidemiologic designs used for examining environmental
21      causes of cancer are analytical studies  and descriptive studies.  Each study type has well-known
22      strengths and weaknesses that affect interpretation of results, as summarized below (Kelsey et
23      al., 1986; Lilienfeld and Lilienfeld, 1979; Mausner and Kramer, 1985; Rothman, 1986).
24            Analytical epidemiologic studies, which include case-control and cohort designs, are
25      generally relied  on for identifying a causal association between human exposure and adverse
26      health effects. In case-control studies, groups of individuals with (cases) and without (controls)
27      a particular disease are identified and compared to determine differences in exposure. In cohort
28      studies, a group  of "exposed" and "nonexposed" individuals are identified and studied over time
29      to determine differences in  disease occurrence. Cohort studies can be performed either
30      prospectively or retrospectively from historical records.
31            Descriptive epidemiologic studies examine symptom or disease rates among populations
32      in relation to personal characteristics such as age, gender, race, and temporal or environmental
33      conditions.  Descriptive studies are most frequently used to generate hypotheses about exposure
34      factors, but subsequent analytical designs are necessary to infer causality. For example, cross-

        February 27,2003                          2-3             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      sectional designs might be used to compare the prevalence of cancer between areas near and far
  2      from a Superfund site. However, in studies where exposure and disease information applies only
  3      to the current conditions, it is not possible to infer that the exposure actually caused the disease.
  4      Therefore, these studies are used to identify patterns or trends in disease occurrence over time or
  5      in different geographical locations, but typical limitations in the characterization of populations
  6      in these studies make it difficult to infer the causal agent or degree of exposure.
  7             Biochemical or molecular epidemiologic studies use biological markers of effect as
  8      indicators of disease or its precursors. The application of techniques for measuring cellular and
  9      molecular alterations due to exposure to specific environmental agents may allow conclusions to
10      be drawn about the mechanisms of carcinogenesis. Refer to the sections on biomarkers (Section
11      2.4) and mode of action (Section 2.5) for more information  on this topic.
12             Case reports describe a particular effect in an individual or group of individuals who
13      were exposed to a substance. These reports are often anecdotal or highly selective in nature and
14      generally are of limited use for hazard assessment. Investigative follow-up may or may not
15      accompany such reports. For cancer, the most common types of case series are associated with
16      occupational and childhood exposures. Case reports can be particularly valuable for identifying
17      unique features such as an association with an uncommon tumor (e.g., vinyl chloride and
18      angiosarcoma or diethylstilbestrol and clear-cell carcinoma of the vagina).
19
20      2.2.1.2. Assessing the Quality of Epidemiologic Studies
21             Characteristics that are generally desirable in epidemiologic studies include (1) clear
22      articulation of study objectives or hypothesis; (2) proper selection and characterization of
23      comparison groups (exposed and unexposed groups or case and control groups); (3) adequate
24      characterization of exposure; (4) sufficient length of follow-up for disease occurrence; (5)  valid
25      ascertainment of the causes of cancer morbidity and mortality;  (6) proper consideration of bias
26      and confounding factors; (7)  adequate sample size to detect an  effect; (8) clear, well-
27      documented, and appropriate methodology for data collection and analysis; (9) adequate
28      response rate and methodology for handling missing data; and (10) complete and clear
29      documentation of results. No single criterion determines the overall adequacy of a study.
30      Practical and financial constraints may limit the ability to address all of these characteristics in a
31      study.  The risk assessor is encouraged to consider how the  limitations of the available studies
32      might influence the conclusions. The following discussions highlight the major factors included
33      in an analysis of epidemiologic studies.
34

        February 27,2003                           2-4             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      2.2.1.2.1.  Population issues. When comparing cases and controls or exposed and non-exposed
  2      populations, it would be preferable for the two populations to differ only in exposure to the agent
  3      in question.  Because this is seldom the case, it is important to identify sources of bias inherent in
  4      a study's design or data collection methods. Bias is a systematic error.  In epidemiological
  5      studies, bias can occur in the selection of cases and controls or exposed and non-exposed
  6      populations, as well as the follow up of the groups, or the classification of disease or exposure.
  7      The size of the risks observed can be affected by noncomparability between populations of
  8      factors such  as general health (McMichael, 1976), diet, lifestyle, or geographic location;
  9      differences in the way case and control individuals recall past events; differences in data
10      collection  that result in unequal ascertainment of health effects in the populations; and unequal
11      follow-up  of individuals. Both acceptance of studies for assessment and judgment of their
12      strengths or weaknesses depend on identifying their sources of bias and the effects on study
13      results.
14
15      2.2.1.2.2.  Exposure issues.  For epidemiologic data to be useful in determining whether there is
16      an association between health effects and exposure to an agent, there should be adequate
17      characterization of exposure  information. In general, greater weight should be given to studies
18      with more precise and specific exposure estimates.
19             Questions to address about exposure are: What can one reliably conclude about the level,
20      duration, route, and frequency of exposure of individuals in one population as compared with
21      another? How sensitive are study results to uncertainties in these parameters?
22             Actual exposure measurements are not available for many retrospective studies.
23      Therefore, surrogates are often used to reconstruct exposure parameters. These may involve
24      attributing exposures to job classifications in a workplace or to broader occupational or
25      geographic groupings. Use of surrogates carries a potential for misclassification in that
26      individuals may be placed in an incorrect exposure group. Misclassification generally leads to
27      reduced ability of a study to detect differences between study and referent populations.
28             When either current or historical monitoring data are available, the exposure evaluation
29      includes consideration of the error bounds of the monitoring and analytic methods and whether
30      the data are from routine or accidental exposures. The potentials for misclassification and
31      measurement errors are amenable to both qualitative and quantitative analysis. These are
32      essential analyses for judging a study's results, because exposure estimation is the most critical
33      part of a retrospective  study.
        February 27, 2003                           2-5            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             Biological markers potentially offer excellent measures of exposure (Hulka and
  2      Margolin, 1992; Peto and Darby, 1994). Validated markers of exposure such as alkylated
  3      hemoglobin from exposure to ethylene oxide (Van Sittert et al., 1985) or urinary arsenic
  4      (Enterline et al., 1987) can greatly improve estimates of dose. Markers closely identified with
  5      effects promise to greatly increase the ability of studies to distinguish real effects from bias at
  6      low levels of relative risk between populations (Taylor et al., 1994; Biggs et al., 1993) and to
  7      resolve problems of confounding risk factors.
  8
  9      2.2.1.2.3.  Confounding factors.  In observational epidemiologic studies, it is very difficult to
10      guarantee the control of confounding variables. A confounder is a variable that is related to both
11      the health outcome of concern (cancer) and exposure.  Common examples include age,
12      socioeconomic status, smoking habits, and diet. For instance, if older people are more likely to
13      be exposed to a given contaminant as well as more likely to have cancer because of their age,
14      age is considered a confounder. Adjustment for potentially confounding factors can occur either
15      in the design of the study (e.g., individual or group matching on critical factors) or in the
16      statistical analysis of the results (stratification or direct or indirect adjustment). Direct
17      adjustment in the statistical analysis may not be possible owing to the presentation of the data or
18      because needed information was not collected during the  study. In this case, indirect
19      comparisons may be possible. For example, in the absence of data on smoking status among
20      individuals in the study population, an examination of the possible contribution of cigarette
21      smoking to increased lung cancer risk may be based on information from other sources, such as
22      the American Cancer Society's longitudinal studies (Hammand, 1966;  Garfinkel and Silverberg,
23      1991). The effectiveness of adjustments contributes to the ability to draw inferences from a
24      study.
25             Different studies involving exposure to an agent may have different confounding factors.
26      If consistent increases in cancer risk are observed across a collection of studies with different
27      confounding factors, the inference that the agent under investigation was the etiologic factor is
28      strengthened. It also  may be the case that the agent of interest is a risk factor in conjunction with
29      another agent.  This relationship may be revealed in a collection of studies, such as in the case of
30      asbestos exposure and smoking.
31
32      2.2.1.2.4. Likelihood of observing an effect. The power of a study-the likelihood of observing
33      an effect if one exists - increases with sample size. If the size of the effect is expected to be very
34      small at low doses, higher doses or longer durations of exposure may be needed to have an

        February 27, 2003                           2-6            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      appreciable likelihood of observing an effect with a given sample size. Because of the often long
  2      latency period in cancer development, the likelihood of observing an effect also depends on
  3      whether adequate time has elapsed since exposure began for effects to occur.  A unique feature
  4      that can be ascribed to the effects of a particular agent (such as a tumor type that is seen only
  5      rarely in the absence of the agent) can increase sensitivity by permitting separation of bias and
  6      confounding factors from real effects. Similarly, a biomarker particular to the agent can permit
  7      these distinctions.  Statistical re-analyses of data, particularly an examination of different
  8      exposure indices, can give insight into potential exposure-response relationships.  These are all
  9      factors to explore in statistical analysis of the data.
10
11      2.2.1.2.5.  Statistical considerations.  The analysis should apply appropriate statistical methods
12      to ascertain whether the observed association between exposure and effects would be expected
13      by chance. A description of the method or methods used should include the reasons for their
14      selection.  Statistical analyses of the bias, confounding, and interaction are part of addressing the
15      significance of an association and the power of a study to detect an effect.
16            The analysis augments examination of the results for the whole population with
17      exploration of the results for groups with comparatively greater exposure or time since first
18      exposure.  This may support identifying an association or establishing a dose-response trend.
19      When studies show no association, such exploration may apply to determining an upper limit on
20      potential human risk for consideration alongside results of animal tumor effects studies.
21
22      2.2.1.2.6.  Combining statistical evidence across studies. Meta-analysis is a means of
23      integrating the results of multiple studies of similar health effects and risk factors. This
24      technique  is particularly useful when  various studies yield varying degrees of risk or even
25      conflicting associations (negative and positive). It is intended to introduce consistency and
26      comprehensiveness into what otherwise might be a more subjective review of the  literature. The
27      value of such an analysis is dependent upon a systematic review of the literature that uses
28      transparent criteria of inclusion and exclusion.  In interpreting such  analyses, it is  important to
29      consider the effects of differences in study quality, as well as the effect of publication bias.
30      Meta-analysis may not be useful in some circumstances. These include when the relationship
31      between exposure and disease is obvious from the individual studies; when there are only a few
32      studies of the key health outcomes; when there is insufficient information from available studies
33      related to disease, risk estimate, or exposure classification to insure  comparability; or when there
        February 27, 2003                           2-7             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      are substantial confounding or other biases that cannot be adjusted for in the analysis (Blair et
  2      al., 1995; Greenland, 1987; Peto, 1992).
  3
  4      2.2.1.3. Evidence for Causality
  5             Determining whether an observed association (risk) is causal rather than spurious
  6      involves consideration of a number of factors. Sir Bradford Hill developed a set of guidelines
  7      for evaluating epidemiologic associations in conjunction with the 1964 Surgeon General's
  8      Report on Smoking (Hill, 1965; Rothman, 1986; IPCS, 1999). Although these guidelines have
  9      become known as "causal criteria," it is important to note that they cannot be used as a strictly
10      quantitative checklist. Rather, these "criteria" should be used to determine the strength of the
11      evidence for concluding causality. The list below has been adapted from Hill's guidelines as an
12      aid in judging causality.
13             (a) Consistency of the observed association. An inference of causality is strengthened
14      when a pattern of elevated risks is observed across several independent studies. The
15      reproducibility of findings constitutes one of the strongest arguments for causality. If there are
16      discordant results among investigations, possible reasons such as differences in exposure,
17      confounding factors, and the power of the study are considered.
18             (b) Strength of the observed association.  The finding of large, precise risks increases
19      confidence that the association is not likely due to chance, bias, or other factors. A modest risk,
20      however, does not preclude a causal association and may reflect a lower level of exposure, an
21      agent of lower potency, or a common disease with a high background level.
22             (c) Specificity of the observed association. As originally intended, this refers to
23      increased inference of causality if one cause is associated with a single effect or disease
24      (Hill, 1965).  Based on our current understanding that many agents cause cancer at multiple sites,
25      and many cancers have multiple causes, this is now considered one of the weaker guidelines for
26      causality.  Thus, although the presence of specificity may support causality, its absence does not
27      exclude it.
28             (d) Temporal relationship of the observed association. A causal interpretation is
29      strengthened when exposure is known to precede development of the disease.  Because a latent
30      period of up to 20 years or longer is associated with cancer development, the study should
31      consider whether exposures occurred sufficiently long ago to produce an effect at the time the
32      cancer is assessed.  This is among the strongest criteria for an inference of causality.
33             (e) Biological gradient (exposure-response relationship).  A clear exposure-response
34      relationship (e.g., increasing effects associated with greater exposure) strongly suggests cause

        February 27, 2003                           2-8            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      and effect, especially when such relationships are also observed for duration of exposure (e.g.,
  2      increasing effects observed following longer exposure times).  Because there are many possible
  3      reasons that an epidemiologic study may fail to detect an exposure-response relationship (for
  4      example, a small range of observed exposure levels or exposure misclassification), the absence
  5      of an exposure-response relationship does not exclude a causal relationship.
  6            (f) Biological plausibility.  An inference of causality tends to be strengthened by
  7      consistency with data from experimental studies or other sources demonstrating plausible
  8      biological mechanisms. A lack of mechanistic data, however,  is not a reason to reject causality.
  9            (g) Coherence. An inference of causality may be strengthened by other lines of evidence
10      that support a cause-and-effect interpretation of the association. Information is considered from
11      animal bioassays, toxicokinetic studies, and short-term studies. The absence of other lines of
12      evidence, however, is not a reason to reject causality.
13            (h) Experimental evidence (from human populations). Experimental evidence is
14      seldom available from human populations and exists only when conditions of human exposure
15      are altered to create a "natural experiment" at different levels of exposure. Strong evidence for
16      causality can be provided when a change in exposure  brings about a change in disease frequency,
17      for example, the decrease in the risk of lung cancer that follows cessation of smoking.
18            (i) Analogy.  S ARs and information on the agent's structural analogues can provide
19      insight into whether an association is causal.
20
21      2.2.1.4. Assessment of Evidence of Carcinogenicity from Human Data
22            All studies that are considered to be of acceptable quality, whether yielding positive or
23      null results, or even suggesting protective carcinogenic effects, should be considered in assessing
24      the totality of the human evidence. Conclusions about the overall evidence for carcinogenicity
25      from available studies in humans should be summarized along with a discussion of uncertainties
26      and gaps in knowledge. Conclusions regarding the strength of the evidence for positive or
27      negative associations observed, as well as evidence supporting judgments of causality, should be
28      clearly described. In assessing the human data within the overall weight of evidence,
29      determination about the strength of the epidemiologic evidence should clearly identify the degree
30      to which the observed associations may be explained by other  factors, including bias or
31      confounding.
32
33      2.2.2.  Animal Data
        February 27, 2003                          2-9             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             Various whole-animal test systems are currently used or are under development for
  2      evaluating potential carcinogenicity. Cancer studies involving chronic exposure for most of the
  3      lifespan of an animal are generally accepted for evaluation of tumor effects (Tomatis et al., 1989;
  4      Rail, 1991; Allen et al., 1988; but see Ames and Gold, 1990). Other studies of special design are
  5      useful for observing formation of preneoplastic lesions or tumors or investigating specific modes
  6      of action.  Their applicability is determined on a case-by-case basis.
  7
  8      2.2.2.1. Long-term Carcinogenicity Studies
  9             The objective of long-term  carcinogenesis bioassays is to determine the potential
10      carcinogenic hazard and dose-response relationships of the test agent.  Carcinogenicity rodent
11      studies are designed to examine the production of tumors as well as preneoplastic lesions and
12      other indications of chronic toxicity that may provide evidence of treatment-related effects and
13      insights into the way the test agent produces tumors. Current standardized carcinogenicity
14      studies in rodents test at least 50 animals per sex per dose group in each of three treatment
15      groups and in a concurrent control  group, usually for 18 to 24 months, depending on the rodent
16      species tested (OECD, 1981;  U.S. EPA, 1998c). The high dose in long-term studies is generally
17      selected to provide the maximum ability to detect treatment-related carcinogenic effects while
18      not compromising the outcome of the study through excessive toxicity or inducing inappropriate
19      toxicokinetics (e.g., overwhelming absorption or detoxification mechanisms). The purpose of
20      two or more lower doses is to provide some information on the shape of the dose-response curve.
21      Similar protocols have been and continue to be used by many laboratories worldwide.
22             All available studies of tumor effects in whole animals should be considered, at least
23      preliminarily. The analysis should discard studies judged to be wholly inadequate in protocol,
24      conduct, or results. Criteria for the technical adequacy of animal carcinogenicity studies have
25      been published and should be used as guidance to judge the acceptability of individual studies
26      (NTP, 1984; OSTP, 1985). Care should be taken to include  studies that provide some evidence
27      bearing on carcinogenicity or that help interpret effects noted in other studies, even if these
28      studies have some limitations of protocol or conduct. Such limited, but not wholly inadequate,
29      studies can contribute as their deficiencies permit. The findings of long-term rodent bioassays
30      should be interpreted in conjunction with results of prechronic studies along with toxicokinetic
31      studies and other pertinent information, if available. Evaluation of tumor effects takes into
32      consideration both biological and statistical significance of the findings (Haseman,  1984, 1985,
33      1990,  1995). The following sections highlight the major issues in the evaluation of long-term
34      carcinogenicity studies.

        February 27,2003                          2-10             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      2.2.2.1.1. Dosing issues. Among the many criteria for technical adequacy of animal
  2      carcinogenicity studies is the appropriateness of dose selection.  The selection of doses for
  3      chronic bioassays is based on scientific judgments and sound toxicologic principles. Dose
  4      selection should be made on the basis of relevant toxicologic information from prechronic,
  5      mechanistic, and toxicokinetic and mechanistic studies. How well the dose selection is made is
  6      evaluated after the completion of the bioassay.  A scientific rationale for dose selection should be
  7      clearly articulated (e.g., ILSI, 1997).
  8             Interpretation of carcinogenicity study results is profoundly affected by study exposure
  9      conditions, especially by inappropriate dose selection. This is particularly important in studies
10      that are nonpositive for carcinogenicity, because failure to reach a sufficient dose reduces the
11      sensitivity of the studies. A lack of tumorigenic responses at exposure levels that cause
12      significant impairment of animal survival may also not be acceptable. In addition, overt toxicity
13      or inappropriate toxicokinetics due to excessively high doses may result in  tumor effects that are
14      secondary to the toxicity rather than directly attributable to the agent.
15             With regard to the appropriateness of the high dose, an adequate high dose would
16      generally be one that produces some toxic effects without unduly affecting  mortality from effects
17      other than cancer or producing significant adverse effects on the nutrition and health of the test
18      animals (OECD,  1981; NRC, 1993a). If the test agent does not appear to cause any specific
19      target organ toxicity or perturbation of physiological function, an adequate  high dose can be
20      specified in terms of a percentage reduction of body weight gain over the lifespan of the animals.
21      The high dose would generally be considered inadequate if neither toxicity nor change in weight
22      gain is  observed. On the other hand, significant increases in mortality from effects other than
23      cancer  generally indicate that an adequate high dose has been exceeded.
24             Other signs of treatment-related toxicity associated with an excessive high dose may
25      include (a) significant reduction of body weight gain (e.g., greater than 10%), (b) significant
26      increases in abnormal behavioral and clinical  signs, (c) significant changes in hematology or
27      clinical chemistry, (d) saturation of absorption and detoxification mechanisms, or (e) marked
28      changes in organ weight, morphology, and histopathology. It should be noted that practical
29      upper limits have been established to avoid the use of excessively high doses in long-term
30      carcinogenicity studies of environmental chemicals (e.g.,  5% of the test substance in the feed for
31      dietary studies or 1 g/kg body weight for oral  gavage  studies [OECD, 1981]).
32             For dietary studies, weight gain reductions should be evaluated as to whether there is a
33      palatability problem or an issue with food efficiency; certainly, the latter is a toxic manifestation.
34      In the case of inhalation studies with respirable particles, evidence of impairment of normal

        February 27,2003                          2-11             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      clearance of particles from the lung should be considered along with other signs of toxicity to the
  2      respiratory airways to determine whether the high exposure concentration has been appropriately
  3      selected.  For dermal studies, evidence of skin irritation may indicate that an adequate high dose
  4      has been reached (U.S. EPA, 1989).
  5            In order to obtain the most relevant information from a long-term carcinogenicity study,
  6      it is important to maximize exposure conditions to the test material. At the same time, caution is
  7      appropriate in using excessive high-dose levels that would confound the interpretation of study
  8      results to humans. The middle and lowest doses should be selected to characterize the shape of
  9      the dose-response curve as much as possible.  It is important that the doses be adequately spaced
10      so that the study can provide relevant dose-response data for assessing human hazard and risk. If
11      the testing of potential carcinogenicity is being combined with an evaluation of noncancer
12      chronic toxicity, the study should be designed to include one dose that does  not elicit adverse
13      effects.
14            There are several possible outcomes regarding the study interpretation of the significance
15      and relevance of tumorigenic effects associated with exposure or dose levels below, at, or above
16      an adequate high dose. The general guidance is given here; for each case, the information at
17      hand should be evaluated and a rationale should be given for the position taken.
18
19            •    Adequate high dose. If an adequate high dose has been used, tumor effects are
20                 judged positive or negative depending on the presence or absence of significant
21                 tumor incidence increases, respectively.
22
23            •    Excessive high dose. If toxicity or mortality is excessive at the high dose,
24                 interpretation depends on the finding of rumors or not.
25
26                 -  Studies that show tumor effects only at excessive doses may be compromised
27                     and may or may not carry weight, depending on the interpretation in the context
28                     of other study results and other lines of evidence.  Results of such studies,
29                     however, are generally not considered suitable for dose-response extrapolation
30                     if it is determined  that the mode(s) of action underlying the tumorigenic
31                     responses at high doses is not operative at lower doses.
32
33                 -  Studies that show rumors at lower doses, even though the high dose is excessive
34                     and may be discounted, should be evaluated on their own merits.

        February 27,2003                          2-12            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1                  -  If a study does not show an increase in tumor incidence at a toxic high dose and
  2                     appropriately spaced lower doses are used without such toxicity or tumors, the
  3                     study is generally judged as negative for carcinogenicity.
  4
  5             •     Inadequate high dose.  Studies of inadequate sensitivity where an adequate high
  6                  dose has not been reached may be used to bound the dose range where carcinogenic
  7                  effects might be expected.
  8
  9      2.2.2.1.2. Statistical considerations.  The main aim of statistical evaluation is to determine
10      whether exposure to the test agent is associated with an increase of tumor development.
11      Statistical analysis of a long-term study should be performed for each tumor type separately.
12      The incidence of benign  and malignant lesions of the same cell type, usually within a single
13      tissue or organ, are considered separately and are combined when scientifically defensible
14      (McConnelletal., 1986).
15             Trend tests and pairwise comparison tests are the recommended tests for determining
16      whether chance, rather than a treatment-related effect, is a plausible explanation for an apparent
17      increase in tumor incidence.  A trend test such as the Cochran-Armitage test (Snedecor and
18      Cochran,  1967) asks whether the results in all dose groups together increase as dose increases. A
19      pairwise comparison test such as the Fisher exact test (Fisher, 1950) asks whether an incidence
20      in one dose group is increased over  that of the control group.  By convention, for both tests a
21      statistically significant comparison is one for which/? is less than 0.05 that the increased
22      incidence is due to chance.  Significance in either kind of test is sufficient to reject the
23      hypothesis that chance accounts for the result.
24             A statistically significant response may or may not be biologically significant and vice
25      versa. The  selection of a significance level is a policy choice based on a trade-off between the
26      risks of false positives and false negatives. A result with a significance level of greater or less
27      than 5% (the most common significance level) is examined to see if the result confirms other
28      scientific information. When the assessment departs from a simple 5% level, this should be
29      highlighted in the risk characterization. A two-tailed test or a one-tailed test can be used.  In
30      either case a rationale is provided.
31             Statistical power  can affect the likelihood that a statistically significant result could
32      reasonably be expected.  This is especially important in studies or dose groups with small sample
33      sizes or low dose rates. Reporting the statistical  power can be useful for comparing and
34      reconciling positive and negative results from different studies.

        February  27,2003                          2-13            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1             Considerations of multiple comparisons should also be taken into account. Haseman
 2      (1983) analyzes typical animal bioassays that test both sexes of two species and concludes that,
 3      because of multiple comparisons, a single tumor increase for a species-sex-site combination that
 4      is statistically significant at the 1% level for common tumors or 5% for rare tumors corresponds
 5      to a 7-8% significance level for the study as a whole. Therefore, animal bioassays presenting
 6      only one significant result that falls short of the 1% level for a common tumor should be treated
 7      with caution.
 8
 9      2.2.2.1.3.  Concurrent and historical controls. The standard for determining statistical
10      significance of tumor incidence comes from a comparison of tumors in dosed animals with those
11      in concurrent control animals. Additional insights about both statistical and biological
12      significance can come from an examination of historical control data (Tarone, 1982; Haseman,
13      1995). Historical control data can add to the analysis, particularly by enabling identification of
14      uncommon tumor types or high spontaneous incidence of a tumor in a given animal strain.
15      Identification of common or uncommon situations prompts further thought about the meaning of
16      the response in the current study in context with other observations in animal studies and with
17      other evidence about the carcinogenic potential of the agent. These other sources of information
18      may reinforce or weaken the significance given to the response in the hazard assessment.
19      Caution should be exercised in simply looking at the ranges of historical responses, because the
20      range  ignores differences in survival of animals among studies and is related to the number of
21      studies in the database.
22             In analyzing results for uncommon tumors in a treated group that are not statistically
23      significant in comparison with concurrent controls, the analyst can use the experience of
24      historical controls to conclude that the result is in fact unlikely to be due to chance. In  analyzing
25      results for common tumors, a different set of considerations comes into play. Generally
26      speaking, statistically significant increases in tumors should not be discounted simply because
27      incidence rates in the treated groups are within the range of historical controls or because
28      incidence rates in the concurrent controls are somewhat lower than average.  Random
29      assignment of animals to groups and proper statistical procedures provide assurance that
30      statistically significant results are unlikely to be due to chance alone. However, caution should
31      be used in interpreting results that are barely statistically significant or in which incidence rates
32      in concurrent controls are unusually low in comparison with historical controls.
        February 27,2003                          2-14            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1             In cases where there may be reason to discount the biological relevance to humans of
  2      increases in common animal tumors, such considerations should be weighed on their own merits
  3      and clearly distinguished from statistical concerns.
  4             When historical control data are used, the discussion should address several issues that
  5      affect comparability of historical and concurrent control data, such as genetic drift in the
  6      laboratory strains, differences in pathology examination at different times and in different
  7      laboratories (e.g., in criteria for evaluating lesions; variations in the techniques for the
  8      preparation or reading of tissue samples among laboratories), and comparability of animals from
  9      different suppliers. The most relevant historical data come from the same laboratory and the
10      same supplier and are gathered within  2 or 3 years one way  or the other of the study under
11      review; other data should be used only with extreme caution.
12
13      2.2.2.1.4. Assessment of evidence of carcinogenicity from  long-term animal studies. In
14      general, observation of tumor effects under different circumstances lends support to the
15      significance of the findings for animal carcinogenicity. Significance is a function of the number
16      of factors present and, for a factor such as malignancy, the severity of the observed pathology.
17      The following observations add significance to the tumor findings:
18
19             •     uncommon tumor types;
20             •     tumors at multiple sites;
21             •     tumors by more than one  route of administration;
22             •     tumors in multiple species, strains, or both sexes;
23             •     progression of lesions from preneoplastic to benign to malignant;
24             •     reduced latency of neoplastic lesions;
25             •     metastases;
26             •     unusual magnitude of tumor response;
27             •     proportion of malignant tumors; and
28             •     dose-related increases.
29
30             Tumor findings in animals generally indicate that an agent may produce such effects in
31      humans. Moreover, the absence of tumor findings in well-conducted, long-term animal studies
32      in at least two species provides reasonable assurance that an agent may not be a carcinogenic
33      concern for humans. Each of these assumptions may be adopted, when appropriate, after
34      evaluation of tumor data and other key evidence.

        February 27,2003                         2-15            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1      2.2.2.1.5. Site concordance. Site concordance of tumor effects between animals and humans
  2      should be considered in each case.  Thus far, there is evidence that growth control mechanisms at
  3      the level of the cell are homologous among mammals, but there is no evidence that these
  4      mechanisms are site concordant. Moreover, agents observed to produce tumors in both humans
  5      and animals have produced tumors either at the same site (e.g., vinyl chloride) or different sites
  6      (e.g., benzene) (NRC, 1994). Hence, site concordance is not assumed a priori. On the other
  7      hand, certain processes with consequences for particular tissue sites (e.g., disruption of thyroid
  8      function) may lead to an anticipation of site concordance.
  9
10      2.2.2.2. Perinatal Carcinogenicity Studies
11            The objective of perinatal carcinogenesis studies is to determine the carcinogenic
12      potential and dose-response relationships of the test agent  in the developing organism. Some
13      investigators have hypothesized that the age of initial exposure to a chemical carcinogen may
14      influence the carcinogenic response (Vesselinovitch et al., 1979; Rice, 1979;  McConnell, 1992).
15      Current standardized long-term carcinogenesis bioassays generally begin dosing animals at 6-8
16      weeks of age and continue dosing for the lifespan of the animal (18-24 months).  This protocol
17      has been modified in some cases to investigate the potential of the test agent to induce
18      transplacental carcinogenesis or to  investigate the potential differences following perinatal and
19      adult exposures, but currently there is not a standardized protocol for testing agents  for
20      carcinogenic effects following prenatal or early postnatal exposure.
21            Several cancer bioassay studies have compared adult and perinatal exposures (see
22      McConnell, 1992; U.S. EPA, 1996b).  A review of these studies reveals that perinatal exposure
23      rarely identifies carcinogens that are not found in standard animal bioassays.  Exposure that is
24      perinatal can increase the incidence of a given type of tumor. The increase may reflect an
25      increased length of exposure and a  higher dose for the developing organism relative to the adult
26      or an increase in susceptibility in some cases. Additionally, exposure that is perinatal through
27      adulthood sometimes reduces the latency period for tumors to develop in the  growing organism
28      (U.S. EPA, 1996b).  EPA evaluates the usefulness of perinatal studies on an agent-by-agent basis
29      (for example, U.S. EPA, 1997a,b).
30            Perinatal study data analysis generally follows the  principles discussed above for
31      evaluating other long-term carcinogenicity studies. When differences in responses between
32      perinatal animals and adult animals suggest an increased susceptibility of perinatal or postnatal
33      animals, such as the ones below, a separate evaluation of the response should be prepared:
34

        February 27,2003                          2-16             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             •     a difference in dose-response relationship,
  2             •     the presence of different tumor types,
  3             •     an earlier onset of tumors, or
  4             •     an increase in the incidence of tumors.
  5
  6      2.2.2.3. Other Studies
  1             Intermediate-term studies often use protocols that screen for carcinogenic or
  8      preneoplastic effects, sometimes in a single tissue. Some protocols involve the development of
  9      various proliferative lesions, such as foci of alteration in the liver (Goldsworthy et al., 1986).
10      Others use tumor endpoints, such as the induction of lung adenomas in the sensitive strain A
11      mouse (Maronpot et al., 1986) or tumor induction in initiation-promotion studies using various
12      organs such as the bladder, intestine, liver, lung, mammary gland, and thyroid (Ito et al., 1992).
13      In these tests, the selected tissue rather than the whole animal is, in a sense, the test system.
14      Important information concerning the steps in the carcinogenic process and mode of action can
15      be obtained from "start/stop" experiments. In these protocols, an agent is given for a period of
16      time to induce particular lesions  or effects and then stopped in order to evaluate the progression
17      or reversibility of processes (Todd, 1986; Marsman and Popp, 1994).
18             Assays in genetically engineered rodents may provide insight into the chemical and gene
19      interactions involved in carcinogenesis (Tennant et al., 1995). These mechanistically based
20      approaches involve activated oncogenes that are introduced (transgenic)  or tumor suppressor
21      genes that are deleted (knocked out). If appropriate genes are selected, not only may these
22      systems provide information on mechanisms, but the rodents typically show tumor development
23      earlier than in the standard bioassay. Transgenic mutagenesis assays also represent a
24      mechanistic approach for assessing the mutagenic properties of agents as well as developing
25      quantitative linkages between exposure, internal dose, and mutation related to tumor induction
26      (Morrison and Ashby, 1994; Sisk et al., 1994; Hayward et al., 1995).
27             The support that these studies give to a determination of carcinogenicity rests on their
28      contribution to the consistency of other evidence about an agent. For instance, benzoyl peroxide
29      has promoter activity on the skin, but the overall evidence may be less supportive (Kraus et al.,
30      1995). These studies also may contribute information about mode of action.  It is important to
31      recognize the limitations of these experimental protocols, such as  short duration, limited
32      histology, lack of complete development of tumors, or experimental manipulation of the
33      carcinogenic process, that may limit their contribution to the overall assessment.  Generally, their
34      results are appropriate as aids in the interpretation of other toxicological  evidence  (e.g., rodent

        February 27, 2003                          2-17            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      chronic bioassays), especially regarding potential modes of action. On the basis of currently
  2      available information, it is unlikely that any of these assays, which are conducted for 6 months
  3      with 15 animals per group, will replace all chronic bioassays for hazard identification (Spalding
  4      et al., 2000; Guzelian et al., 2000; ILSI, 2001).
  5
  6      2.2.3. Structural Analogue Data
  7             For some chemical classes, there is significant available information, largely from rodent
  8      bioassays, on the carcinogenicity of analogues. Analogue effects are instructive in investigating
  9      carcinogenic potential of an agent as well as in identifying potential target organs, exposures
10      associated with effects, and potential functional class effects or modes of action. All appropriate
11      studies should be included and analyzed, whether indicative of a positive effect or not.
12      Evaluation includes tests in various animal species, strains, and sexes; with different routes of
13      administration; and at various doses, as data are available. Confidence in conclusions is a
14      function of how similar the analogues are to the agent under review in structure, metabolism, and
15      biological activity. It is important to consider this confidence to ensure a balanced position.
16
17
18      2.3. ANALYSIS OF OTHER KEY DATA
19             The physical, chemical, and structural properties of an agent, as well as data on endpoints
20      that are thought to be critical elements of the carcinogenic process, provide valuable insights into
21      the likelihood of human cancer risk. The following sections provide guidance for analyses of
22      these data.
23
24      2.3.1. Physicochemical Properties
25             Physicochemical properties  affect an agent's absorption, tissue distribution
26      (bioavailability), biotransformation, and degradation in the body and are important determinants
27      of hazard potential (and dose-response analysis).  Properties that should be analyzed include, but
28      are not limited to, molecular weight, size, and shape; valence state; physical state (gas, liquid,
29      solid); water or lipid solubility, which can influence retention and tissue distribution; and
30      potential for chemical degradation or stabilization in the body.
31             An agent's potential for chemical reaction with cellular components, particularly with
32      DNA and proteins, is also important.  The agent's molecular size and shape, electrophilicity, and
33      charge  distribution are considered in order to decide whether they would facilitate such
34      reactions.

        February 27,2003                           2-18             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      2.3.2. Structure-Activity Relationships
  2             SAR analyses and models can be used to predict molecular properties, surrogate
  3      biological endpoints, and carcinogenicity. Overall, these analyses provide valuable initial
  4      information on agents, they may strengthen or weaken concern, and they are part of the weight
  5      of evidence.
  6             Currently, SAR analysis is most useful for chemicals and metabolites that are believed to
  7      initiate carcinogenesis through covalent interaction with DNA (i.e., DNA-reactive, mutagenic,
  8      electrophilic, or proelectrophilic chemicals) (Ashby and Tennant, 1991). For organic chemicals,
  9      the predictive capability of SAR analysis combined with other toxicity information has been
10      demonstrated (Ashby and Tennant, 1994). The following parameters are useful in comparing an
11      agent to its structural analogues and congeners that produce tumors and affect related biological
12      processes such as receptor binding and activation, mutagenicity, and general toxicity (Woo and
13      Arcos, 1989):
14
15             •     nature and reactivity of the electrophilic moiety or moieties present;
16
17             •     potential to form electrophilic reactive intermediate(s) through chemical,
18                  photochemical, or metabolic activation;
19
20             •     contribution of the carrier molecule to which the electrophilic moiety(ies) is
21                  attached;
22
23             •     physicochemical properties (e.g., physical state, solubility, octanol/water partition
24                  coefficient, half-life in aqueous solution);
25
26             •     structural and substructural features (e.g., electronic, stearic, molecular geometric);
27
28             •     metabolic pattern (e.g., metabolic pathways and activation and detoxification ratio);
29                  and
30
31             •     possible exposure route(s) of the agent.
32
33             Suitable SAR analysis of non-DNA-reactive chemicals and of DNA-reactive chemicals
34      that do not appear to bind covalently to DNA should be based on knowledge or postulation of

        February 27,2003                          2-19            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      the probable mode(s) of action of closely related carcinogenic structural analogues (e.g., receptor
  2      mediated, cytotoxicity related). Examination of the physicochemical and biochemical properties
  3      of the agent may then provide the rest of the information needed in order to make an assessment
  4      of the likelihood of the agent's activity by that mode of action.
  5
  6      2.3.3. Comparative Metabolism and Toxicokinetics
  7             Studies of the absorption, distribution, biotransformation, and excretion of agents permit
  8      comparisons among species to assist in determining the implications of animal responses for
  9      human hazard assessment, supporting identification of active metabolites, identifying changes in
10      distribution and metabolic pathway or pathways over a dose range, and making comparisons
11      among different routes of exposure.
12             If extensive data are available (e.g., blood/tissue partition coefficients and pertinent
13      physiological parameters of the species of interest), physiologically based toxicokinetic models
14      can be constructed to assist in a determination of tissue dosimetry, species-to-species
15      extrapolation of dose, and route-to-route extrapolation (Connolly and Andersen, 1991; see
16      Section 3.1.2). If it is not contrary to available data, it may be assumed as a default that
17      toxicokinetic and metabolic processes are qualitatively comparable among species. Discussion
18      of appropriate defaults regarding quantitative comparison and their modifications appears in
19      Chapter3.
20             The qualitative question of whether an agent is absorbed by  a particular route of exposure
21      is important for weight of evidence classification, discussed in Section 2.6.  Decisions about
22      whether route of exposure is a limiting factor on expression of any hazard, in that absorption
23      does not occur by a route, are generally based on studies in which effects of the agent or its
24      structural analogues have been observed by different routes, on physical-chemical properties, or
25      on toxicokinetics studies.
26             Adequate metabolism and toxicokinetic  data can be applied toward the following as  data
27      permit. Confidence in conclusions is enhanced  when in vivo data are available.
28
29             •     Identifying metabolites and reactive intermediates of metabolism and determining
30                  whether one or more of these intermediates is likely to be responsible for the
31                  observed effects. This information on the reactive intermediates appropriately
32                  focuses SAR analysis, analysis of potential modes of action, and estimation of
33                  internal dose in dose-response assessment (D'Souza et al., 1987; Krewski et al.,
34                  1987).

        February 27, 2003                          2-20            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             •     Identifying and comparing the relative activities of metabolic pathways in animals
  2                  and humans and at different ages.  This analysis can provide insights for
  3                  extrapolating results of animal studies to humans.
  4
  5             •     Describing anticipated distribution within the body and possibly identifying target
  6                  organs.  Use of water solubility, molecular weight, and structure analysis can
  7                  support qualitative inferences about anticipated distribution and excretion.  In
  8                  addition, describing whether the agent or metabolite of concern will be excreted
  9                  rapidly or slowly or whether it will be stored in a particular tissue or tissues to be
10                  mobilized later can identify issues  in comparing species and formulating dose-
11                  response assessment approaches.
12
13             •     Identifying changes in toxicokinetics and metabolic pathways with increases in
14                  dose.  These changes may result in important differences between high and low
15                  dose levels in disposition of the agent or its generation of active forms. These
16                  studies play an important role in providing a rationale for dose selection in
17                  carcinogenicity studies.
18
19             •     Identifying and comparing metabolic process differences by age, sex, or other
20                  characteristic so that susceptible subpopulations can be recognized. For example,
21                  metabolic capacity with respect to  P450 enzymes in newborn children is extremely
22                  limited compared to that in adults,  so that a carcinogenic metabolite formed through
23                  P450 activity will have limited effect in the young, whereas a carcinogenic agent
24                  deactivated through P450 activity will result in increased susceptibility of this
25                  lifestage (Cresteil, 1998). A variety of changes in toxicokinetics and physiology
26                  occur from the fetal stage to post-weaning to young child.  Any of these changes
27                  may make a difference for risk (Renwick,  1998).
28
29             •     Determining bioavailability via different routes of exposure by analyzing uptake
30                  processes under various exposure  conditions. This analysis supports identification
31                  of hazards for untested routes. In addition, use of physicochemical data (e.g.,
32                  octanol-water partition coefficient  information) can support an inference about the
33                  likelihood of dermal absorption (Flynn, 1990).
34

        February 27, 2003                          2-21            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1            Attempts should be made in all of these areas to clarify and describe as much as possible
  2      the variability to be expected because of differences in species, sex, age, and route of exposure.
  3      The analysis takes into account the presence of subpopulations of individuals who are
  4      particularly vulnerable to the effects of an agent because of toxicokinetic or metabolic
  5      differences (genetically or environmentally determined) (Bois et al., 1995) and is a special
  6      emphasis for assessment of risks to children.
  7
  8      2.3.4. Toxicological and Clinical Findings
  9            Toxicological findings in experimental animals and clinical observations in humans are
10      important resources for the cancer hazard assessment.  Such findings provide information on
11      physiological effects and effects on enzymes, hormones, and other important macromolecules as
12      well as on target organs for toxicity.  Given that the cancer process represents defects in terminal
13      differentiation, growth control, and cell death, developmental studies of agents may provide an
14      understanding of the activity of an agent that carries over to cancer assessment. Toxicity studies
15      in animals by different routes of administration support comparison of absorption and
16      metabolism by those routes. Data on human variability in standard clinical tests may provide
17      insight into the range of human susceptibility and the common mechanisms of agents that affect
18      the tested parameters.
19
20      2.3.5. Events Relevant to Mode of Carcinogenic Action
21            Knowledge of the biochemical and biological changes that precede tumor development
22      (which include but are not limited to mutagenesis, increased cell proliferation, inhibition of
23      programmed cell death, and receptor activation) may provide important insight for determining
24      whether a cancer hazard exists and may help inform the dose-response relationship below the
25      range of observable tumor response.  Because cancer results from a series of genetic alterations
26      in the genes that control cell growth, division, and differentiation (Vogelstein et al., 1988;
27      Hanahan and Weinberg, 2000; Kinzler and Vogelstein, 2002), the ability of an agent to affect
28      genotype (and hence gene products) or gene expression is of obvious importance in evaluating
29      its influence on the carcinogenic process.  Initial and key questions to examine are: Does the
30      agent (or its metabolite) interact directly with DNA, leading to mutations that bring about
31      changes in gene products or gene expression?  Does the agent bring about effects on gene
32      expression via other nondirect DNA interaction processes?
33            Furthermore, carcinogenesis involves a complex series and  interplay of events that alter
34      the signals a cell receives from its extracellular environment,  thereby promoting uncontrolled

        February 27, 2003                         2-22            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      growth.  Many, but not all, mutagens are carcinogens, and some, but not all, agents that induce
  2      cell proliferation lead to tumor development. Thus, understanding the range of key steps in the
  3      carcinogenic process upon which an agent might act is essential for evaluating its mode of
  4      action. Endpoints that provide insight into an agent's ability to alter gene products and gene
  5      expression, together with other features of an agent's potential mode of carcinogenic action, are
  6      discussed below.
  7
  8      2.3.5.1. Direct DNA-Reactive Effects
  9            It is well known that many carcinogens are electrophiles that interact with DNA,
10      resulting in DNA adducts and breakage (referred to in these guidelines as direct DNA effects).
11      Usually during the process of DNA replication, these DNA lesions can be converted into
12      mutations and chromosomal alterations, which then may initiate and otherwise contribute to the
13      carcinogenic process (Shelby and Zeiger, 1990; Tinwell and Ashby, 1991; IARC,  1999).  Thus,
14      studies of mutations and other genetic lesions continue to be predictive in the assessment of
15      potential human cancer hazard and in the understanding of an agent's mode of carcinogenic
16      action.
17            EPA has published testing guidelines for detecting the ability of an agent to damage
18      DNA and produce mutations and chromosomal alterations.  Briefly, standard tests for gene
19      mutations in bacteria and mammalian cells in vitro and in vivo and for structural chromosomal
20      aberrations in vitro and in vivo are important examples of relevant methods. New molecular
21      approaches such as mouse mutations and cancer transgenic models, are providing a means to
22      examine mutation at tissue sites where the tumor response is observed (Heddle and Swiger,
23      1996; Tennant et al., 1999). Additionally, continued  improvements in fluorescent-based
24      chromosome staining methods (FISH, fluorescent in situ hybridization) will allow the detection
25      of specific chromosomal abnormalities in relevant target tissues (Tucker and Preston,  1998).
26            Endpoints indicative of DNA damage but not  measures of mutation per se, such as DNA
27      adducts or strand breakage, can be detected in relevant target tissues and thus contribute to
28      evaluating an agent's mutagenic potential. Evidence  of chemical-specific DNA adducts (e.g.,
29      reactions at oxygen sites in DNA bases or with ring nitrogens of guanine and adenine) provides
30      information on a mutagen's ability to directly interact with DNA (La and Swenberg, 1996).  It
31      should be noted that an increase in DNA binding shown with a radioactive label incorporated in
32      the chemical (e.g., C14) may reflect a direct DNA-reactive mechanism, but this needs to be
33      examined, because the label may reflect reuse of C14 in the synthesis of DNA rather than
34      binding. Some planar molecules (e.g., 9-aminoacridine) intercalate between base pairs of DNA,

        February 27, 2003                         2-23            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      which results in a physical distortion in DNA that may lead to mutations when DNA replicates.
 2      As discussed below, some carcinogens do not interact directly with DNA, but they can produce
 3      increases in endogenous levels of DNA adducts (e.g., 8-hydroxyguanine) by indirect
 4      mechanisms.
 5
 6      2.3.5.2. Indirect DNA Effects or Other Effects on Genes/Gene Expression
 1            Although some carcinogens may result in an elevation of mutations or cytogenetic
 8      anomalies, as detected in standard assays, they may do so by indirect mechanisms. These effects
 9      may be brought about by chemical-cell interactions rather than by the chemical (or its
10      metabolite) directly interacting with DNA. An increase in mutations might be due to cytotoxic
11      exposures causing regenerative proliferation or to mitogenic influences (Cohen and Ellwein,
12      1990). Increased cell division may elevate mutation by clonal expansion of initiated cells or by
13      increasing the number of genetic errors by rapid cell division and reduced time for DNA repair.
14      Some agents might result in an elevation of mutations by interfering with the enzymes involved
15      in DNA repair and recombination (Barrett and Lee, 1992). Damage to certain critical DNA
16      repair genes or other genes (e.g., the p53 gene) may result in genomic instability, which
17      predisposes cells to  further genetic alterations and increases the probability of neoplastic
18      progression (Harris  and Hollstein, 1993; Levine et al., 1994; Rouse and Jackson, 2002).
19      Likewise, DNA repair processes may be saturated at certain doses of a chemical, leading to an
20      elevation of genetic alterations.
21            The initiation of programmed cell death (apoptosis) can potentially be blocked by an
22      agent, thereby permitting replication of cells carrying genetic errors that would normally be
23      removed from the proliferative pool. For example, peroxisome proliferators can suppress
24      apoptotic pathways  (Shulte-Hermann et al., 1993; Bayly et al., 1994) that could enhance the
25      carcinogenic process.  At certain doses an agent may also generate reactive oxygen species that
26      produce oxidative damage to DNA and other macromolecules (Chang et al. 1988; Kehrer, 1993;
27      Clayson et al., 1994).  The role of cellular alterations that are attributable to oxidative damage in
28      tumorigenesis (e.g., 8-hydroxyguanine) is currently unclear.
29            Several carcinogens have been shown to induce aneuploidy (the loss  or gain of
30      chromosomes)  (Barrett, 1992; Gibson et al., 1995). Aneuploidy can result in the loss of
31      heterozygosity  or genomic instability (Cavenee et al.,  1986; Fearon and Vogelstein, 1990).
32      Agents that cause aneuploidy typically interfere with the normal process of chromosome
33      segregation by interacting with non-DNA targets such as the proteins needed for chromosome
34      segregation and chromosome movement.  All tumors (with the possible exception of some

        February 27, 2003                         2-24            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      leukemias and lymphomas) are aneuploid, but whether this chromosome imbalance is the cause
  2      or the effect of tumorigenesis is not clear. Thus, it is important to understand whether the agent
  3      induces aneuploidy as a key early event in the carcinogenic process or is necessary for tumor
  4      progression.
  5             It is possible for an agent to alter gene expression by transcriptional, translational, or
  6      post-translational modifications. For example, perturbation of DNA methylation patterns may
  7      cause effects that contribute to carcinogenesis (Jones, 1986; Holliday, 1987; Goodman and
  8      Counts, 1993; Chuang et al., 1996; Baylin and Bestor, 2002).  Overexpression of genes by DNA
  9      amplification has been observed in certain tumors (Vainio et al., 1992).  Gene amplification may
10      result from disproportionate DNA replication. Other mechanisms of altering gene expression
11      may involve cellular reprogramming through hormonal or receptor-mediated mechanisms
12      (Barrett, 1992; Ashby et al., 1994).
13             Both cell proliferation and programmed cell death are mandatory for the maintenance of
14      homeostasis in normal tissues, and alterations in the level or rate of either are important elements
15      of the carcinogenic process. The balance between the two directly affects the survival and
16      growth of initiated cells as well as preneoplastic and tumor cell populations (i.e., increase in cell
17      proliferation or decrease in cell death) (Cohen and Ellwein, 1990, 1991; Cohen et  al., 1991;
18      Bellamy et al., 1995). Thus, measurements of these events contribute to the weight of the
19      evidence for cancer hazard prediction and to mode of action understanding. In studies of
20      proliferative effects distinctions should be made between mitogenesis and regenerative
21      proliferation (Cohen and Ellwein, 1990,  1991; Cohen et al., 1991).
22             In applying information from  studies on cell proliferation and apoptosis to risk
23      assessment, it is important to identify the tissues and target cells involved, to measure effects in
24      both normal and neoplastic tissue, to distinguish between apoptosis and necrosis, and to
25      determine the dose that affects these processes. Gap-junctional intercellular communication is
26      believed to play a role in tissue and organ development and in the maintenance of a normal
27      cellular phenotype within tissues. A growing body of evidence suggests that chemical
28      interference with gap-junctional intercellular communication is a contributing factor in tumor
29      development (Swierenga and Yamasaki, 1992; Yamasaki, 1995).
30
31      2.3.5.3. Experimental Considerations in Evaluating Data on Precursor Events
32             Most testing schemes for mutagenicity and other short-term assays were designed for
33      hazard identification purposes; thus, these assays are generally conducted using acute exposures.
34      For data on "precursor steps" to be useful in informing the dose-response curve for tumor

        February 27, 2003                          2-25            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      induction below the level of observation, it is important that data come from in vivo studies and
 2      from studies where exposure is repeated or given over an extended period of time.  Although
 3      consistency of results across different assays and animal models provides a stronger basis for
 4      drawing conclusions, it is desirable to have data on the precursor event in the same target organ,
 5      sex, animal strain, and species as the tumor data. In evaluating an agent's mode of action, it is
 6      usually not sufficient to determine that some event commences upon dosing.  It is important to
 7      understand whether it is a causal event that plays a key role in the process that leads to tumor
 8      development versus an effect of the cancer process itself or simply an associated event.
 9
10      2.3.5.4.  Judging Data
11            Criteria that are generally applicable for judging the adequacy of mechanistically based
12      data include
13
14            •    mechanistic relevance of the data to carcinogenicity,
15            •    number of studies of each endpoint,
16            •    consistency of results in different test systems and different species,
17            •    similar dose-response relationships for tumor and mode of action-related effects,
18            •    conduct of the tests in accordance with generally accepted protocols, and
19            •    degree of consensus and general acceptance among scientists regarding
20                 interpretation of the significance and specificity of the tests.
21
22      Although important information can be gained from in vitro test systems, a higher level of
23      confidence is generally given to data that are derived from in vivo systems, particularly those
24      results that show a site concordance with the tumor data.
25            It is important to remember that when judging and considering the use of any data, the
26      basic standard of quality, as defined by the EPA Information Quality Guidelines, should be
27      satisfied.
28
29      2.4. BIOMARKER INFORMATION
30            Various endpoints can serve as biological markers of events in biological systems or
31      samples. In some cases, these  molecular or cellular effects (e.g., DNA or protein adducts,
32      mutation, chromosomal aberrations, levels of thyroid-stimulating hormone) can be  measured in
33      blood, body fluids, cells, and tissues to serve as biomarkers of exposure in both animals and
34      humans  (Callemen et al., 1978; Birner et al., 1990).  As such, they can

        February 27,2003                         2-26            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
1
              •    act as an internal surrogate measure of chemical dose, representing, as appropriate,
 2                 either recent exposure (e.g., serum concentration) or accumulated (e.g., hemoglobin
 3                 adducts) exposure;
 4
 5            •    help identify doses at which elements of the carcinogenic process are operating;
 6
 7            •    aid in interspecies extrapolations when data are available from both experimental
 8                 animal and human cells; and,
 9
10            •    under certain circumstances, provide insights into the possible shape of the dose-
11                 response curve below levels where tumor incidences are observed (e.g., Choy,
12                 1993).
13
14            Genetic and other findings (such as changes in proto-oncogenes and tumor suppressor
15      genes in preneoplastic and neoplastic tissue or, possibly, measures of endocrine disruption) can
16      indicate the potential for disease and, as such, serve as biomarkers of effect. They, too, can be
17      used in different ways:
18
19            •    The spectrum of genetic changes in proliferative lesions and tumors following
20                 chemical administration to experimental animals can be determined and compared
21                 with that in spontaneous tumors in control animals, in animals exposed to other
22                 agents of varying structural and functional activities, and in persons exposed to the
23                 agent under study.
24
25            •    They may provide a linkage to tumor response.
26
27            •    They may help to identify subpopulations of individuals who may be at an elevated
28                 risk for cancer, for example, cytochrome P450 2D6/debrisoquine sensitivity for
29                 lung cancer (Caporaso et al., 1989) or inherited colon cancer syndromes (Kinzler et
30                 al., 1991; Peltomaki et al.,  1993).
31
32            •   ' As with biomarkers of exposure, it may be justified in some cases to use these
33                 endpoints for dose-response assessment or to provide insight into the potential
      February 27, 2003                          2-27            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1                 shape of the dose-response curve at doses below those at which tumors are induced
 2                 experimentally.
 3
 4            In applying biomarker data to cancer assessment (particularly assessments based on
 5      epidemiologic data), an assessment should consider
 6
 7            •    routes of exposure,
 8            •    exposure to mixtures,
 9            •    time after exposure,
10            •    sensitivity and specificity of biomarkers, and
11            •    dose-response relationships.
12
13      2.5.   MODE OF ACTION—GENERAL CONSIDERATIONS AND FRAMEWORK
14            FOR ANALYSIS
15      2.5.1. General Considerations
16            The interaction between the biology of the organism and the chemical properties of the
17      agent determine whether there is an adverse effect. Thus, mode of action analysis is based on
18      physical, chemical, and biological information that helps to explain key events in an agent's
19      influence on development of tumors.  The entire range of information developed in the
20      assessment is reviewed to arrive at a reasoned judgment. An agent may work by more than one
21      mode of action, both at different sites and at the same tumor site. At least some information
22      bearing on mode of action (e.g., SAR, screening tests for mutagenicity) is present  for most
23      agents undergoing assessment of carcinogenicity, even though certainty about exact molecular
24      mechanisms may be rare.
25            Inputs to mode of action analysis generally include tumor data in humans and animals
26      and among structural  analogues as well as the other key data.  The more complete the data
27      package and the generic knowledge about a given mode of action, the more confidence one has
28      and the more one can replace or refine default positions with relevant information. Reasoned
29      judgments are generally based on  a data-rich source of chemical, chemical class, and tumor type-
30      specific information.  Many times there will be conflicting data and gaps in the information base;
31      it is important to carefully evaluate these uncertainties before reaching any conclusion.
32            In making decisions about potential modes of action and the relevance of animal tumor
33      findings to humans (Ashby et al.,  1990), very often the results of chronic animal studies may
34      give important clues.  Some of the important factors to review include

        February 27, 2003                         2-28            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1           . •    tumor types, for example, those responsive to endocrine influence or those
  2                 produced by reactive carcinogens (Ashby and Tennant, 1991);
  3
  4            •    number of tumor sites, sexes, studies, and species affected or unaffected (Tennant,
  5                 1993);
  6
  7            •    influence of route of exposure, spectrum of tumors, and local or systemic sites;
  8
  9            •    target organ or system toxicity, for example, urinary chemical changes associated
10                 with stone formation, effects on immune surveillance;
11
12            •    presence of proliferative lesions, for example, hepatic foci, hyperplasias;
13
14            •    progression of lesions from preneoplastic to benign to malignant with dose and
15                 time;
16
17            •    ratio of malignant to benign tumors as a function of dose and time;
18
19            •    time of appearance of tumors after commencing exposure;
20
21            •    tumors invading locally, metastasizing, producing death;
22
23            •    tumors at sites in laboratory animals with high or low spontaneous historical
24                 incidence;
25
26            •    biomarkers in tumor cells, both induced and spontaneous, for example, DNA or
27                 protein adducts, mutation spectra, chromosome changes, oncogene activation; and
28
29            •    shape of the dose-response curve in the range of tumor observation, for example,
30                 linear versus profound change in slope.
31
32            Some of the myriad ways in which information from chronic animal studies influences
33     mode of action judgments include the following.  Multisite and multispecies tumor effects are
34     often associated with mutagenic agents.  Tumors restricted to one sex or species may suggest an

       February 27, 2003                         2-29           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      influence restricted to gender, strain, or species. Late onset of tumors that are primarily benign
 2      or are at sites with a high historical background incidence or that show reversal of lesions on
 3      cessation of exposure may point to a growth-promoting mode of action. It is important to
 4      consider the possibility that an agent may act differently in different tissues or have more than
 5      one mode of action in a single tissue.
 6            Simple knowledge of sites of tumor increase in rodent studies can give preliminary clues
 7      as to mode of action. Experience at the National Toxicology Program (NTP) indicates that
 8      substances that are DNA reactive and that produce gene mutations may be unique in producing
 9      tumors in certain anatomical sites, whereas tumors at other sites may arise from both mutagenic
10      or nonmutagenic influences (Ashby and Tennant, 1991; Huff et al., 1991).
11
12      2.5.2. Evaluating a Hypothesized Mode of Action
13      2.5.2.1. Peer Review
14            This section contains a framework for evaluating a hypothesized mode of action. In
15      reaching conclusions, the question of "general acceptance" of a mode of action should be tested
16      as part of the independent peer review that EPA obtains for its assessment and conclusions.  In
17      some cases the mode of action may already have been established by development of a large
18      body of research information and characterization of the phenomenon over time.  In some cases
19      there will have been development of an Agency policy (e.g., mode of action involving alpha-2u-
20      globulin in the male rat, U.S. EPA, 1991b) or a series  of previous assessments in which both the
21      mode of action and its applicability to particular cases has been explored. If so, the assessment
22      and its peer review can  focus on the evidence that a particular agent acts in this mode. When
23      necessary, the peer review should also evaluate the strengths and weaknesses of competing
24      modes of action.
25            In other cases, the mode of action may not have previously been the subject of an Agency
26      document.  If so, the data to support both the mode of action and the associated activity of the
27      agent should undergo EPA assessment and subsequent peer review.
28
29      2.5.2.2.  Use of the Framework
30            The framework  supports  a full analysis of mode of action information, but it can also be
31      used as a screen to decide whether sufficient information is available to evaluate  or whether the
32      data gaps are too substantial to justify further analysis. Mode of action conclusions are used to
33      address the question of human relevance of animal tumor responses, to address differences in
34      anticipated response among humans, such as between children and adults or men and women;

        February 27,2003                         2-30             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      and as the basis of decisions about the anticipated shape of the dose-response relationship.
  2      Guidance on the latter appears in Section 3.
  3
  4      2.5.3. Framework for Evaluating Each Hypothesized Carcinogenic Mode of Action
  5            This framework is intended to be an analytic tool for judging whether available data
  6      support a mode of carcinogenic action hypothesized for an agent. This mode of action
  7      framework was initiated by the International Programme for Chemical Safety (WHO,  1999). It
  8      is based upon considerations for causality in epidemiologic investigations originally articulated
  9      by Hill (1965) but later modified by others and extended to experimental studies. The original
10      Hill criteria were applied to epidemiologic data, whereas this framework is applied to a much
11      wider assortment of experimental data, so it retains the basic principles of Hill but is much
12      modified in content.
13            The modified Hill criteria can be useful for organizing thinking about aspects of
14      causation, and they are consistent with the scientific method of developing hypotheses and
15      testing those hypotheses experimentally. During analysis by EPA, and as guidance for peer
16      review, a key question is whether the data to support a mode of action meet the standards
17      generally applied in experimental biology regarding inference of causation.
18            All pertinent studies are reviewed in analyzing a mode of action, and an overall weighing
19      of evidence is performed, laying out the strengths, weaknesses, and uncertainties of the case as
20      well as potential alternative positions and rationales.  Identifying data gaps and research needs is
21      also part of the assessment.
22            To show that a hypothesized mode of action is operative, it is generally important to
23      outline the sequence of events leading to cancer, to identify key events that can be measured, and
24      to weigh information to determine whether there is a causal relationship between events and
25      cancer formation. It is not generally expected that the complete sequence will be known at the
26      molecular level. Instead, empirical observations made at different levels of biological
27      organization—biochemical, cellular, physiological, tissue, organ, and system—are analyzed.
28            Several important points should be considered when working with the framework:
29
30            •     The topics listed for analysis should not be regarded as a checklist of necessary
31                  "proofs." The judgment of whether a hypothesized mode of action is supported by
32                  available data takes account of the analysis as a whole.
33
        February 27, 2003                         2-31            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             •     The framework provides a structure for organizing the facts upon which
  2                  conclusions as to mode of action rest. The purpose of using the framework is to
  3                  make analysis transparent and to allow the reader to understand the facts and
  4                  reasoning behind a conclusion.
  5
  6             •     The framework does not dictate an answer. The weight of evidence that is
  7                  sufficient to support a decision about a mode of action may be less or more,
  8                  depending on the purpose of the analysis, for example, screening, research needs
  9                  identification, or full risk assessment. To make the reasoning transparent, the
10                  purpose of the analysis should be made apparent to the reader.
11
12             •     Toxicokinetic studies may contribute to mode of action analysis by identifying the
13                  active form of an agent that is central to the mode of action. Apart from
14                  contributing in this way, toxicokinetics studies may reveal effects of saturation of
15                  metabolic processes. These are not considered key events in a mode of action, but
16                  they are given separate consideration in assessing dose metrics and potential
17                  nonlinearity of the dose-response relationship.
18
19             •     Generally, "sufficient" support is a matter of scientific judgment in the context of
20                  the requirements of the decision maker or in the context of science policy guidance
21                  regarding a certain mode of action.
22
23             •     Even when a hypothesized mode of action is supported for a described response in a
24                  specific tissue, it may not explain other tumor responses observed, which need
25                  separate consideration in hazard and dose-response assessment.
26
27             In a risk assessment document, the analysis of a hypothesized mode of action should be
28      presented before or with the characterization of an agent's potential hazard to humans.
29             For each tumor site, the mode of action analysis should begin with a description of the
30      hypothesized mode of action and its sequence of key events (see Section 2.5.3.1). This should
31      be followed by a discussion of various aspects of the experimental support for the hypothesized
32      mode of action (see Section 2.5.3.2). The possibility of other modes of action also should be
33      considered (see Section 2.5.3.3);  if there is evidence for more than one mode of action, each
34      should receive a separate analysis. Conclusions about the hypothesized mode of action should

        February 27, 2003                         2-32             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      address whether the mode of action is supported in animals and is relevant to humans and which
 2      populations or lifestages can be particularly susceptible (see Section 2.5.3.4).
 3
 4      2.5.3.1. Description of 'the Hypothesized Mode of 'Action
 5            Summary description of the hypothesized mode of action. For each tumor site, the mode
 6      of action analysis should begin with a description of the hypothesized mode of action and its
 7      sequence of key events. If there is evidence for more than one mode of action, each receives a
 8      separate analysis.
 9            Identification of key events. This is a consideration devised for this framework.  In order
10      to judge how well data support involvement of a key event in carcinogenic processes, the
11      experimental definition of the event or events should be clear and repeatable.  To support an
12      association, experiments should define and measure an event consistently.
13
14            •    Can a  list of events be identified that are key to the carcinogenic process?
15            •    Are the events well defined?
16
17      Pertinent observations may include, but are not limited to, receptor-ligand changes, cytotoxicity,
18      cell cycle effects, increased cell growth, organ weight differences, histological changes, hormone
19      or other protein perturbations, DNA and chromosome effects.
20
21      2.5.3.2. Discussion of the Experimental Support for the Hypothesized Mode of Action
22            The experimental support for the hypothesized mode of action should be discussed from
23      several viewpoints patterned after the Hill criteria (see Section 2.2.1.3).  For illustration, the
24      explanation of each topic includes  typical questions to be addressed to the available empirical
25      data and experimental observations anticipated to be pertinent.  The latter will vary from case to
26      case. For a particular mode of action, certain observations may be established as essential in
27      practice or policy, for example, measures of thyroid hormone levels in supporting thyroid
28      hormone elevation as a key event in carcinogenesis.
29            Strength,  consistency, specificity of association. A statistically significant association
30      between events and a tumor response observed in well-conducted studies is generally supportive
31      of causation.  Consistent observations in a number of such studies with differing experimental
32      designs increase that support, because different designs may reduce unknown biases.  Studies
33      showing "recovery," that is, absence  or reduction of carcinogenicity when the event is blocked or
34      diminished, are particularly  important tests of the association. Specificity of the association,

        February 27,2003                          2-33            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      without evidence of other modes of action, strengthens a causal conclusion. A lack of strength,
  2      consistency, and specificity of association weakens the causal conclusions for a particular mode
  3      of action.
  4
  5             •     What is the level of statistical and biological significance for each event and for
  6                  cancer?
  7
  8             •     Do independent studies and different experimental hypothesis-testing approaches
  9                  produce the same associations?
10
11             •     Does the agent produce effects other than those hypothesized?
12
13             •     Is the key event associated with precursor lesions?
14
15      Pertinent observations include tumor response associated with events (site of action logically
16      relates to event[s]), precursor lesions associated with events, initiation-promotion studies, and
17      stop/recovery studies.
18             Dose-response concordance.  If a key event and tumor endpoints increase with dose such
19      that the key events forecast the appearance of tumors at a later time or higher dose, a causal
20      association can be strengthened. Dose-response associations of the key event with other
21      precursor events can add further strength. Difficulty arises when an event is not causal but
22      accompanies the process generally. For example, if tumors and the hypothesized precursor both
23      increase with dose, the two responses will be correlated regardless of whether a causal
24      relationship exists. This is similar to the issue of confounding in epidemiologic studies.  Dose-
25      response studies coupled with mechanistic studies can assist in clarifying these relationships.
26
27             •     What are the correlations among doses producing events and cancer?
28
29      Pertinent observations include 2-year bioassay observation of lesions correlated with
30      observations of hormone changes and the same lesions in shorter term studies or in interim
31      sacrifice.
32             Temporal relationship.  If an event is a cause of tumorigenesis, it must precede tumor
33      appearance.  An event may also be observed contemporaneously or after tumor appearance;
34      these observations may add to the strength of association but not to the temporal association.

        February 27, 2003                          2-34            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             •     What is the ordering of events that underlie the carcinogenic process?
  2             •     Is this ordering consistent among independent studies?
  3
  4      Pertinent observations include studies of varying duration observing the temporal sequence of
  5      events and tumorigenicity.
  6             Biological plausibility and coherence. It is important that the hypothesized mode of
  7      action and the events that are part of it be based on current understanding of the biology of
  8      cancer to be accepted.  If the body of information under scrutiny is consistent with other
  9      examples (including structurally related agents) for which the hypothesized mode of action is
10      accepted, the case is strengthened. Because some modes of action can be anticipated to evoke
11      effects other than cancer, the available toxicity database on noncancer effects, for example,
12      reproductive effects of certain hormonal disturbances, can contribute to this evaluation.
13
14             •    Is the mode of action consistent with what is known about carcinogenesis in general
15                 and for the case specifically?
16
17             •    Are carcinogenic effects  and events consistent across structural analogues?
18
19             •    Is the database on the agent internally consistent in supporting the purported mode
20                 of action, including relevant noncancer toxicities?
21
22      Pertinent observations include the scientific basis for considering a hypothesized mode of action
23      generally, given current state of knowledge of carcinogenic processes; previous examples of data
24      sets showing the mode of action; data  sets on analogues; and coherence of data in this case from
25      cancer and noncancer toxicity studies.
26
27      2.5.3.3.  Consideration of the Possibility of Other Modes of Action
28             The possible involvement of more than one mode of action at the tumor site should be
29      considered. Pertinent observations that are not consistent with the hypothesized mode of action
30      can suggest the possibility of other modes of action.  Some pertinent observations can be
31      consistent with more than one mode of action. Futhermore, different modes of action can
32      operate in different dose ranges;  for example, an agent can act predominantly through
33      cytotoxicity at high doses and through mutagenicity  at lower doses where cytotoxicity does not
34      occur.

        February 27, 2003                          2-35            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1            If there is evidence for more than one mode of action, each should receive a separate
 2      analysis. There may be an uneven level of experimental support for the different modes of
 3      action.  Sometimes this can reflect disproportionate resources spent on investigating one
 4      particular mode of action and not the validity or relative importance of the other possible modes
 5      of action.
 6
 7      2.5.3.4. Conclusions About the Hypothesized Mode of Action
 8            Conclusions about the hypothesized mode of action should address the following
 9      questions:
10            (a) Is the hypothesized mode of action sufficiently supported in the test animals?
11      Associations observed between key events and tumors may or may not support an inference of
12      causation.  The conclusion that the  agent causes a sequence of key events that results in tumors is
13      strengthened as more aspects of causation are satisfied and weakened as fewer are satisfied.
14      Consistent results in different experiments that test the hypothesized mode of action build
15      support for that mode of action.  Replicating results in a similar experiment does not generally
16      meaningfully strengthen the original evidence, and discordant results generally weaken that
17      support. Experimental challenge to the hypothesized mode of action, where interrupting the
18      sequence of key events suppresses the tumor response or enhancement of key events increases
19      the tumor response, creates very strong support for the mode of action.
20            (b) Is the hypothesized mode of action relevant to humans?  If a hypothesized mode of
21      action is sufficiently supported in the test animals, the sequence of key precursor events should
22      be reviewed to identify critical similarities and differences between the test animals and humans.
23      The question of concordance can be complicated by cross-species differences in toxicokinetics
24      or toxicodynamics. For example, the active agent can be formed through different metabolic
25      pathways in animals and humans.  Any information suggesting quantitative differences between
26      animals and humans is flagged for consideration in the dose-response assessment.  This includes
27      the potential for  different internal doses of the active agent or for differential occurrence of a key
28      precursor event.
29            "Relevance" of a potential mode of action is considered in the context of characterization
30      of hazard, not level of risk.  Anticipated levels of human exposure are not used to determine
31      whether the hypothesized mode of action is relevant to humans. Exposure information is
32      integrated into the overall risk characterization.
33            The question of relevance considers all populations and lifestages. It is possible that the
34      conditions under which a mode of action operates exist primarily in a particular population or

        February 27, 2003                         2-36            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      lifestage, for example, in those with a pre-existing hormonal imbalance.  Other populations or
  2      lifestages may not be analogous to the test animals, in which case the question of relevance
  3      would be decided by inference.
  4             Special attention should be paid to whether tumors can arise from childhood exposure,
  5      considering various aspects of development during these lifestages. Because the studies that
  6      support a mode of action are typically conducted in mature animals, conclusions about relevance
  7      during  childhood generally rely on inference.  There is currently no suggested default to settle
  8      the question of whether tumors arising through the hypothesized mode of action are relevant
  9      during  childhood; understanding the mode of action implies that there are sufficient data (on
10      either the specific agent or the general mode of action) to form a confident conclusion about
11      relevance during childhood.
12             (c) Which populations or lifestages can be particularly susceptible to the hypothesized
13      mode of action? If a hypothesized mode of action is judged relevant to humans, information
14      about the key precursor events is reviewed to identify populations or lifestages that can be
15      particularly susceptible to their occurrence. Although agent-specific data would provide the
16      strongest indication of susceptibility, this review may rely on general knowledge about the
17      precursor events and characteristics of individuals susceptible to these events. Any information
18      suggesting quantitative differences between populations or lifestages  should be flagged for
19      consideration in the dose-response assessment (see Section 3.5). This includes the potential for a
20      higher internal dose of the active agent or for an increased occurrence of a key precursor event.
21      Quantitative differences may result in separate risk estimates for susceptible populations or
22      lifestages.
23             The possibility that childhood is a susceptible period for exposure should be explicitly
24      addressed. Generic understanding of the mode of action can be used to gauge childhood
25      susceptibility, and this determination can be refined through analysis  of agent-specific data.
26
27      2.6. WEIGHT OF EVIDENCE NARRATIVE
28             The weight of evidence narrative is a short summary (one to two pages) that explains an
29      agent's  human carcinogenic potential and the conditions that characterize its expression. It can
30      stand alone and it can be useful to risk managers and nonexpert readers.
31             Weight of evidence should be presented as a narrative laying out the complexity of
32      information that is essential to understanding the hazard and its dependence on the circumstances
33      of exposure or the traits of an exposed population. For example, route of exposure can be used
34      to qualify a hazard if an agent is not absorbed by some routes.  Other examples are when an

        February 27, 2003                          2-37            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      agent's mode of action occurs only on reaching a minimum dose or a minimum duration.
  2      Another example is when a hazard is expressed disproportionately in individuals possessing a
  3      specific gene; such characterizations may follow from a better understanding of the human
  4      genome.  Similarly, a hazard can be attributable to exposures during a susceptible lifestage on
  5      the basis of our understanding of human development.
  6             To capture this complexity, a weight of evidence narrative generally includes
  7
  8             •     conclusions about human carcinogenic potential and the conditions that characterize
  9                  its expression (route, magnitude, and duration of exposure; susceptible populations
10                  or lifestages),
11
12             •     a summary of the key evidence supporting these conclusions,
13
14             •     a summary of the key default options invoked when the available information is
15                  inconclusive, and
16
17             •     a summary of potential modes of action and how they reinforce the conclusions.
18
19             To provide some measure of clarity and consistency in an otherwise free-form narrative,
20      weight of evidence descriptors should be used in the first sentence of the narrative. Applying a
21      descriptor is a matter of judgment and cannot be reduced to a formula.  Each descriptor may be
22      applicable to a wide variety of potential data sets and weights of evidence.  Descriptors represent
23      points along a continuum of evidence; consequently, there are gradations and borderline cases
24      that are clarified by the full narrative.  Using descriptors within a narrative preserves and
25      presents the complexity that is an essential part of the hazard characterization.  Risk managers
26      should consider the entire range of information included in the narrative rather than
27      focusing simply on the descriptor. These narratives are intended to permit sufficient flexibility
28      to accommodate new scientific understanding and new testing methods as they are developed
29      and accepted by the scientific community and the public.
30             In borderline cases, the narrative explains the case for choosing one descriptor and
31      discusses the arguments for considering but not choosing another. For example, between
32      "suggestive" and "likely" or between "suggestive" and "inadequate," the explanation clearly
33      communicates the information needed to appropriately consider the agent's carcinogenic
34      potential in subsequent decisions.

        February 27, 2003                         2-3 8            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             Multiple descriptors can be used for a single agent when carcinogenesis is dose- or route-
  2      dependent.  For example, if an agent causes point-of-contact tumors by one exposure route but
  3      adequate testing is negative by another route, then the agent could be described as likely to be
  4      carcinogenic by the first route but not likely to be carcinogenic by the second. Another example
  5      is when the mode of action is sufficiently understood to conclude that a key event in tumor
  6      development would not occur below a certain dose range. In this case, the agent could be
  7      described as likely to be carcinogenic above a certain dose range but not likely to be
  8      carcinogenic below that range.
  9             Descriptors can be used when an agent has not been tested in a cancer bioassay but
10      toxicokinetic and mode of action information are available to make a strong logical case through
11      scientific inference. For example, if an agent is one of a well-defined class of agents that are
12      understood to operate through a common  mode of action, then in the narrative the untested agent
13      would have the same descriptor as the class.  Another example is when an untested agent's
14      effects are understood to be caused by a human metabolite, in which case in the narrative the
15      untested agent would have the same descriptor as the metabolite. As new testing methods are
16      developed and used, assessments may increasingly be based on inferences  from toxicokinetic
17      and mode of action information in the absence of tumor studies in animals  or humans.
18             When tumors occur at a site other  than the point of initial contact, the descriptor
19      generally applies to all exposure routes that have not been adequately tested at sufficient doses.
20      An exception occurs when there is convincing toxicokinetic information that  absorption does not
21      occur by another route.
22             When a well-studied agent produces tumors only at a point of initial contact, the
23      descriptor generally applies only to the exposure route producing tumors unless the mode of
24      action is relevant to other routes. The rationale for this conclusion would be explained in the
25      narrative.
26             Dose can represent a qualitative limitation on hazard.  In some cases reaching a certain
27      dose range can be a precondition for effects to occur, as when cancer is secondary to another
28      toxic effect that appears only above a certain dose.  In other cases exposure duration can be a
29      precondition for hazard if effects occur only after exposure is sustained for a certain duration.
30      These qualitative considerations differ from the quantitative issues of relative absorption  or
31      potency at different dose levels, which are addressed in the dose-response assessment.
32             When multiple bioassays have led to a borderline case, mode of action studies are likely
33      to hold the key to resolution of the more appropriate descriptor. When bioassays are few, further
        February 27,2003                          2-39            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      bioassays to replicate a study's results or to investigate the potential for effects in another sex,
 2      strain, or species may be useful.
 3            When there are few pertinent data, the descriptor makes a statement about the database,
 4      for example, "inadequate information to assess carcinogenic potential" or a database that
 5      provides "suggestive evidence of carcinogenic potential." With more information, the descriptor
 6      expresses a conclusion about the agent's carcinogenic potential to humans. If the conclusion is
 7      positive, the agent could be described as "likely to be carcinogenic to humans" or (with strong
 8      evidence) "carcinogenic to humans." If the conclusion is negative, the agent could be described
 9      as "not likely to be carcinogenic to humans."
10            The following descriptors may be of value as part of the weight-of-evidence narrative:
11
12      "Carcinogenic to Humans "
13            This descriptor indicates strong evidence of human carcinogenicity.  It covers different
14      combinations of evidence:
15
16            •    This descriptor is appropriate when there is convincing epidemiologic evidence of a
17                 causal association between human exposure and cancer.
18
19            •    Exceptionally, this descriptor is  equally appropriate with a lesser weight of
20                 epidemiologic evidence that is strengthened by other lines of evidence. It can be
21                 used when all of the following conditions are met: (a) there is strong evidence of an
22                 association between human exposure and either cancer or the key precursor events
23                 of the agent's mode of action but not enough for a causal association, and (b) there
24                 is extensive evidence of carcinogenicity in animals, and (c) the mode(s) of
25                 carcinogenic action and associated key precursor events have been identified in
26                 animals, and (d) the key precursor events that precede the cancer response in
27                 animals are anticipated to occur in humans and progress to tumors, based on
28                 available biological information.
29
30      "Likely to Be Carcinogenic to Humans"
31            This descriptor is appropriate when the weight of the evidence  is adequate to demonstrate
32      carcinogenic potential to humans but does not reach the weight of evidence for the descriptor
33      "carcinogenic to humans." Adequate evidence consistent with this descriptor covers a broad
        February 27,2003                         2-40            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1      spectrum.  Some examples to illustrate the broad range of data combinations that are covered by
 2      this descriptor include
 3
 4            •    an agent with some evidence of an association between human exposure and
 5                 cancer, with or without evidence of carcinogenicity in animals.
 6
 7            •    an agent that has tested positive in more than one species, sex, strain, site, or
 8                 exposure route, with or without evidence of carcinogenicity in humans;
 9
10                 a positive study that indicates a highly significant result, for example, an
11                 uncommon tumor, a high degree of malignancy, or an early age at onset;
12
13            •    a positive study that is strengthened by other lines of evidence, for example, some
14                 evidence of an association between human exposure and cancer (but not enough to
15                 infer a causal association), or evidence that the agent or an important metabolite
16                 causes events generally known to be associated with tumor formation (such as DNA
17                 reactivity or effects on cell growth control) likely to be related to the tumor
18                 response in this case; or
19
20            •    a robust animal tumor response in a single experiment that is assumed to be relevant
21                 to humans.
22
23            Although the term "likely" can have a probabilistic connotation in other contexts, its use
24      as a weight of evidence descriptor does not correspond to a quantifiable probability.  This is
25      because the data that support cancer assessments generally are not suitable for numerical
26      calculations of the probability that an agent is a carcinogen.  The weight of evidence descriptor
27      "likely to be carcinogenic to humans" may be taken loosely to imply that an agent is more likely
28      than not—but is not certain—to cause cancer in humans. Other health agencies have expressed a
29      comparable weight of evidence using terms such as "reasonably anticipated to be a human
30      carcinogen" (NTP) or "probably carcinogenic to humans" and "possibly carcinogenic to
31      humans" (International Agency for Research on Cancer).
32
33
34

        February 27,2003                         2-41            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      "Suggestive Evidence of Carcinogenic Potential"
  2             This descriptor of the database is appropriate when the weight of evidence is suggestive
  3      of carcinogenicity; a concern for potential carcinogenic effects in humans is raised, but the data
  4      are judged not sufficient for a stronger conclusion. This descriptor covers a spectrum of
  5      evidence associated with varying levels of concern for carcinogenicity, ranging from a positive
  6      result in the only study on an agent to a single positive result in an extensive database that
  7      includes negative studies in other species.  Depending on the extent of the database, additional
  8      studies may or may not provide further insights.  Some examples include
  9
10             •    a marginal increase in tumors observed only in a single animal or human study;
11
12             •    a slight increase in a tumor with a high background rate in that sex and strain;
13
14             •    a statistically significant increase at one dose only but no significant response at the
15                 other doses or trend overall; or
16
17             •    evidence of a response in a study whose power, design, or conduct limits the ability
18                 to draw a confident conclusion.
19
20      "Inadequate Information to Assess Carcinogenic Potential"
21             This descriptor of the database is appropriate when available data are judged inadequate
22      for applying one of the other descriptors.  Additional studies generally would be expected to
23      provide further insights.  Some examples include
24
25             •    little or no pertinent information.
26
27             •    conflicting evidence, that is, some studies provide evidence of carcinogenicity but
28                 other studies of equal quality in the same sex and strain are negative. (Differing
29                 results, that is, positive results in some studies  and negative results in one or more
30                 different experimental systems, do not constitute conflicting evidence, as the term is
31                 used here. Depending on the overall weight of evidence, differing results can be
32                 considered either suggestive evidence or likely evidence.)
33
        February 27, 2003                          2-42            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             •    negative results that are not sufficiently robust for the descriptor, "not likely to be
  2                 carcinogenic to humans."
  3
  4      "Not Likely to Be Carcinogenic to Humans"
  5             This descriptor is appropriate when the available data are considered robust for deciding
  6      that there is no basis for human hazard concern. In some instances, there can be positive results
  7      in experimental animals when there is strong, consistent evidence that each mode of action in
  8      experimental animals does not operate in humans. The judgment may be based on
  9
10             •    animal evidence that demonstrates lack of carcinogenic effect in well-designed and
11                 well-conducted studies in at least two appropriate animal species (in the absence of
12                 other animal or human data suggesting a potential for cancer effects),
13
14             •    extensive experimental evidence showing that the only carcinogenic effects
15                 observed in animals are not relevant to humans,
16
17             •    convincing evidence that carcinogenic effects are not likely by a particular exposure
18                 route (see Section 2.3.3), or
19
20             •    convincing evidence that carcinogenic effects are not likely below a defined dose
21                 range.
22
23             A descriptor of "not likely" applies only to the circumstances supported by the data. For
24      example, an agent may be "not likely to be carcinogenic" by one route but not necessarily by
25      another.
26
27      Multiple Descriptors
28             As discussed previously, more than one descriptor can be used when an agent's effects
29      differ by dose or exposure route. For example, an agent may be "carcinogenic" by one exposure
30      route but "not likely to be carcinogenic" by a route by which it is not absorbed. Another
31      example is when an agent is "likely to be carcinogenic" above a specified dose but "not likely to
32      be carcinogenic" below that dose because a key event in tumor formation does not occur below
33      that dose.
34

        February 27, 2003                         2-43            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             Some examples show how a single positive study can lead to a wide range of descriptors,
  2      depending on the information provided by other studies: If there is only a single study and it is
  3      positive, a descriptor of "likely to be carcinogenic to humans" would generally be appropriate.
  4      If there are also some negative studies in another species ("differing results"), a descriptor of
  5      "suggestive evidence of carcinogenic potential" might be appropriate. If the negative studies are
  6      in the same test system as the positive study and are of equal quality ("conflicting evidence"),
  7      the descriptor "inadequate information to assess carcinogenic potential" could be used. If there
  8      are adequate negative studies in two  species and if there is sufficient evidence to determine that
  9      the tumors in the positive study are caused by a mode of action that is not relevant to humans,
10      the descriptor "not likely to be carcinogenic to humans" can be considered. In each case, the
11      descriptor is determined by the overall weight of evidence, taking into account all the studies.
12
13      2.7. HAZARD CHARACTERIZATION
14            The hazard characterization contains the hazard information needed for a full risk
15      characterization (U.S. EPA, 2000b).  It presents the results of the hazard assessment and explains
16      how the weight of evidence conclusion was reached. The hazard characterization summarizes, in
17      plain language, conclusions about the agent's potential effects, whether they can be expected to
18      depend qualitatively on the circumstances of exposure, and who can be expected to be especially
19      susceptible.  It  discusses the extent to which these conclusions are supported by data or are the
20      result of default options invoked because the data are inconclusive.  It explains how complex
21      cases with differing results in different studies were resolved.  The hazard characterization
22      highlights the major issues addressed in  the hazard assessment and discusses alternative
23      interpretations  of the data and the degree to which they are supportable scientifically and are
24      consistent with EPA guidelines.
25            When the conclusion is supported by mode of action information, the hazard
26      characterization also provides a clear summary of the mode of action conclusions (see
27      Section 2.5.3.4), including the completeness of the data, the strengths and limitations of the
28      inferences made, the potential for other modes of action, and the implications of the mode of
29      action for selecting viable approaches to the dose-response assessment.  The hazard
30      characterization also discusses the extent to which mode of action information is available to
31      address the potential for disproportionate risks in specific populations or lifestages or the
32      potential for enhanced risks on the basis of interactions with other agents or stressors.
33            Topics  that should be addressed in a hazard characterization include
34

        February 27, 2003                          2-44            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1             •     summary of the results of the hazard assessment;
 2
 3             •     identification of susceptible populations and lifestages, especially attending to
 4                  children, infants, and fetuses;
 5
 6             •     conclusions about the agent's mode of action and implications for selecting
 7                  approaches to the dose-response assessment;
 8
 9             •     identification of the available lines of evidence (animal bioassays, epidemiologic
10                  studies, toxicokinetic information, mode of action studies, and information about
11                  structural analogues or metabolites), highlighting data quality and coherence of
12                  results from different lines of evidence; and
13             •     strengths and limitations of the hazard assessment, highlighting significant issues in
14                  interpreting the data, alternative interpretations that are considered equally
15                  plausible, critical data gaps, and default options invoked when the available
16                  information is inconclusive.
        February 27,2003                          2-45            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1                               3. DOSE-RESPONSE ASSESSMENT
  2
  3             Dose-response assessment estimates potential risks to humans at exposure levels of
  4      interest. Dose-response assessments are useful in many applications: estimating risk at different
  5      exposure levels, estimating the risk reduction for different decision options, estimating the risk
  6      remaining after an action is taken, providing the risk information needed for benefit/cost
  7      analyses of different decision options, comparing risks across different agents or health effects,
  8      and setting research priorities. The purpose of the assessment should consider the quality of the
  9      data available, which will vary from case to case.
10             An analysis is developed from each study that reports quantitative data on dose and
11      response. Alternative measures of dose are available for analyzing human and animal studies
12      (see Section 3.1). A two-step approach distinguishes analysis of the dose-response data from
13      inferences made about lower doses. The first step is an analysis of dose and response in the
14      range of observation of the experimental and epidemiologic studies (see Section 3.2). Modeling
15      is encouraged to incorporate a wide range of experimental data into the dose-response
16      assessment (see Sections 3.1.2, 3.2.1, 3.2.2, 3.3.3).  The modeling yields a POD that marks the
17      boundary between the range of observation and the range of extrapolation to lower doses (see
18      Sections 3.2.4, 3.2.5). The second step is extrapolation to lower doses (see Section 3.3).  The
19      extrapolation approach considers what is known about the agent's mode of action (see
20      Section 3.3.1). Both linear and nonlinear approaches are available (see Sections 3.3.4, 3.3.3).
21      When multiple estimates can be developed, they are combined in a way that best represents
22      human  cancer risk (see Section 3.3.5). Special consideration is given to describing dose-
23      response differences attributable to different human exposure scenarios (see Section 3.4)  and to
24      susceptible populations and lifestages  (see Section 3.5). It is important to discuss significant
25      uncertainties encountered in the analysis (see Section 3.6) and to characterize other important
26      aspects of the  dose-response assessment (see Section 3.7).
27             The scope, depth, and use of a  dose-response assessment vary in different circumstances.
28      Although the quality of dose-response data is not necessarily related to the weight of evidence
29      descriptor, dose-response assessments are generally completed for human carcinogens and likely
30      human  carcinogens. When there is suggestive evidence, the Agency generally would not attempt
31      a dose-response assessment, as the nature of the data generally would not support one; however,
32      when the evidence includes a well-conducted study, quantitative analyses may be useful for
33      some purposes, for example, providing a sense of the magnitude and Uncertainty of potential
34      risks, ranking  potential hazards, or setting research priorities. In each case,  the rationale  for the

        February 27,2003                          3-1            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      quantitative analysis is explained, considering the uncertainty in the data and the suggestive
 2      nature of the weight of evidence. These analyses generally would not be considered Agency
 3      consensus estimates. Dose-response assessments are generally not done when there is
 4      inadequate evidence, although calculating a bounding estimate from a nonpositive epidemiologic
 5      study can indicate the study's level of sensitivity and capacity to detect risk levels of concern.
 6            Cancer is a collection of several diseases that develop through cell and tissue changes
 7      over time.  Dose-response assessment procedures based on tumor incidence have seldom taken
 8      into account the effects of key precursor events within the whole biological process due to lack
 9      of empirical data and understanding about these events. In this discussion, response data include
10      measures of key precursor events considered integral to the carcinogenic process in addition to
11      tumor incidence. These responses may include changes in DNA, chromosomes, or other key
12      macromolecules; effects on growth signal transduction, including induction of hormonal
13      changes; or physiological or toxic effects that include proliferative events diagnosed as
14      precancerous but not pathology that is judged to be cancer. Analysis of such responses may be
15      done along with that of tumor incidence to enhance the tumor dose-response analysis.  If dose-
16      response analysis of nontumor key events is more informative about the carcinogenic process for
17      an agent, it is used in lieu of, or in conjunction with, tumor incidence analysis for the overall
18      dose-response assessment.
19            As understanding of mode of action improves and new types of data become available,
20      dose-response assessment will continue to evolve. These guidelines encourage the development
21      and application of new methods that improve dose-response assessment by reflecting new
22      scientific understanding and new sources of information.
23
24      3.1. ANALYSIS OF DOSE
25            For each effect observed, dose-response assessment should begin by determining an
26      appropriate dose metric. The objective is to use the available data to estimate, as closely as
27      possible, the delivered dose of the active agent at the target organ or cell of the species studied.
28      When the delivered dose cannot be determined with confidence, dose-response assessment
29      proceeds with another dose metric,  for example, the average daily dose of the administered
30      agent.
31            Selection of an appropriate dose metric considers what data are available and what is
32      known about the agent's mode of action at the target site. The dose metric specifies
33
34            •    the active agent (administered agent or a metabolite),

        February 27, 2003                          3-2            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             •     proximity to the target site (exposure concentration, potential dose, internal dose, or
  2                   delivered dose,5 reflecting increasing proximity), and
  3
  4             •     the time component of the effective dose (cumulative dose, average dose, peak
  5                   dose, or body burden).
  6
  7             Analyses can be based on estimates of animal dose metrics or human dose metrics.  The
  8      assessment should describe the approach used to select a dose metric and the reasons for this
  9      approach.  The final analysis, however, should determine an equivalent human dose. This
10      facilitates comparing results  from different datasets and effects by using equivalent human dose
11      as a common metric. When appropriate, it may be necessary to convert doses across exposure
12      routes.
13             Timing of exposure can also be important. When there is a susceptible lifestage, doses
14      during the susceptible period are not equivalent to doses at other times, and they would be
15      analyzed separately.
16
17      3.1.1.  Standardizing Different Experimental Dosing Regimens
18             Complex dosing regimens are often present in experimental and epidemiologic studies.
19      The resulting internal dose depends on many variables, including concentration, duration,
20      frequency of administration,  and duration of recovery periods between administrations.  Internal
21      dose also depends on variables that are intrinsic to the exposed individual, such as lifestage and
22      rates of metabolism and clearance.  To facilitate comparing results from different study designs
23      and to make  inferences about human exposures, a summary estimate of dose may be derived for
24      a complex dosing regimen.
25             Toxicokinetic modeling is the preferred approach for estimating dose. Toxicokinetic
26      models generally consider a dose profile over time. More complex models can reflect sources of
27      intrinsic variation, such as polymorphisms in metabolism and clearance rates. When a robust
               5 Exposure is contact of an agent with the outer boundary of an organism. Exposure concentration is the
        concentration of a chemical in its transport or carrier medium at the point of contact. Dose is the amount of a
        substance available for interaction with metabolic processes or biologically significant receptors after crossing the
        outer boundary of an organism.  Potential dose is the amount ingested, inhaled, or applied to the skin. Applied dose
        is the amount of a substance presented to an absorption barrier and available for absorption (although not necessarily
        having yet crossed the outer boundary of the organism). Absorbed dose is the amount crossing a specific absorption
        barrier (e.g., the exchange boundaries of skin, lung, and digestive tract) through uptake processes. Internal dose is a
        more general term without respect to  specific absorption barriers or exchange boundaries. Delivered dose is the
        amount of the chemical available for  interaction by any particular organ or cell. (U.S. EPA, 1992a)

        February 27, 2003                            3-3            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      model is not available, or when the purpose of the assessment does not warrant developing a
  2      model, simpler approaches may be used.
  3             For chronic-dosing studies, the cumulative dose received should be expressed as an
  4      average over the duration of the study. This implies that a high dose received over a short
  5      duration at any period in life is equivalent to a commensurately lower dose spread over a
  6      lifetime. Uncertainty increases as the duration becomes shorter or the intermittent doses become
  7      more intense. Moreover, doses during a susceptible period are not equivalent to doses at other
  8      times.  For these reasons, cumulative dose may be replaced by a more appropriate dose metric
  9      when indicated by the data.
10             For mode of action studies, the daily dose should be calculated over a duration that
11      reflects the time to occurrence of the key precursor effects. Mode of action studies are often of
12      limited duration, as the precursors can be observed after less-than-chronic dosing. When the
13      experimental dosing regimen  is specified on a weekly basis (for example, 4 hours a day, 5 days a
14      week), the daily dose may be  averaged over the week.
15             Doses in studies at the cellular or molecular level can be difficult to relate to organ- or
16      organism-level dose metrics.  Toxicokinetic modeling can sometimes be used to relate doses at
17      the cellular or molecular level to doses at higher levels of organization.
18
19      3.1.2.  Toxicokinetic Modeling
20             Physiologically based toxicokinetic modeling is potentially the most comprehensive way
21      to account for biological processes that determine internal dose. Models are based on blood flow
22      between physiological compartments and simulate the relationship between applied dose and
23      internal dose. Toxicokinetic models generally need data on absorption, distribution, metabolism,
24      and elimination of the administered agent and its metabolites.
25             Additionally, in the case of inhaled dose, models can explicitly characterize the geometry
26      of the respiratory tract and the airflow through it, as well as the interaction of this airflow with
27      the entrained particles or fibers and gases (Kimbell et al., 2001; Subramaniam et al., 2003).
28      Because of large interspecies  differences in airway morphometry, such models  are particularly
29      useful in interspecies extrapolations. Nonetheless, because of large interindividual differences in
30      airway morphometry, particularly in humans, such models may not be representative of human
31      populations.
32             Toxicokinetic models can improve dose-response assessment by revealing and describing
33      nonlinear relationships between applied and internal dose. Nonlinearity observed in a dose-
34      response curve often can be attributed to toxicokinetics (Hoel et al., 1983; Gaylor et al., 1994),

        February 27, 2003                          3-4            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      involving, for example, saturation or induction of enzymatic processes at high doses.
  2      Toxicokinetic processes tend to become linear at low doses (Hattis, 1990).
  3            A discussion of confidence should accompany the presentation of model results and
  4      include consideration of model validation and sensitivity analysis, stressing the predictive
  5      performance of the model. Quantitative uncertainty analysis is important for evaluating the
  6      performance of a model.  The uncertainty analysis covers questions of model uncertainty (Is the
  7      model based on the  appropriate dose metrics?) and parameter uncertainty (Do the data support
  8      unbiased and stable estimates of the model parameters?). When a delivered dose measure is
  9      used in animal-to-human extrapolation, the assessment discusses the confidence of the target
10      tissue and its toxicodynamics being the same in both species (see Section 3.6).  Toxicokinetic
11      modeling results may be presented as the preferred method of estimating equivalent human doses
12      or in parallel with default procedures (see Section 3.1.3), depending on the confidence in the
13      modeling.
14
15      3.1.3.  Cross-species Scaling Procedures
16            Standard cross-species scaling procedures are available when the data are not sufficient
17      to support a toxicokinetic model or when the purpose of the assessment does  not warrant
18      developing one.  The aim is to define dose levels for humans and animals that are expected to
19      produce  the same degree of effect (U.S. EPA, 1992b), taking into account differences in scale
20      between test animals and humans in size and in lifespan.
21            For oral exposures, doses should be scaled from animals to humans on the basis of
22      equivalence of mg/kg3/4-d (milligrams of the agent normalized by the 3/4 power of body weight
23      per day) (U.S. EPA, 1992b). The 3/4 power is consistent with current science, including
24      empirical data that allow comparison of potencies in humans and animals, and it is also
25      supported by analysis of the allometric variation of key physiological parameters across
26      mammalian species. It is generally more appropriate at low doses, where sources of nonlinearity
27      such as saturation of enzyme activity are less likely to occur.  This scaling is  intended as an
28      unbiased estimate rather than a conservative one. Equating exposure concentrations in food or
29      water is  an alternative version of the same approach, because daily intakes of food or water are
30      approximately proportional to the 3/4 power of body weight.
31            The aim of these cross-species scaling procedures is to estimate administered doses in
32      animals  and humans that result in equal lifetime risks.  It is useful to recognize two components
33      of this equivalence:  toxicokinetic equivalence, which determines administered doses in animals
34      and humans that yield equal tissue doses, and toxicodynamic equivalence, which determines

        February 27, 2003                          3-5             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      tissue doses in animals and humans that yield equal lifetime risks (U.S. EPA, 1992b).
 2      Toxicokinetic modeling (see Section 3.1.2) addresses factors associated with toxicokinetic
 3      equivalence, and toxicodynamic modeling (see Section 3.2.2) addresses factors associated with
 4      toxicodynamic equivalence. When toxicokinetic modeling is used without toxicodynamic
 5      modeling, the dose-response assessment develops and supports an approach for addressing
 6      toxicodynamic equivalence, perhaps by retaining some of the cross-species scaling factor (e.g.,
 7      using the square root of the cross-speies scaling factor or using a factor of 3  to cover
 8      toxicodynamic differences between animals and humans, as is done in deriving inhalation
 9      reference concentrations (EPA 1994)).
10            When assessing risks from childhood exposure, the mg/kg3/4-d scaling factor does not use
11      the child's body weight (U.S. EPA, 1992b).  This reflects several uncertainties in extrapolating
12      risks to children:
13
14            •     The data supporting the mg/kg3/4-d scaling factor were derived  for differences
15                  across species and do not apply as well to differently sized individuals of the same
16                  species or to different lifestages.
17
18            •     Using the child's body weight in the mg/kg3/4-d scaling factor would erroneously
19                  imply that the child's intake, metabolism, and clearance are well described by such
20                  scaling.
21
22            •     In addition to metabolic differences, there are also important toxicodynamic
23                  differences; for example, children have faster rates of cell division than do adults.
24
25            For inhalation exposures, an equivalent human concentration should be calculated using
26      EPA's methods for deriving inhalation reference concentrations (U.S. EPA,  1994), which give
27      preference to the use of toxicokinetic modeling. Otherwise, mathematical dosimetry models of
28      particle or gas deposition in animals and humans are applied to yield a human-equivalent
29      concentration. As with oral exposures, when toxicokinetic modeling or dosimetry modeling is
30      used without toxicodynamic modeling, the dose-response assessment develops and supports an
31      approach for addressing toxicodynamic equivalence.
32            The dosimetry models typically use a default breathing rate and respiratory tract
33      dimensions for an  adult (U.S. EPA, 1994). Children and adults breathing the same concentration
34      of an agent (such as a reactive gas) may receive different doses to the body or lungs (U.S.

        February 27,2003                          3-6             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      EPA, 2002b). A generalized approach to assessing such differences between children and adults
  2      is a comparison of breathing rates relative to size of the body or lungs (U.S. EPA, 2002b). The
  3      human respiratory system passes through several distinct stages of maturation and growth during
  4      the first several years of life and into adolescence (Pinkerton and Joad, 2000) during which the
  5      ratio of breathing rate to lung surface area may be markedly different (U.S. EPA, 2002b). With
  6      certain assumptions, the models can be adapted by scaling breathing rates and respiratory tract
  7      dimensions for a child's size (U.S. EPA, 1994). This scaling should be undertaken with caution
  8      because of the correlations between breathing rate, respiratory tract dimensions, and body
  9      weight. Properly done, the comparison of human-equivalent concentrations for an adult and
10      child can indicate whether it is important to carry both concentrations forward in the dose-
11      response assessment or whether a verbal characterization of the difference between the two will
12      suffice.
13
14      3.1.4. Route Extrapolation
15             Often an assessment based on studies of one exposure route is applied to another
16      exposure  route.  Route-to-route extrapolation has both qualitative and quantitative aspects. For
17      the qualitative aspect, the assessor should weigh the degree to which positive results by one
18      exposure  route support a judgment that similar results would be expected by another route.  In
19      general, confidence in making such a judgment is strengthened when tumors are observed at a
20      site distant from the portal of entry and when absorption is similar through both routes.  In the
21      absence of contrary data, a qualitative default option can be used that if the agent is absorbed
22      through an exposure route to give an internal dose, it may be carcinogenic by that route.
23             When a qualitative extrapolation can be supported, quantitative extrapolation may still be
24      problematic in the absence of adequate data. The differences in biological processes among
25      routes of exposure (oral, inhalation, dermal) can be great because of, for example, first-pass
26      effects and different results from different exposure patterns. There is no generally applicable
27      method for accounting for these differences in uptake processes in a quantitative route-to-route
28      extrapolation of dose-response data in the absence of good data on the agent of interest.
29      Therefore, route-to-route extrapolation of dose data relies on a case-by-case analysis of available
30      data. When good data on the agent itself are limited,  an extrapolation analysis  can be based on
31      expectations from physical and chemical properties of the agent, properties and route-specific
32      data on structurally analogous compounds, or in vitro or in vivo uptake data on the  agent.
33             Route-to-route uptake models may be applied if model parameters are suitable for the
34      compound of interest. Such models are currently considered interim methods;  further model

        February  27, 2003                           3-7             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      development and validation is awaiting the development of more extensive data. For screening
  2      or hazard ranking, route-to-route extrapolation may be based on assumed quantitative
  3      comparability as a default, as long as it is reasonable to assume absorption by compared routes.
  4      When route-to-route extrapolation is used, the assessor's degree of confidence in both the
  5      qualitative and quantitative extrapolation is discussed in the assessment and highlighted in the
  6      dose-response characterization.
  7            Toxicokinetic modeling can be used to compare results of studies by different exposure
  8      routes. Results can also be compared on the basis of internal dose for effects distant from the
  9      point of contact.
10            Route extrapolation can be used to understand how internal dose and subsequent effects
11      depend on exposure route.  Route extrapolation can also determine whether testing by different
12      exposure routes has achieved similar internal doses, which can be important in determining
13      whether testing is adequate to conclude that an agent causes effects by one route but not by
14      another.
15
16      3.2. ANALYSIS IN THE  RANGE OF OBSERVATION
17            The principle underlying these guidelines is to use approaches that include as much
18      information as possible. Quantitative information about key precursor events can be used to
19      develop a toxicodynamic model. Alternatively, such information can be fitted by empirical
20      models to extend the dose-response analysis of tumor incidence to lower doses and response
21      levels. The analysis in the range of observation is used to establish a POD that marks the
22      boundary between the range of observation and the range of extrapolation to lower doses (see
23      Section 3.3).
24
25      3.2.1.  Analysis of Epidemiologic Studies
26            Analysis of epidemiologic studies depends on the type of study and quality of data,
27      particularly the availability of quantitative measures of exposure. The objective is a dose-
28      response curve that estimates the incidence of cancer attributable to exposure to the agent. In
29      some cases, estimation of the number of cancer cases expected in a population (sometimes called
30      "population risk") may be appropriate.  Also in some cases, the agent can have discernible
31      interactive effects with another agent, making it possible to estimate the contribution of each
32      agent as a risk factor for the effects of the other. The analysis is tailored to the nature of each
33      study, with due consideration of the consequences of study design.  For example:
34

        February 27, 2003                          3-8            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             •     Many studies collect information from death certificates, which leads to estimates
  2                  of mortality rather than incidence.  Because survival rates vary for different
  3                  cancers, the analysis can be improved by adjusting mortality figures to reflect the
  4                  relationship between incidence and mortality.
  5
  6             •     Competing risks in a study population can limit the observed occurrence of cancer.
  7                  The analysis can be improved by correcting for competing risks that are not similar
  8                  in exposed and comparison groups.
  9
10             •     Comparison groups that are not free from exposure to the agent can bias the risk
11                  estimates toward zero. The analysis can be improved by considering background
12                  exposures in the exposed and comparison groups.
13
14             Some study designs can yield only a partial characterization of the overall risk, as, for
15      example, in studies that
16
17             •     investigate only one effect (typical of many case-control studies),
18             •     include only one population segment (e.g., male workers), or
19             •     include only one lifestage (e.g., childhood leukemia following maternal exposure to
20                  contaminated drinking water).
21
22      To obtain a fuller characterization that includes risks of other cancers, estimates from these
23      studies can be supplemented with estimates from other studies that investigated other cancers,
24      population segments, or lifestages (see  Section 3.3.5).
25             The latent period for cancer implies that  exposures immediately preceding the detection
26      of a tumor would be less likely to have contributed to its development and, therefore, may count
27      less in the analysis. Study subjects who were first exposed near the end of the study would not
28      have had adequate time since exposure for cancer to develop, therefore, analysis of their data
29      may be similar to analysis of data for those who were not exposed.
30             For epidemiologic studies, analysis by linear models in the range of observation should
31      be used unless the fit is poor. This is justified by the relatively small dose range observed in
32      many epidemiologic studies, which makes it difficult to discern the shape of the dose-response
33      curve.  Exposure misclassification and errors in  exposure estimation also obscure the shape of
34      the dose-response curve. When these errors are  unsystematic, or random, the result is to bias the

        February 27, 2003                          3-9             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      risk estimates toward zero. When a linear model fits poorly, more flexible models that allow for
  2      low-dose linearity, for example, a linear-quadratic model or a Hill model (Murrell et al 1998),
  3      are considered next.
  4            When several studies are available for dose-response analysis, meta-analysis can provide
  5      a systematic approach to weighing positive and nonpositive studies and calculating an overall
  6      risk estimate with greater precision. Issues considered include the comparability of studies,
  7      heterogeneity across studies, and the potential for a single large study to dominate the analysis.
  8      Confidence in a meta-analysis is increased when it considers study quality, including definition
  9      of the study population and comparison group, measurement of exposure, potential for exposure
10      misclassification, adequacy of follow-up period, and analysis of confounders (see Section
11      2.2.1.2).
12
13      3.2.2. Toxicodynamic ("Biologically Based") Modeling
14            Toxicodynamic modeling can be used when there are sufficient data to ascertain the
15      mode of action (see Section 2.5) and quantitatively support model parameters that represent rates
16      and other quantities associated with the key precursor events of the mode of action.
17      Toxicodynamic modeling is potentially the most comprehensive way to account for the
18      biological processes involved in a response.  Models reflect the sequence of key precursor events
19      that lead to cancer. Toxicodynamic models can improve dose-response assessment by revealing
20      and describing nonlinear relationships between internal dose and cancer response. Such models
21      are generally the better approach for analysis in the range of observation, provided the purpose
22      of the assessment justifies the effort involved.
23            If a new model is developed for a specific agent, extensive data on the agent are
24      important for identifying the form of the model, estimating its parameters, and building
25      confidence in its results. Conformance to the observed tumor incidence data does not establish a
26      model's predictive validity, as a model can be overparameterized to fit a given dataset. Peer
27      review, including both an examination of the scientific basis supporting the model and an
28      independent evaluation of the model's performance, is an essential part of evaluating the new
29      model.
30            If a standard model already exists for the agent's mode of action, the model can be
31      adapted for the agent by using agent-specific data to estimate the  model's parameters. An
32      example is the two-stage clonal expansion model developed by Moolgavkar and Knudson (1981)
33      and Chen and Farland (1991). These models continue to be improved upon.
        February 27, 2003                         3-10            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             It is possible for different models to provide equivalent fits to the observed data but to
  2      diverge substantially in their projections at lower doses. When model parameters are estimated
  3      from tumor incidence data, it is often the case that different combinations of parameter estimates
  4      can yield similar results in the observed range. For this reason, critical parameters (e.g.,
  5      mutation rates and cell birth and death rates) are estimated from laboratory studies and not by
  6      curve-fitting to tumor incidence data (Portier, 1987). This approach reduces model uncertainty
  7      (see Section 3.6) and ensures that the model does not give answers that are biologically
  8      unrealistic. This approach also provides a robustness of results, where the results are not likely
  9      to change substantially if fitted to slightly different data.
10             Toxicodynamic modeling can provide insight into the relationship between tumors and
11      key precursor events. For example, a model that includes cell proliferation can be used to
12      explore the extent to which small increases in the cell proliferation rate can lead to large lifetime
13      tumor incidences (Gaylor and Zheng, 1996).  In this way, toxicodynamic modeling can be used
14      to select and characterize an appropriate precursor response level (see Section 3.2.4,  3.2.5).
15
16      3.2.3. Empirical Modeling ("Curve Fitting")
17             When a toxicodynamic model is not available or when the purpose of the assessment
18      does not warrant developing such a model, empirical modeling (sometimes called "curve
19      fitting") should be used in the range of observation. A model can be fitted to data on either
20      tumor incidence or a key precursor event. Goodness-of-fit to the experimental observations is
21      not by itself an effective means of discriminating among models that adequately fit the data
22      (OSTP, 1985). Quantitative data on precursors can be used in conjunction with, or in lieu of,
23      data on tumor incidence to extend the dose-response curve to lower doses. Caution is used with
24      rates of molecular events such as mutation or cell proliferation or signal transduction. Such rates
25      can be difficult to relate to cell or tissue changes overall.  The timing of observations of these
26      phenomena, as well as the cell type involved, need to be linked to other precursor events to
27      ensure that the measurement is truly a key event (see Section 2.5).
28             For incidence data on either tumors or a precursor, an established empirical procedure
29      should be used to provide objectivity and consistency among assessments. The procedure
30      models incidence, corrected for background, as an increasing function of dose. The model is
31      sufficiently flexible in the observed range to fit linear and nonlinear datasets.  Additional
32      judgment and perhaps an alternative analysis are used when the procedure fails to yield reliable
33      results. For example, when the model fit is poor, the highest dose is often omitted in cases where
34      it is judged that the highest dose reflects competing toxicity that is more relevant at high doses

        February 27, 2003                          3-11           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      than at lower doses.  Another example is when there are large differences in survival across dose
  2      groups; here, a more detailed model that includes time-to-tumor or time-to-event information
  3      may be useful.
  4            For continuous data on key precursor effects, an empirical model can be chosen on the
  5      basis of the structure of the data. The rationale for the choice of model, the alternatives
  6      considered and rejected, and a discussion of model uncertainty are included in the dose-response
  7      characterization.
  8
  9      3.2.4. Point of Departure
10            For each tumor response, a POD from the observed data should be estimated to mark the
11      beginning of extrapolation to lower doses.  The POD is an estimated dose (expressed in human-
12      equivalent terms) near the lower end of the observed range without significant extrapolation to
13      lower doses.
14            The POD is used as the starting point for subsequent extrapolations and analyses.  For
15      linear extrapolation, the POD is used to calculate a slope factor (see Section 3.3.4), and for
16      nonlinear extrapolation the POD is used to calculate a reference dose or reference concentration
17      (see Section 3.3.3). In a risk characterization, the POD is part of the determination of a margin of
18      exposure (see  Section 5.4). With appropriate adjustments, it can also be used as the basis for
19      hazard rankings that compare different agents or health effects.
20            The goal is to use the lowest POD that is adequately supported by the data.  If the POD is
21      above some data points, it can fail to reflect the shape of the dose-response curve at the lowest
22      doses and can introduce bias into subsequent extrapolations (see Figure 3-1). On the other hand,
23      if the POD is far below all observed data points, it can introduce model uncertainty and
24      parameter uncertainty (see Section 3.6) that increase with the distance  between the data and the
25      POD. Use of a POD at the lowest level supported by the data seeks to balance these
26      considerations. It uses information from the model a small distance below the observed range
27      rather than discarding this information and invoking default extrapolation procedures in a range
28      where the model can provide some useful information.  Statistical tests involving the ratio of the
29      central estimate and its lower bound (i.e., EDXX/LEDXX) can be useful for evaluating how well the
30      data support model estimates at a particular response level. (Note that the ability to model at a
31      particular response level is not the same as the study's ability to identify an increase at that
32      response level as statistically significant.)
33            For applications that involve extrapolation, Agency practice has been to use a lower
34      bound as the POD. This reflects the Agency's appraisal of the relative consequences of

        February 27,2003                          3-12             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1      overestimating or underestimating the POD. It also ensures that the POD considers the variance
  2      of the estimated dose, which can depend on a study's design, sample size, and quality.  For
  3      applications that do not involve extrapolation (e.g., hazard rankings), Agency practice has been
  4      to use a central estimate as the POD. In either case, both the central estimate and its lower
  5      bound are presented to convey a sense of the uncertainty in the POD.
  6            When tumor data are used, a POD is obtained from the modeled tumor incidences.
  7      Conventional cancer bioassays, with approximately 50 animals per group, generally can support
  8      modeling down to an increased incidence of 1-10%; epidemiologic studies, with larger sample
  9      sizes, below 1%.  Various models commonly used for carcinogens yield similar estimates of the
10      POD at response levels as low as 1% (Krewski and Van Ryzin, 1981; Gaylor et al., 1994).
11      Consequently, response levels below 10% can often be used as the POD. As a modeling
12      convention, the lower bound on the doses associated with standard response levels of 1, 5, and
13      10% can be analyzed, presented, and considered. For making comparisons at doses within the
14      observed range, the EDIO and LEDIO are also reported as a common POD that can be used, with
15      appropriate adjustments, in hazard rankings that compare different agents or health effects (U.S.
16      EPA,2002c).
17            When precursor data are available and of good quality, models that include both tumors
18      and their precursors are generally most useful for deriving a POD. Such models can provide
19      insight into quantitative relationships between tumors and precursors (see Section 3.2.2),
20      possibly  suggesting the precursor response level that is associated with a particular tumor
21      response level. The goal is to use precursor data to extend the observed range below what can be
22      observed in tumor studies.  If the precursor data are drawn from small samples or if the
23      quantitative relationship between tumors and precursors is not well defined, then the tumor data
24      may provide a more reliable POD. Precursor effects may or may not be biologically adverse in
25      themselves; the intent is to consider not only tumors but also damage that can lead to subsequent
26      tumor development by this or another agent. Special attention  is needed when analyzing
27      continuous precursor data; Murrell et al. (1998) discuss alternative approaches to deriving a
28      POD from  continuous data. A no-observed-adverse-effect level generally is not used for
29      assessing the potential for carcinogenic response when a model can be fitted to the data.
30
31      3.2.5. Characterizing the POD: the POD Narrative
32            As a single-point summary of a single dose-response curve, the POD alone does not
33      convey all the critical information present in the data from which it is derived.  To convey a
34      measure  of uncertainty, the POD should be presented as a central estimate with upper and lower

        February 27,2003                         3-13           DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1      confidence bounds. A POD narrative summarizes other important features of the database and
 2      the POD that are important to account for in low-dose extrapolations or other analyses.
 3            (a) Nature of the response.  Is the POD based on tumors or a precursor?  If on tumors,
 4  .    does the POD measure incidence or mortality? Is it a lifetime measure or was the study
 5      terminated early? The relationships between precursors and tumors, incidence and mortality,
 6      and lifetime and early-termination results vary from case to case. Modeling can provide
 7      quantitative insight into these relationships, for example, linking a change in a precursor
 8      response to a tumor incidence (see Section 3.2.2). This can aid in evaluating the significance of
 9      the response at the POD and adjusting different PODs to make them comparable.
10            (b) Level of the response. What level of response is associated with the POD, for
11      example,  1% cancer risk, 10% cancer risk, or 10% change in a precursor measure?
12            (c) Nature of the study population.  Is the POD based on humans or animals?  How large
13      is the effective sample size?  Is the study group representative of the general population, of
14      healthy adult workers, or of a susceptible group?  Are both sexes represented? Did exposure
15      occur during a susceptible lifestage?
16            (d) Slope of the dose-response curve at the POD.  How does response change as dose is
17      reduced below the POD? A steep slope indicates that risk decreases rapidly as dose decreases.
18      On the other hand, a steep slope also indicates that errors in an exposure assessment can lead to
19      large errors in estimating risk. Both aspects of the slope are important.  The slope also indicates
20      whether dose-response curves for different effects are likely to cross below the POD. For
21      example, in the ED01  study where 2-acetylaminofluorene caused bladder carcinomas and liver
22      carcinomas in mice (Littlefield et al., 1980), the dose-response curves for these tumors cross
23      between 10% and 1% response (see Figure 3-2).  This crossing, which can be inferred from the
24      slopes of the curves at a  10% response, shows how considering the slope can  lead to better
25      inferences about the predominant effects expected at lower doses.  Mode of action data can also
26      be useful; quantitative information about key precursor events can be used to  describe how risk
27      decreases as dose decreases below the POD.
28            (e) Relationship of the POD with other cancers. How does the POD  for this cancer
29      relate to PODs for other cancers observed in the database? For example, a POD based on male
30      workers would not reflect the implications of mammary tumors  in female rats or mice.
31            (f) Extent of the overall cancer database.  Have potential cancer responses been
32      adequately studied (e.g., were all tissues examined), or is the database limited to particular
33      effects, population segments, or lifestages? Do the mode of action data suggest a potential for
       February 27,2003                         3-14           DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1      cancers not observed in the database (e.g., disruption of particular endocrine pathways leading to
 2      related cancers)?
 3
 4      3.2.6. Relative Potency Factors
 5            Relative potency factors can be used for a well-defined class of agents that operate
 6      through a common mode of action. A complete dose-response assessment is conducted for one
 7      well-studied member of the class that serves as the index chemical for the class. The other
 8      members of the class are tied to the index chemical by relative potency factors that are based on
 9      characteristics such as relative toxicological outcomes, relative metabolic rates, relative
10      absorption rates, quantitative SARs, or receptor binding characteristics (U.S. EPA, 2000c).
11      Examples of this approach are the toxicity equivalence factors for dioxin-like compounds and the
12      relative potency factors for some carcinogenic polycyclic aromatic hydrocarbons.
13
14      3.3. EXTRAPOLATION TO LOWER DOSES
15            The purpose of low-dose extrapolation is to provide as much information as possible
16      about risk in the range of doses below the observed data.  The most versatile form of low-dose
17      extrapolation is a dose-response model that characterizes risk as a probability over a range of
18      environmental exposure levels.  These risk probabilities allow estimates of the risk reduction
19      under different decision options and estimates of the risk remaining after an action is taken and
20      provide the risk information needed for benefit/cost analyses of different decision  options.
21            When a dose-response model is not developed for lower doses, another form of low-dose
22      extrapolation is a safety assessment that characterizes the safety of one lower dose, with no
23      explicit characterization of risks above or below that dose. Although this type of extrapolation
24      may be adequate for evaluating different decision options, it may not be adequate for other
25      purposes (e.g., benefit/cost analyses) that require a quantitative characterization of risks across a
26      range of doses. At this time, safety assessment is the default approach for tumors that arise
27      through a nonlinear mode of action; however, EPA continues to explore methods for quantifying
28      dose-response relationships over a range of environmental exposure levels for tumors that arise
29      through a nonlinear mode of action (U.S. EPA, 2002c). EPA program offices that need this more
30      explicit dose-response information may develop and apply methods that are informed by the
31      methods described in these guidelines.
32
33      3.3.1. Choosing an Extrapolation Approach
        February 27,2003                         3-15            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1             The approach for extrapolation below the observed data considers the understanding of
  2      the agent's mode of action at each site (see Section 2.5). Mode of action data can suggest the
  3      likely shape of the dose-response curve at lower doses. The extent of inter-individual variation
  4      is also considered, with greater variation spreading the response over a wider range of doses.
  5             Linear extrapolation should be used when there are data to indicate that the dose-
  6      response curve has a linear component below the POD, as when
  7
  8             •    the agent is  DNA-reactive and has direct mutagenic activity or the agent operates
  9                 through another mode of action that is expected to be linear at low doses, or
10
11             •    human exposure or body burden is high and near doses associated with key
12                 precursor events in the carcinogenic process, so that background exposures to this
13                 and other agents operating through a common mode of action are in the increasing,
14                 approximately linear, portion of the dose-response curve.
15
16             Linear extrapolation can also be used as a default approach when the available data fall
17      short of establishing the mode of action at a tumor site, because linear extrapolation generally is
18      considered to be a health-protective approach for addressing uncertainty about the mode of
19      action.
20             A nonlinear approach should be selected when there are sufficient data to ascertain the
21      mode of action and conclude that it is not linear at low doses and the agent does not demonstrate
22      mutagenic or other activity consistent with linearity at low doses. Special attention is needed
23      when the data support a nonlinear mode of action but there is also a suggestion of mutagenicity
24      (either the evidence of mutagenicity is weak, or the mutagenic effect is weak, or mutagenicity is
25      expected only at high doses).  Depending on the strength of the  suggestion of mutagenicity, the
26      assessment may justify a  conclusion that mutagenicity is not operative at low doses and focus on
27      a nonlinear approach, or alternatively, the assessment may use both linear and nonlinear
28      approaches.
29             Both linear and nonlinear approaches may be used when there are multiple modes of
30      action:
31
32             •    If there are multiple tumor sites, one with a linear and another with a nonlinear
33                 mode of action, then the corresponding approach is used at each site.
34

        February 27,2003                         3-16             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1            •    If there are multiple modes of action at a single rumor site, one linear and another
 2                 nonlinear, then both approaches are used to decouple and consider the respective
 3                 contributions of each mode of action in different dose ranges. For example, an
 4                 agent can act predominantly through cytotoxicity at high doses and through
 5                 mutagenicity at lower doses where cytotoxicity does not occur.  Modeling to a low
 6                 response level can be useful for estimating the response at doses where the high-
 7                 dose mode of action would be less important.
 8
 9      Nonlinear approaches generally should not be used in cases where the mode of action has not
10      been ascertained.
11
12      3.3.2.  Extrapolation Using a Toxicodynamic Model
13            The better approach is to develop a toxicodynamic model of the agent's mode of action
14      and use that model for extrapolation to lower doses (see Section 3.2.2). The extent of
15      extrapolation is governed by an analysis of model uncertainty, where alternative models that fit
16      similarly in the observed range can diverge below that range (see Section 3.6).  Substantial
17      divergence is likely when model parameters  are estimated from tumor incidence data, so that
18      different combinations of parameter estimates yield similar fits in the observed range but have
19      different implications at lower doses.  An analysis of model uncertainty can be used to determine
20      the range where extrapolation using the toxicodynamic model is supported and where further
21      extrapolation would be based on either a linear or a nonlinear default, as appropriate (see
22      Sections 3.3.4, 3.3.3).
23
24      3.3.3.  Nonlinear Extrapolation to Lower Doses
25            A nonlinear default can be used for cases with sufficient data to ascertain the mode of
26      action and conclude that it is not linear at low doses but not enough data to support a
27      toxicodynamic model at low doses. Currently, nonlinear default approaches do not estimate risk
28      probabilities or provide a dose-response curve at low doses, because there is considerable model
29      uncertainty (see Section 3.6) inherent in the extrapolation of nonlinear models: different
30      nonlinear models that fit the observed data can lead to a wide range of results at lower doses,
31      with no basis to choose among them.  EPA is continuing to explore methods for quantifying
32      dose-response relationships over a range of environmental exposure levels for tumors that arise
33      through a nonlinear mode of action.
        February 27,2003                         3-17            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1            For cases where the tumors arise through a nonlinear mode of action, an oral reference
  2      dose or an inhalation reference concentration, or both, should be developed in accordance with
  3      EPA's established practice for developing such values, taking into consideration the factors
  4      summarized in the characterization of the POD (see Section 3.2.5).  This approach expands the
  5      past focus of such reference values (previously reserved for effects other than cancer) to include
  6      carcinogenic effects determined to have a nonlinear mode of action.  As with other health effects
  7      of concern, it is important to put cancer in perspective with the overall health impact of an
  8      exposure by comparing reference value calculations for cancer with those for other health
  9      effects.
10            For effects other than cancer, reference values have been described as being based on the
11      assumption of biological thresholds. The Agency's more current guidelines for these effects,
12      however, do not use this assumption, citing the difficulty of empirically distinguishing a true
13      threshold from a dose-response curve that is nonlinear at low doses (U.S. EPA, 1998b,1996a).
14            Economic and policy analysts need to know how the probability of cancer varies at
15      exposures above the reference dose and whether, and to what extent, there are health benefits
16      from reducing exposures below the reference dose. The risk assessment community is working
17      to develop better methods to provide more useful information to economic and policy analysts.
18
19      3.3.4.  Extrapolation Using a Low-dose Linear Model
20            Linear extrapolation should be used in two distinct circumstances: (1) when there are
21      data to indicate that the dose-response curve has a linear component below the POD, or (2) as a
22      default for a tumor site where the mode of action is not established (see Section 3.3.1).  For
23      linear extrapolation, a line should be drawn from the POD to the origin, corrected for
24      background.  This implies a proportional (linear) relationship between risk and dose at low
25      doses. (Note that the dose-response curve generally is not linear at higher doses.)
26            The slope of this line, known as the slope factor, is an upper-bound estimate of risk per
27      increment of dose that can be used to estimate risk probabilities for different exposure levels.
28      The slope factor is equal to 0.01/LED01 if the LED01 is used as the POD.
29            Unit risk estimates express the slope in terms of |ig/L drinking water or ng/m3 air. In
30      general, the drinking water unit risk is derived by converting a slope factor from units of
31      mg/kg-d to units of \igfL, whereas an inhalation unit risk is developed directly from a dose-
32      response analysis using equivalent human concentrations already expressed in units of ng/m3.
33      Unit risk estimates often assume a standard intake rate (L/day drinking water or mVday air) and
34      body weight (kg), which may need to be reconciled with the exposure factors for the population

        February 27,2003                          3-18            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1      of interest in an exposure assessment (see Section 4.4). Although unit risks have not been
 2      calculated in the past for dermal exposures, both exposures that are absorbed into the systemic
 3      circulation and those that remain in contact with the skin are also important.
 4            Risk-specific doses are derived from the slope factor or unit risk to estimate the dose
 5      associated with a specific risk level, for example, a one-in-a-million increased lifetime risk.
 6
 7      3.3.5.  Comparing and Combining Multiple Extrapolations
 8            When multiple estimates can be developed, all datasets should be considered and a
 9      judgment made about how best to represent the human cancer risk. Some options for presenting
10      results include
11
12            •    adding risk estimates derived from different tumor sites (NRC, 1994),
13
14            •    combining data from different datasets in a joint analysis (Stiteler et al., 1993; Vater
15                 etal., 1993),
16
17            •    combining responses that operate through a common mode of action,
18
19            •    representing the overall response in each experiment by counting animals with any
20                 tumor showing a statistically significant increase,
21
22            •    presenting a range of results from multiple datasets (in this case, the dose-response
23                 assessment includes guidance on how to choose an appropriate value from the
24                 range),
25
26            •    choosing a single dataset if it can be justified as most representative of the overall
27                 response in humans, or
28
29            •    a combination of these options.
30
31            Cross-comparison of estimates from human and animal studies can provide a valuable
32      risk perspective:
33
       February 27,2003                         3-19            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1            •    Calculating an animal-derived slope factor and using it to estimate the risk expected
  2                 in a human study can provide information about the human study design, for
  3                 example, adequacy of exposure level and sample size.
  4
  5            •    Calculating an upper-bound slope factor from a nonpositive human study with good
  6                 exposure information and comparing it to an animal-derived slope factor can
  7                 indicate whether the positive animal and nonpositive humans studies are consistent.
  8
  9      3.4. EXTRAPOLATION TO DIFFERENT HUMAN EXPOSURE SCENARIOS
10            Often, an assessment based on human or animal studies of long-term, constant exposure
11      is applied to different human exposure scenarios, for example, less-than-lifetime durations or
12      intermittent patterns of exposure. The dose-response assessment provides recommendations to
13      exposure assessors who will evaluate such scenarios.  In developing these recommendations,
14      tumor studies involving less-than-lifetime dosing or follow-up are often not informative, as these
15      studies can be limited by inadequate power or insufficient allowance for latency.
16            For lifetime human exposure scenarios that involve intermittent or varying levels of
17      exposure, the prevailing practice has been to assess exposure by calculating a lifetime average
18      daily dose (U.S. EPA, 1992a). This approach assumes that an intermittent exposure scenario is
19      equivalent to constant lifetime exposure at the average level, which matches the dosing regimen
20      used in conventional cancer bioassays.
21            For less-than-lifetime human exposure scenarios, too, the lifetime average daily dose has
22      been used. This implies that less-than-lifetime exposure is associated with a proportional
23      reduction of the lifetime risk, regardless of when exposures occur. The appeal of this default lies
24      in its simplicity and its appearance of being risk neutral with regard to timing of exposure. It is
25      not, however, compatible with current dose-response models of carcinogenesis: both the
26      multistage model and the  two-stage clonal expansion model predict that short-duration risks are
27      not necessarily  proportional to exposure duration and can depend on the nature of the carcinogen
28      and the timing of exposure (Goddard et al., 1995).  In some circumstances, use of a lifetime
29      average daily dose would underestimate cancer risk by two- to fivefold (Murdoch et al., 1992).
30      Consistent with these theoretical results, an empirical comparison of results from parallel chronic
31      and stop-exposure studies conducted by NTP suggests that use of the lifetime average daily dose
32      is more likely to lead to an underestimate than an overestimate of risk (Halmes et al., 2000).  As
33      methodological research focuses on new approaches for estimating risks from less-than-lifetime
34      exposures, methods and defaults can be expected to change.

        February 27, 2003                         3-20           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             This highlights the importance for each dose-response assessment to critically evaluate
  2      all information pertaining to less-than-lifetime exposure. For example, detailed stop-exposure
  3      studies can provide information about the relationship between exposure duration, precursor
  4      effects, potential for reversibility, and tumor development.  Toxicokinetic modeling can
  5      investigate differences in internal dose between short-term and long-term exposure or between
  6      intermittent and constant exposure.  Persistence in the body can be useful in explaining long-
  7      term effects resulting from shorter-term exposures.
  8             The use of lifetime average daily dose described above was adopted with low-dose linear
  9      cancer assessments in mind. For nonlinear cancer analyses, it is appropriate to assess exposure
10      by calculating a daily dose that is not averaged over a lifetime (see Section 3.1.1).  This reflects
11      an expectation that the precursor effects on which the analysis is based can result from less-than-
12      lifetime exposure, bringing consistency to the methods used for dose-response assessment and
13      exposure assessment in such cases.  The dose-response assessment provides a recommendation
14      to exposure assessors about the averaging time that is appropriate to the mode of action.
15
16      3.5. EXTRAPOLATION TO SUSCEPTIBLE POPULATIONS AND LIFESTAGES
17             The dose-response assessment strives to derive separate estimates for susceptible
18      populations and lifestages so that these risks can be explicitly characterized.  For a susceptible
19      population, higher risks can be expected from exposures anytime during life, but this applies to
20      only a portion of the general population (e.g.,  those bearing a particular genetic susceptibility).
21      In contrast, for a susceptible lifestage, higher risks can be expected from exposures during only  a
22      portion of a lifetime, but this applies to the entire population. Exposures during a susceptible
23      period are not equivalent to exposures at other times;  consequently, it is useful to estimate the
24      risk attributable to exposures during each period.
25             Depending on the data available, a tiered approach should be used to address susceptible
26      populations and lifestages.
27
28             1.   When there is an epidemiologic study or an animal bioassay that reports
29                 quantitative results for susceptible individuals, the data should be analyzed to
30                 provide a separate risk estimate for those who are susceptible.  If susceptibility
31                 pertains to a lifestage, it is useful to characterize the portion of the lifetime risk that
32                 can be attributed to the susceptible lifestage.
33
        February 27,2003                          3-21            DRAFT FINAL -DO NOT CITE OR QUOTE

-------
 1            2.   When there are data on some risk-related parameters that allow comparison of the
 2                 general population and susceptible individuals, the data should be analyzed with an
 3                 eye toward adjusting the general population estimate for susceptible individuals.
 4                 This analysis can range from toxicokinetic modeling that uses parameter values
 5                 representative of susceptible individuals to more simply adjusting a general
 6                 population estimate to reflect differences in important rate-governing parameters.
 7                 Care is taken to not make parameter adjustments in isolation, as the appropriate
 8                 adjustment can depend on the interactions of several parameters; for example, the
 9              •   ratio of metabolic activation and clearance rates can be more appropriate than the
10                 activation rate alone (U.S. EPA, 1992b).
11
12            3.   In the absence of such agent-specific data, there is some general information to
13                 indicate that childhood can be a susceptible lifestage for exposure to some
14                 carcinogens (EPA 2003); this warrants explicit consideration in each assessment.
15                 The potential for susceptibility  from early-life exposure is expected to vary among
16                 specific agents and chemical classes. In addition, the concern that dose-averaging
17                 generally used for assessing less-than-lifetime exposure is more likely to understate
18                 than overstate risk (Halmes et al., 2000, see also Section 3.4) contributes to the
19                 suggestion that alternative approaches be considered for assessing risks from less-
20                 than-lifetime exposure that occurs during childhood. Accompanying these
21                 guidelines is supplemental guidance that the Agency will use to assess risks from
22                 early-life exposure to potential  carcinogens (U.S. EPA, 2003). [This draft
23                 Supplemental Guidance presents, at this time, a possible approach for
24                 assessing cancer susceptibility from early-life exposure to carcinogens. The
25                 final guidance will reflect public comment and recommendations from the
26                 Science Advisory Board's review of the Supplemental Guidance.] The
27                 supplemental guidance may be  updated to reflect new data and new understanding
28                 that may become available in the future.
29
30      3.6. UNCERTAINTY
31            The NRC (1983, 1994, 1996, 2002) has repeatedly advised that proper characterization of
32      uncertainty is essential in risk assessment. An assessment that omits or underestimates
33      uncertainty can leave decision-makers with a false sense of confidence in estimates of risk. On
34      the other hand, a high level of uncertainty does not imply that a risk assessment or a risk

        February 27, 2003                         3-22            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      management action should be delayed (NRC, 2002).  Uncertainty in dose-response assessment
 2      can be classified as either model uncertainty or parameter uncertainty. A related concept is
 3      human variation, discussed below. Assessments should discuss the significant uncertainties
 4      encountered in the analysis, distinguishing, if possible, between model uncertainty, parameter
 5      uncertainty, and human variation.
 6            Model uncertainty refers to a lack of knowledge needed to determine which scientific
 7      theory a model is based upon is correct.  In risk assessment, model uncertainty is reflected in
 8      alternative choices for model structure, dose metrics, and extrapolation approaches.  Other
 9      sources of model uncertainty concern whether surrogate data are appropriate, for example, using
10      data on adults to make inferences about children.  The full extent of model uncertainty cannot be
11      quantified; a partial characterization can  be obtained by comparing the results of alternative
12      models. Model uncertainty is expressed  through comparison of separate analyses from each
13      model, coupled with a subjective probability statement, where feasible and appropriate, of the
14      likelihood that each model might be correct (NRC, 1994).
15            Some aspects of model uncertainty that should be addressed in an assessment include the
16      use of animal models  as a surrogate for humans, the influence of cross-species differences in
17      metabolism and physiology, the use of effects observed at high doses  as an indicator of the
18      potential for effects at lower doses, the effect of using linear or nonlinear extrapolation to
19      estimate risks, the use of using small samples and subgroups to make  inferences about entire
20      human populations or subpopulations with differential susceptibilities, and the use of
21      experimental exposure regimens to make inferences about different human exposure scenarios
22      (NRC, 2002).
23            Toxicokinetic  and toxicodynamic models are generally premised on site concordance
24      across species, modeling, for example, the relationship between administered dose and liver
25      tissue concentrations to predict increased incidences of liver cancer. This relationship, which
26      can be observed in animals, is typically only inferred for humans. There are, however, numerous
27      examples of an agent  causing different cancers in different species.  The assessment should
28      discuss the relevant data that bear on this form of model uncertainty.
29            Parameter uncertainty refers to a lack of knowledge about the values of a model's
30      parameters. This leads to a distribution of values for each parameter.  Common sources of
31      parameter uncertainty include random measurement errors, systematic measurement errors, use
32      of surrogate data  instead of direct measurements,  misclassification of exposure status, random
33      sampling  errors, and use of an  unrepresentative sample.  Most types of parameter uncertainty can
34      be quantified by statistical analysis.

        February  27, 2003                         3-23             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1            Human variation refers to person-to-person differences in biological susceptibility or in
  2      exposure.  Although both human variation and uncertainty can be characterized as ranges or
  3      distributions, they are fundamentally different concepts. Uncertainty can be reduced by further
  4      research that supports a model or improves a parameter estimate, but human variation is a reality
  5      that can be better characterized, but not reduced, by further research. Fields other than risk
  6      assessment use "variation" or "variability" to mean dispersion about a central value, including
  7      measurement errors and other random errors that risk assessors address as uncertainty.
  8
  9            Probabilistic risk assessment, informed by expert judgment, has been used in exposure
10      assessment to estimate human variation and uncertainty in lifetime  average daily dose.
11      Probabilistic methods can be used in this exposure assessment application because the pertinent
12      variables (for example, concentration, intake rate, exposure duration, and body weight) have
13      been identified, their distributions can be observed, and the formula for combining the variables
14      to estimate the lifetime average daily dose is well defined (see U.S. EPA, 1992a). Similarly,
15      probabilistic methods can be applied in dose-response assessment when there is an
16      understanding of the important parameters and their relationships, such as identification of the
17      key determinants of human variation (for example, metabolic polymorphisms, hormone levels,
18      and cell replication rates), observation of the distributions of these variables,  and valid models
19      for combining these variables.  With appropriate data and expert judgment, formal approaches to
20      probabilistic risk assessment can be applied to provide insight into the overall extent and
21      dominant sources of human variation and uncertainty.  In doing this, it is important to note that
22      analyses that omit or underestimate some principal sources of variation or uncertainty could
23      provide a misleadingly narrow description of the true extent of variation and uncertainty and
24      give decision-makers a false sense of confidence in estimates of risk. Specification  of joint
25      probability distributions is appropriate when variables are not independent of each other.  In
26      each case, the assessment should carefully consider the questions of uncertainty and human
27      variation and discuss the extent to which there are data to address them.
28            Probabilistic risk assessment has been used in dose-response assessment to determine and
29      distinguish the degree of uncertainty and variability in toxicokinetic and toxicodynamic
30      modeling.  Although this field is less advanced that probabilistic exposure assessment, progress
31      is being made and these guidelines are flexible enough to accommodate continuing advances in
32      these approaches.
33
34

        February 27, 2003                          3-24            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      3.7. DOSE-RESPONSE CHARACTERIZATION
  2            A dose-response characterization extracts the dose-response information needed in a full
  3      risk characterization (U.S. EPA, 2000b), including
  4
  5            •    presentation of the recommended estimates (slope factors, reference doses,
  6                 reference concentrations),
  7
  8            •    a summary of the data supporting these estimates,
  9
10            •    a summary of the modeling approaches used,
11
12            •    the POD narrative (see Section 3.2.5),
13
14            •    a summary of the key defaults invoked,
15
16            •    identification of susceptible populations or lifestages and quantification of their
17                 differential susceptibility, and
18
19            •    a discussion of the strengths and limitations of the dose-response assessment,
20                 highlighting significant issues in developing risk estimates, alternative approaches
21                 considered equally plausible, and how these issues were resolved.
22
23            All estimates should be accompanied by the weight of evidence descriptor (see
24      Section 2.6) to convey a sense of the qualitative uncertainty about whether the agent may or may
25      not be carcinogenic.
26            Slope factors generally represent an upper bound on the average risk in a population or
27      the risk for a randomly selected individual but not the risk for a highly susceptible individual or
28      group. Some individuals face a higher risk and some face a lower risk. The use of upper bounds
29      generally is considered to be a health-protective approach for covering the risk to susceptible
30      individuals, although the calculation of upper bounds is not based on susceptibility data.
31      Similarly, exposure during some lifestages can contribute more or less to the total lifetime risk
32      than do similar exposures at other times.  The dose-response assessment characterizes, to the
33      extent possible, the extent of these variations.
        February 27, 2003                          3-25            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1            Depending on the supporting data and modeling approach, a slope factor can have a mix
 2      of traits that tend to either estimate, overestimate, or underestimate risk.
 3            Some examples of traits that tend to overestimate risk include:
 4
 5            •    The slope factor is derived from data on a highly susceptible animal strain.
 6            •    Linear extrapolation is used as a default and extends over several orders of
 7                 magnitude.
 8
 9            •    The largest of several slope factors is chosen.
10
11            Some examples of traits that tend to underestimate risk include:
12
13            •    Several tumor types were observed, but the slope factor is based on a subset of
14                 them.
15
16            •    The study design does not include exposure during a susceptible lifestage, for
17                 example, perinatal exposure.
18
19            •    The study population is of less-than-average susceptibility, for example, healthy
20                 adult workers.
21
22            •    There is random exposure misclassification or random exposure measurement error
23                 in the study from which the slope factor is derived.
24
25            Some examples of traits that neither overestimate nor underestimate risk include:
26
27            •    The slope factor is derived from data in humans or in an animal strain that responds
28                 like humans.
29
30            •    Linear extrapolation is appropriate for the agent's mode of action.
31
32            •    Environmental exposures are close to the observed data.
33
        February 27, 2003                         3-26            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
1            •     Several slope factors for the same tumor are averaged or a slope factor is derived
2                  from pooled data from several studies.
3
4            •     The slope factor is derived from the only suitable study.
5
6            The dose-response characterization weighs these traits and discusses the degree to which
7     the slope factor, on balance, would tend to yield an overestimate, underestimate, or central
8     estimate of risk. If the overall tendency appears to underestimate risk, then the assessment may
9     adjust the slope factor so that risk is not likely to be underestimated.
      February 27, 2003                          3-27            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
   Figure 3-1. Compatability of alternative points of departure with
   observed and modeled tumor incidences
  15%
                X Observed tumor incidence
                   Modeled tumor incidence
                "- Extrapolations from LED10 and LED01
   Figure 3-2. Crossing—between 10% and 1%—of dose-response curves
   for bladder carcinomas and liver carcinomas induced by 2-AAF
  10%
   5%
   0%
X Observed bladder tumors
— Modeled bladder tumors
•*• Extrapolations from LED10 and LED01 for
   bladder tumors
+ Observed liver tumors                  ^
— Modeled liver tumors               s
•* Extrapolation from LED10 and I,ED01 for
   liver tumors              , '
                          s
                          50
                                  100
150
February 27, 2003
                                 3-28
                                                  DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1                                  4.  EXPOSURE ASSESSMENT
  2
  3            Exposure assessment is the determination (qualitative and quantitative) of the magnitude,
  4      frequency, and duration of exposure (U.S. EPA, 1992a).  This section provides a brief overview
  5      of exposure assessment principles, with an emphasis on issues related to carcinogenic risk
  6      assessment. The information presented here should be used in conjunction with other guidance
  7      documents, including Guidelines for Exposure Assessment (U.S. EPA, 1992a), Policy and
  8      Guidance for Risk Characterization (U.S. EPA, 2000b), Exposure Factors Handbook (U.S.
  9      EPA, 1997c), the 1997 Policy for Use of Probabilistic Analysis  in Risk Assessments (U.S. EPA,
10      1997d), and the 1997 Guiding Principles for Monte Carlo Analysis (U.S. EPA, 1997e). In
11      addition, program-specific guidelines for exposure assessment should be consulted.
12            Exposure assessment generally consists of four major steps: defining the assessment
13      questions, selecting or developing the conceptual and mathematical models, collecting data or
14      selecting and evaluating available data, and exposure characterization. Each of these steps is
15      briefly described below.
16
17      4.1. DEFINING THE ASSESSMENT QUESTIONS
18            In providing a clear and unambiguous statement of the purpose and scope of the exposure
19      assessment (U.S. EPA, 1997e), consider the following:
20
21            •    The management objectives of the assessment will determine whether deterministic
22                 screening level analyses are adequate or whether full probabilistic exposure
23                 characterization is needed.
24
25            •    Identify and include all important sources (e.g., pesticide applications), pathways
26                 (e.g., food or water), and routes (e.g., ingestion, inhalation, and dermal) of exposure
27                 in the assessment. If a particular source, pathway,  or route is omitted, a clear and
28                 transparent explanation should be provided.
29
30            •    Separate analyses should be conducted for each definable subgroup within the
31                 population of interest. In particular, subgroups that are believed to be highly
32                 exposed or susceptible to a particular health effect  should be studied.  These include
33                 people with certain diseases or genetic susceptibilities and others whose behavior or
       February 27,2003                         4-1             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1                 physiology may lead to higher exposure or susceptibility. Consider the following
 2                 examples:
 3
 4                 —   Physiological differences between men and women (e.g., body weight and
 5                      inhalation rate) may lead to important differences in exposures.  See, for
 6                      example, the discussion in Exposure Factors Handbook, Appendix 1A (U.S.
 7                      EPA, 1997c).
 8
 9                 —   Pregnant and lactating women may have exposures that differ from the
10                      general population (e.g., slightly higher water consumption) (U.S.
11                      EPA, 1997c). Further, exposure to pregnant women may result in exposure to
12                      the developing fetus (NRC, 1993b).
13
14                 —   Children consume more food per body weight than do adults while consuming
15                      fewer types of foods (ILSI, 1992; NRC, 1993b; U.S. EPA, 1997c). In
16                      addition, children engage in crawling and mouthing (i.e., putting hands and
17                      objects in the mouth) behaviors, which can increase their exposures.
18
19                 —   The elderly and disabled may have important differences in their exposures
20                      due to a more sedentary lifestyle (U.S. EPA, 1997c). In addition, the health
21                      status of this group may affect their susceptibility to the detrimental effects of
22                      exposure.
23
24            For further guidance, see Guidelines for Exposure Assessment, § 3 (U.S. EPA, 1992a).
25
26     4.2. SELECTING OR DEVELOPING THE CONCEPTUAL AND MATHEMATICAL
27     MODELS
28            Carcinogen risk assessment models are generally based on the premise that risk is
29     proportional to total lifetime dose.  For lifetime human exposure scenarios, therefore, the
30     exposure metric used for carcinogenic risk assessment is the lifetime average daily dose
31     (LADD).  The LADD is typically used in conjunction with the slope factor to calculate
32     individual excess cancer risk.  It is an estimate of the daily intake of a carcinogenic agent
33     throughout the entire life of an individual. Depending on the objectives of the assessment, the
34     LADD may be calculated deterministically (using point estimates for each factor to derive a

       February 27,2003                        4-2           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1     point estimate of the exposure) or stochastically (using probability distributions to represent each
 2     factor and such techniques as Monte Carlo analysis to derive a distribution of the LADD) (U.S.
 3     EPA, 1997e). Stochastic analyses may help to identify certain population segments that are
 4     highly exposed and may need to be assessed as a special subgroup.  For further guidance, see
 5     Guidelines for Exposure Assessment, § 5.3.5.2 (U.S. EPA, 1992a).
 6            When the route of exposure is inhalation or dermal contact, derivation of the LADD often
 7     needs an approach to "route-to-route extrapolation."  The slope factor and other measures of
 8     toxicity are typically derived from oral administered doses in animal studies. Therefore, for
 9     ingestion exposures in a human population it is not usually necessary to make adjustments to
10     account for route-specific differences in absorption and uptake. However, for inhalation and
11     dermal exposures, such adjustments may be necessary. For further guidance, see Guidelines for
12     Exposure Assessment, § 2.1.4 (U.S. EPA, 1992a).
13            For less-than-lifetime human exposure scenarios, use of an LADD is more likely to lead
14     to an underestimate than an overestimate of risk (see  Section 3.4).  As methodological research
15     focuses on new approaches for estimating risks from  less-than-lifetime exposures, methods and
16     defaults can be expected to change.
17            There may be cases where the mode of action indicates that dose rates are important in
18     the carcinogenic process.  In these cases, short-term, less-than-lifetime exposure estimates may
19     be more appropriate than the LADD for risk assessment.  This is typically the case when a
20     nonlinear dose-response approach is used (see Section 3.4).
21
22     4.3. COLLECTING DATA OR SELECTING AND EVALUATING AVAILABLE DATA
23            After the assessment questions have been defined and the conceptual and mathematical
24     models have been developed, it is important to compile and evaluate existing data or, if
25     necessary, to collect new data. Depending on the exposure scenario under consideration, data on
26     a wide variety of exposure factors may be needed. EPA's Exposure Factors Handbook (U.S.
27     EPA, 1997c) contains a large compilation of exposure data, with some analysis and
28     recommendations.  Some of these data are organized by age groups to assist with assessing such
29     subgroups as children. See, for example, Exposure Factors Handbook, Volume 1, Chapter 3
30     (U.S. EPA, 1997c). When using these existing data, it is important to evaluate the quality of the
31     data and the extent to which the data are representative of the population under consideration.
32     EPA's Guidance for Data Quality Assessment (U.S. EPA, 2000d) and program-specific
33     guidances can provide further assistance for evaluating existing data.
       February 27,2003                         4-3            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
  1             When existing data fail to provide an adequate surrogate for the needs of a particular
  2      assessment, it is important to collect new data.  Such data collection efforts should be guided by
  3      the references listed above (e.g., Guidance for Data Quality Assessment and program-specific
  4      guidance). Once again, subgroups of concern are an important consideration in any data
  5      collection effort.
  6
  7      4.3.1. Adjusting Unit Risks for Highly Exposed Populations and Lifestages
  8             Unit risk estimates developed in the dose-response assessment often assume standard
  9      adult intake rates. When an exposure assessment focuses on a population with higher exposure,
10      good exposure assessment practice would replace the standard intake rates with values
11      representative of the exposed population.
12
13                 For example, to adjust the drinking water unit risk for an active
14                 population that drinks 4 L/day (instead of 2 L/day), multiply the unit
15                 risk by 2.
16
17             Because children eat more food, drink more water, and breathe more air relative to body
18      weight than do adults (U.S. EPA, 2002d), adjustments to unit risk estimates are warranted
19      whenever they are applied in an assessment of childhood exposure.
20
21                 For example, to adjust the drinking water unit risk for a 9-kg infant
22                 who drinks 1 L/day (instead of a 70-kg adult who drinks 2 L/day),
23                 multiply the unit risk by [(1 L/day) / (9 kg)] / [(2 L/day)
24                 / (70 kg)] = 3.9.
25
26             Air unit risks are typically expressed in terms of air concentrations rather than daily
27      intakes (U.S. EPA, 1994). Children and  adults breathing the same concentration of an agent
28      (such as a reactive gas) may receive  different doses to the body or lungs (U.S. EPA, 2002b). For
29      effects other than cancer, reference concentrations derived from a human-equivalent
30      concentration are made to cover the general population by applying uncertainty factors for
31      human variation or an incomplete database (U.S. EPA, 1994). For cancer unit risks, the human-
32      equivalent concentration has been used without applying uncertainty factors, necessitating
33      another approach to ensure that other groups are represented.  One such approach  would be to
        February 27, 2003                          4-4            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      calculate separate human-equivalent concentrations for children and adults in the dose-response
 2      assessment (see Section 3.1.3), leading to separate unit risks for children and adults.
 3             However, if only adult-based values were presented in the dose-response assessment, a
 4      comparison of breathing rates relative to respiratory tract dimensions in children and adults can
 5      be undertaken (U.S. EPA, 2002b, 1994) in the exposure assessment to decide whether risk values
 6      for children can be  improved by (1) substituting child-specific parameter values in the dosimetry
 7      model, (2) applying an adjustment or uncertainty factor, or (3) determining whether a verbal
 8      characterization of exposure differences between children and adults will suffice.
 9             Any adjustments are made consistent with the dosimetry model that was used. In these
10      models, dose is generally proportional to air intake rate adjusted for surface area (for respiratory
11      tract effects) or body weight (for effects elsewhere in the body). The dosimetry model that was
12      used can be adapted for healthy children by substituting the child's air intake rate, surface area,
13      and body weight in place of the adult default (U.S. EPA, 1994).
14             An exception occurs for gases that are not reactive and not water soluble. In this case,
15      dose is proportional to the blood:gas partition coefficient, independent of intake rate and surface
16      area, assuming equilibrium between ambient air, blood, and body compartments
17      (U.S. EPA, 1994).  Consequently, it is important to determine whether children reach
18      equilibrium as quickly as do adults. Under nonequilibrium conditions, dose can depend on
19      intake rate and body size.
20             The dose-response assessment discusses the key sources of uncertainty in estimating
21      children's doses, including use of dosimetry models that are based on the dimensions of the adult
22      respiratory tract. This is particularly crucial for particle dosimetry, because a different
23      distribution of particle sizes would be expected in a child's smaller respiratory tract. Children's
24      dose is also affected by other anatomical and metabolic differences between children and adults.
25
26      4.4. EXPOSURE CHARACTERIZATION
27             The exposure characterization is a technical characterization that presents the assessment
28      results and supports the risk characterization.  It provides a statement of the purpose, scope, and
29      approach used in the assessment,  identifying the exposure scenarios and population subgroups
30      covered. It provides estimates of the magnitude, frequency, duration,  and distribution of
31      exposures among members of the exposed population as the data permit.  It identifies and
32      compares the contribution of different sources, pathways, and routes of exposure. In particular, a
33      qualitative discussion of the strengths and limitations (uncertainties) of the data and models are
34      presented.

        February 27, 2003                          4-5             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1             The discussion of uncertainties is a critical component of the exposure characterization.
  2      Uncertainties can arise out of problems with the conceptual and mathematical models.
  3      Uncertainties can also arise from poor data quality and data that are not quite representative of
  4      the population or scenario of interest. Consider the following examples of uncertainties.
  5
  6             •     National data (i.e., data collected to represent the entire U.S. population) may not
  7                  be representative of exposures occurring within a regional or local population.
  8
  9             •     Use of short-term data to infer chronic, lifetime exposures should be done with
10                  caution.  Use of short-term data to estimate long-term exposures has the tendency to
11                  underestimate the number of people exposed while overestimating the exposure
12                  levels experienced by those in the upper end (i.e., above the 90th percentile) of the
13                  exposure distribution. For further guidance, refer to Guidelines for Exposure
14                  Assessment, § 5.3.1 (U.S. EPA, 1992a).
15
16             •     Children's behavior may lead to relatively high but intermittent exposures. This
17                  pattern of exposure, "one that gradually declines over the developmental period and
18                  which remains relatively constant thereafter" is not accounted for in the LADD
19                  model (ILSI, 1992).  Further, the physiological characteristics of children may lead
20                  to important differences in exposure.  Some of these differences can be accounted
21                  for in the LADD model. For further guidance, see Guidelines for Exposure
22                  Assessment, § 5.3.5.2 (U.S. EPA, 1992a).
23
24             Overall, the exposure characterization should provide a full description of the sources,
25      pathways, and routes of exposure.  The characterization also should include a full description of
26      the populations assessed. In particular, highly exposed or susceptible subgroups should be
27      discussed. For further guidance on the  exposure characterization, consult Guidelines for
28      Exposure Assessment (U.S. EPA,  1992a), the Policy and Guidance for Risk Characterization
29      (U.S. EPA, 2000b, 1995) and EPA's Rule Writer's Guide to Executive Order 13045 (especially
30      Attachment C: Technical Support for Risk Assessors—Suggestions for Characterizing Risks to
31      Children) (U.S. EPA, 1998d).
32
        February 27, 2003                          4-6             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1                                 5. RISK CHARACTERIZATION
  2
  3      5.1. PURPOSE
  4            EPA has developed general guidance on risk characterization for use in its risk
  5      assessment activities. The core of EPA's risk characterization policy (U.S. EPA, 2000b, 1995)
  6      includes the following:
  7
  8                 Each risk assessment prepared in support of decision making at EPA should
  9                 include a risk characterization that follows the principles and reflects the
10                 values outlined in this policy. A risk characterization should be prepared in
11                 a manner that is clear, transparent, reasonable, and consistent with other risk
12                 characterizations of similar scope  prepared across programs in the Agency.
13                 Further, discussion of risk in all EPA reports, presentations, decision
14                 packages, and other documents should be substantively consistent with the
15                 risk characterization.  The nature of the risk characterization will depend
16                 upon the information available, the regulatory application of the risk
17                 information, and the resources (including time) available. In all cases,
18                 however, the assessment should identify and discuss all the major issues
19                 associated with determining the nature and extent of the risk and provide
20                 commentary on any constraints limiting fuller exposition.
21
22            Risk characterization should be carried  out in accordance with the EPA and OMB
23      information quality guidelines.  EPA's Risk Characterization Handbook (U.S. EPA, 2000b)
24      provides detailed guidance to Agency staff. The discussion below does not attempt to duplicate
25      this material, but it summarizes its applicability to carcinogen risk assessment.
26            The risk characterization process includes an integrative analysis of the major results of
27      the risk assessment that is summarized for the risk manager in a nontechnical discussion that
28      minimizes the use of technical terms. It is an appraisal of the science that informs the risk
29      manager in public health decisions, as do other decision-making analyses of economic, social, or
30      technology issues. It also serves the needs of other interested readers.  The summary is an
31      information resource for preparing risk communication information, but being somewhat
32      technical, is not itself the usual vehicle for communication with every audience.
33            The integrative analysis brings together the assessments of hazard, dose response, and
34      exposure to make risk estimates for the exposure scenarios  of interest.  This analysis is generally

        February 27, 2003                  .         5-1             DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1      much more extensive than the risk characterization summary.  It may be peer reviewed or subject
 2      to public comment along with the summary in preparation for an Agency decision. The
 3      integrative analysis may be titled differently by different EPA  programs (e.g., "Staff Paper" for
 4      criteria air pollutants), but it typically will identify exposure scenarios of interest in decision
 5      making and present risk analyses associated with them. Some of the analyses may concern
 6      scenarios in several media; others may examine, for example, only drinking water risks.  The
 7      integrative analysis also may be the document that contains quantitative analyses of uncertainty.
 8            The values supported by a risk characterization throughout the process are transparency
 9      in environmental decision making, clarity in communication, consistency in core assumptions
10      and science policies from case to case, and reasonableness.  While it is appropriate to err on the
11      side of protection of health and the environment in the face of scientific uncertainty, common
12      sense and reasonable application of assumptions and policies are essential to avoid unrealistic
13      estimates of risk (U.S. EPA, 2000b, 1995).  Both integrative analyses and the risk
14      characterization summary present an integrated and balanced picture of the analysis of the
15      hazard, dose-response, and exposure. The risk analyst should provide summaries of the evidence
16      and results and describe the quality of available data and the degree of confidence to be placed in
17      the risk estimates. Important features include the constraints of available data and the state of
18      knowledge, significant scientific issues, and significant science and science policy choices that
19      were made when alternative interpretations  of data exist (U.S.  EPA, 2000b, 1995).  Choices
20      made about using default options or data in  the assessment are explicitly discussed in the course
21      of analysis, and if a choice is a significant issue, it is highlighted in the summary.
22
23      5.2. APPLICATION
24            Risk characterization is a necessary part of generating any Agency report on risk,
25      whether the report is preliminary—to support allocation of resources toward further study—or
26      comprehensive—to support regulatory decisions.  In the former case, the detail and
27      sophistication of the characterization are appropriately small in scale; in the latter case,
28      appropriately extensive. Even if a document covers only parts of a risk assessment (hazard and
29      dose-response analyses, for instance), the results of these are characterized.
30            Risk assessment is an iterative process that grows in depth and scope in stages from
31      screening for priority making to preliminary estimation to fuller examination in support of
32      complex regulatory decision making. Default options are typically used at every stage because
33      no database is ever complete, but they are predominant at screening stages and are used less as
34      more data are gathered and incorporated at later stages. Various provisions in EPA-administered

        February 27, 2003                           5-2            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      statutes require decisions based on differing findings for which differing degrees of analysis are
  2      appropriate.  There are close to 30 provisions within the major statutes that require decisions
  3      based on risk, hazard, or exposure assessment. For example, Agency review of pre-manufacture
  4      notices under Section 5 of the Toxic Substances Control Act relies on screening analyses,
  5      whereas requirements for industry testing under Section 4 of that Act rely on preliminary
  6      analyses of risk or simply of exposure. In comparison, air quality criteria under the Clean Air
  7      Act rest on a rich data collection and required by statute to undergo periodic reassessment.
  8      There are provisions that require ranking of hazards of numerous pollutants—which may be
  9      addressed through a screening level of analysis—and other provisions for which a full
10      assessment of risk is more appropriate.
11            Given this range in the scope and depth of analyses, not all risk characterizations can or
12      should be equal in coverage or depth. The risk assessor should carefully decide which issues in a
13      particular assessment are important to present, choosing those that are noteworthy in their impact
14      on results. For example, health effect assessments typically rely on animal data because human
15      data are rarely available. The objective of characterization of the use of animal data is not to
16      recount generic issues about interpreting and using animal data; Agency guidance documents
17      cover these issues. Rather, the objective is to call out any significant issues that arose within the
18      particular assessment being characterized and inform the reader about significant uncertainties
19      that affect conclusions.
20
21      5.3. PRESENTATION OF THE RISK CHARACTERIZATION SUMMARY
22            The presentation is a nontechnical discussion of important conclusions, issues, and
23      uncertainties that uses the hazard, dose response, exposure, and integrative analyses for technical
24      support.  The primary technical supports within the risk assessment are the hazard
25      characterization, dose-response characterization, and exposure characterization described in this
26      guideline. The risk characterization  is derived from these. The presentation should fulfill the
27      aims  outlined in the purpose section  above.
28
29      5.4. CONTENT OF THE RISK CHARACTERIZATION SUMMARY
30            Specific guidance on hazard, dose-response, and exposure characterization appears in
31      previous sections. Overall, the risk characterization routinely includes the following, capturing
32      the important items covered in hazard, dose response, and exposure characterization:
33
        February 27,2003                          5-3            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
 1            •    Primary conclusions about hazard, dose response, and exposure, including equally
 2                 plausible alternatives.
 3
 4            •    Nature of key supporting information and analytic methods.
 5
 6            •    Risk estimates and their attendant uncertainties, including key uses of default
 7                 options when data are missing or uncertain.
 8
 9                 —  With linear extrapolations, risk is typically approximated by multiplying the
10                      slope factor by an estimate of exposure [Risk = Slope factor x Exposure]. For
11                      exposure levels above the POD, the dose-response model is used instead of
12                      this approximation.
13
14                 —  With nonlinear extrapolations, hazard can be expressed as a hazard quotient
15                      (HQ), defined as the ratio of an exposure estimate over the reference dose
16                      (RfD)  (HQ  = Exposure / RfD).  From the hazard quotient, it can generally be
17                      inferred whether the nonlinear mode of action is relevant at the environmental
18                      exposure level in question.
19
20            •    Statement of the extent of extrapolation of risk estimates from observed data to
21                 exposure levels of interest and its implications for certainty or uncertainty in
22                 quantifying risk.  The extent of extrapolation can be expressed as a margin of
23                 exposure (MOE), defined as the ratio of the POD over an exposure estimate
24                 (MOE = POD / Exposure).
25
26            •    Significant strengths and limitations of the data and analyses, including any major
27                 peer review issues.
28
29            •    Appropriate comparison with similar EPA risk analyses or common risks with
30                 which people may be familiar.
31
32            •    Comparison with assessment of the same problem by another organization.
33
        February 27, 2003                          5-4            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
1            When a cancer risk assessment is prepared in a context where the results are likely to be
2      used by Agency economists and policy analysts, it is important that the resulting
3      characterizations include expected estimates of risk, as stipulated in OMB and EPA guidelines
4      for benefit-cost analysis. Statutory mandates, such as the Safe Drinking Water Act, the Food
5      Quality Protection Act, and the Clean Air Act, call for the Agency to generate specific kinds of
6      risk information and thus these updated cancer assessment guidelines should be read in
7      conjunction with the Agency's statutory mandates regarding risk assessment.
       February 27, 2003                          5-5             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1                           APPENDIX: MAJOR DEFAULT OPTIONS
  2
  3            This discussion covers the major default options commonly employed in a cancer risk
  4      assessment and adopted in these guidelines. These options are predominantly inferences that are
  5      needed to use the data observed under empirical conditions in order to estimate events and
  6      outcomes under environmental conditions. Several inferential issues arise when effects seen in a
  7      subpopulation of humans or animals are used to infer potential effects in the population of
  8      environmentally exposed humans.  Several more inferential issues arise in extrapolating the
  9      exposure-effect relationship observed empirically to  lower-exposure environmental conditions.
10      The following issues cover the major default areas. Typically, an issue has some sub-issues;
11      they are introduced here but are discussed in greater detail in later sections.
12
13         •  Is the presence or absence of effects observed in a human population predictive of effects
14            in another exposed human population?
15
16         «Is the presence or absence of effects observed in an animal population predictive of
17            effects in exposed humans?
18
19         •  How do metabolic pathways relate across species and among different age groups and
20            between sexes in humans?
21
22         •  How do toxicokinetic processes relate across  species and among different age groups and
23            between sexes in humans?
24
25         •  What is the correlation of the observed dose-response relationship to the relationship at
26            lower doses?
27
28      Is the Presence or Absence of Effects Observed in a Human Population Predictive of Effects
29      in Another Exposed Human Population ?
30            When cancer effects in exposed humans are attributed to exposure to an exogenous
31      agent, the default option is that the resulting data are predictive of cancer in any other exposed
32      human population.  Studies either attributing cancer effects in humans to exogenous agents or
33      reporting no effects  are often studies of occupationally exposed humans. By sex, age, and
34      general health, workers are not representative of the general  population exposed environmentally

        February 27,2003                          A-l             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      to the same agents. In such studies there is no opportunity to observe subpopulations who are
 2      likely to be under represented, such as fetuses, infants and children, women, or people in poor
 3      health, who may respond differently from healthy workers.  Therefore, it is understood that this
 4      option could still underestimate the response of certain human subpopulations. (NRC, 1993b,
 5      1994).
 6            There is not yet enough knowledge to form a basis for any generally applicable
 7      qualitative or quantitative inference to compensate for this knowledge gap. In these guidelines,
 8      this problem is left to analysis in individual cases, to be attended to with further general guidance
 9      as future research and information allow.  When information on a susceptible subpopulation or
10      lifestage exists, it will be used. For example, an agent such as diethylstilbestrol (DBS) causes a
11      rare form of vaginal cancer (clear-cell adenocarcinoma) (Herbst, 1971) in about 1 per 1000 of
12      adult women whose mothers were exposed during pregnancy (Hatch et al., 1998).  When cancer
13      effects are not found in an exposed human population, this information by itself is not generally
14      sufficient to conclude that the agent poses no carcinogenic hazard to this or other populations of
15      potentially exposed humans,  including susceptible subpopulations or lifestages. This is because
16      epidemiologic studies usually have low power to detect and attribute responses and typically
17      evaluate cancer potential in a restricted population (e.g., by age, occupation).  The topic of
18      susceptibility and variation is addressed further in the discussion below of quantitative default
19      options about dose-response relationships.
20
21      Is the Presence or Absence of Effects Observed in an Animal Population Predictive of Effects
22      in Exposed Humans ?
23            The default option is  that positive effects in animal cancer studies indicate that the agent
24      under study can have carcinogenic potential in humans. Thus, if no adequate human data are
25      present, positive effects in animal cancer studies are a basis for assessing the carcinogenic hazard
26      to humans. This option is a public health-conservative policy, and it is both appropriate and
27      necessary given that we do not test for carcinogenicity in humans. The option is supported by
28      the fact that nearly all of the  agents known to cause cancer in humans are carcinogenic in
29      animals in tests that have adequate protocols (IARC, 1994; Tomatis et al., 1989; Huff, 1994).
30      Moreover, almost one-third of human carcinogens were identified subsequent to animal testing
31      (Huff, 1993). Further support is provided by research on the molecular biology of cancer
32      processes, which has shown that the mechanisms of control of cell growth and differentiation are
33      remarkably homologous among species and highly conserved in evolution. Nevertheless, the
34      same research tools that have enabled recognition of the nature and commonality of cancer

        February 27, 2003                          A-2            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      processes at the molecular level also have the power to reveal differences and instances in which
  2      animal responses are not relevant to humans (Lijinsky, 1993; U.S. EPA, 1991b).  Under these
  3      guidelines, available mode of action information is studied for its implications in both hazard
  4      and dose-response assessment and its effect on default options.
  5             There may be instances in which the use of an animal model would identify a hazard in
  6      animals that is not truly a hazard in humans (e.g., the alpha-2u-globulin association with renal
  7      neoplasia in male rats [U.S. EPA, 1991b]).  The extent to which animal studies may yield false
  8      positive indications for humans is a matter of scientific debate. To demonstrate that a response
  9      in animals is not relevant to any human situation, adequate data to assess the relevancy issue
10      must be available.
11             The default option is that effects seen at the highest dose tested are appropriate for
12      assessment, but it is necessary that the experimental conditions be scrutinized. Animal studies
13      are conducted at high doses in order to provide statistical power, the highest dose being one that
14      is minimally toxic (maximum tolerated dose). Consequently, the question often arises of
15      whether a carcinogenic effect at the highest dose may be a consequence of cell killing with
16      compensatory cell replication or of general physiological disruption rather than inherent
17      carcinogenicity of the tested agent. There is little doubt that this may happen in some cases, but
18      skepticism exists among some scientists that it is a pervasive problem (Ames and Gold, 1990;
19      Melnick et al., 1993; Barrett,  1993). If adequate data demonstrate that the effects are solely the
20      result of excessive toxicity rather than carcinogenicity of the tested agent per se, then the effects
21      may be regarded as not appropriate to include in assessment of the potential for human
22      carcinogenicity of the agent.  This is a matter of expert judgment, with consideration given to all
23      of the data available about the agent, including effects in other toxicity studies, structure-activity
24      relationships, and effects on growth  control and differentiation.
25            When cancer effects are not found in well-conducted animal cancer studies in two or
26      more appropriate species and other information does not support the carcinogenic potential of
27      the agent, these data provide a basis for concluding that the agent is not likely to possess human
28      carcinogenic potential, in the absence of human data to the contrary. This default option about
29      lack of cancer effects has limitations. It is recognized that animal studies (and epidemiologic
30      studies as well) have very low power to detect cancer effects. Detection of a 10% tumor
31      incidence is generally the limit of power with standard protocols for animal studies  (with the
32      exception of rare tumors that are virtually markers for a particular agent, e.g., angiosarcoma
33      caused by vinyl chloride). In some situations, the tested animal species may not be  predictive of
34      effects in humans; for example, arsenic shows only minimal or no effect in animals, whereas it is

        February 27, 2003                          A-3            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      clearly positive in humans.  Therefore, it is important to consider other information as well;
 2      absence of mutagenic activity or absence of carcinogenic activity among structural analogues
 3      can increase the confidence that negative results in animal studies indicate a lack of human
 4      hazard.
 5            Another limitation is that standard animal study protocols are not yet available for
 6      effectively studying perinatal effects. The potential for effects on the very young generally
 7      should be considered separately. Under existing Agency policy (U.S. EPA, 1997a, b), perinatal
 8      studies accomplished by modification of existing adult bioassay protocols are required in special
 9      circumstances.
10            The default option is that target organ concordance is not a prerequisite for evaluating
11      the implications of animal study results for humans.  Target organs of carcinogenesis for agents
12      that cause cancer in both animals and humans are most often concordant at one or more sites
13      (Tomatis et al., 1989; Huff, 1994). However, concordance by site is not uniform.  The
14      mechanisms of control of cell growth and differentiation are concordant among species,  but there
15      are marked differences among species in the way control is managed in various tissues.  For
16      example, in humans, mutations of the tumor suppressor genes p53 and retinoblastoma are
17      frequently observed genetic changes in tumors. These tumor-suppressor genes are also observed
18      to be operating in some rodent tissues, but other growth control mechanisms predominate in
19      other rodent tissues. Thus, an animal response may be due to changes in a control that are
20      relevant to humans but appear in animals in a different way.
21            However, it is appropriate under these guidelines to consider the influences of route of
22      exposure, metabolism, and, particularly, some modes of action that may either support or not
23      support target organ concordance between animals and humans. When data allow, these
24      influences are considered in deciding whether the default remains  appropriate in individual
25      instances (NRC, 1994). Another exception to the basic default of not assuming site concordance
26      exists in the context of toxicokinetic modeling. Site concordance is inherently assumed  when
27      these models are used to estimate delivered dose in humans on the basis of animal data.
28            The default is to include benign tumors observed in animal studies in the assessment of
29      animal tumor incidence if such tumors have the capacity to progress to the malignancies with
30      which  they are associated. This default is consistent with the approach of the National
31      Toxicology Program and the International Agency for Research on Cancer and is somewhat
32      more protective of public health than not including benign tumors in the assessment; benign and
33      malignant tumors are treated as representative of related responses to the test agent (McConnell
34      et al., 1986), which is scientifically appropriate. Nonetheless, in assessing findings from animal

        February 27, 2003                         A-4           DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      studies, a greater proportion of malignancy is weighed more heavily than is a response with a
  2      greater proportion of benign tumors. Greater frequency of malignancy of a particular tumor type
  3      in comparison with other tumor responses observed in an animal study is also a factor to be
  4      considered in selecting the response to be used in dose-response assessment.
  5            Benign tumors that are not observed to progress to malignancy are assessed on a case-
  6      by-case basis. There is a range of possibilities for the overall significance of benign tumors.
  7      They may deserve attention because they are serious health problems even though they are not
  8      malignant; for instance, benign tumors may be a health risk because of their effect on the
  9      function of a target tissue, such as the brain.  They may be significant indicators of the need for
10      further testing of an agent if they are observed in a short-term test protocol, or such an
11      observation may add to the overall weight of evidence if the same agent causes malignancies in a
12      long-term study. Knowledge of the mode of action associated with a benign tumor response may
13      aid in the interpretation of other tumor responses associated with the same agent.
14
15      How Do Metabolic Pathways Relate Across Species and Among Different Age Groups and
16      Between Sexes in Humans?
17            The default option is that there is a similarity of the basic pathways of metabolism and
18      the occurrence of metabolites  in tissues in regard to the species-to-species extrapolation of
19      cancer hazard and risk.  If comparative metabolism studies were to show no similarity between
20      the tested species and humans and a metabolite(s) was the active form, there would be less
21      support for an inference that the animal response(s) relates to humans.  In other cases,
22      parameters of metabolism may vary quantitatively between species; this becomes a factor in
23      deciding on an appropriate human equivalent dose based on animal studies, optimally in the
24      context of a toxicokinetic model. Although the basic pathways are assumed to be the same
25      among humans, the presence of polymorphisms and the maturation of the pathways in infants
26      need to be considered. The active form of an agent may be present to differing degrees, or it
27      may be completely absent, which may result in greater or lesser risk for subpopulations.
28
29      How Do Toxicokinetic Processes Relate A cross Species and Among Different Age Groups and
30      Between Sexes in Humans?
31            A major issue is how to estimate human equivalent doses in extrapolating from animal
32      studies. As a default for oral exposure, a human equivalent dose for adults is estimated from
33      data on another species by an adjustment of animal applied oral dose by a scaling factor of body
34      weight to the 0.75 power. This adjustment factor is used because it represents scaling of

        February 27, 2003                         A-5            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      metabolic rate across animals of different size.  Because the factor adjusts for a parameter that
  2      can be improved on and brought into more sophisticated toxicokinetic modeling when such data
  3      become available, the default option of 0.75 power can be refined or replaced.  The same factor
  4      is used for children because it is slightly more protective than using children's body weight (see
  5      Section 3.1.3).
  6            For inhalation exposure, a human equivalent dose for adults is estimated by default
  1      methodologies that provide estimates of lung deposition and internal dose. The methodologies
  8      can be refined to more sophisticated forms with data on toxicokinetic and metabolic parameters
  9      of the specific agent. This default option, like the one for oral exposure, is selected in part
10      because it lays a foundation for incorporating better data. For gases and aerosols, an adjustment
11      is made for infants and children because their breathing rate and body weight differ from those
12      of adults (see Section 3.1.3).  For inhaled particles, the adjustment does not take into account the
13      different size and spacing of airways of children and adults; this difference could result in
14      children and adults retaining particles with a different size distribution and different toxicologic
15      properties.  To reduce this uncertainty, EPA is developing a default dosimetry model for children
16      that is based on children's inhalation parameters. The use of information to improve dose
17      estimation from applied to internal to delivered dose is encouraged, including use of
18      toxicokinetic modeling instead of any default, where data are available.
19            There are important differences between infants, adults, and older adults in the processes
20      of absorption, distribution, and elimination; for example, infants tend to, absorb metals through
21      the gut more rapidly and more efficiently than do older children or adults (Calabrese,  1986).
22      Renal elimination is also not as efficient in infants.  Although these processes reach adult
23      competency at about the time of weaning, they may have important implications, particularly
24      when the dose-response relationship for an agent is considered to be nonlinear and there is an
25      exposure scenario disproportionately affecting infants, because in these cases the magnitude of
26      dose is more pertinent than the usual approach in linear extrapolation of averaging dose across a
27      lifetime. Efficiency of intestinal absorption in older adults tends to be generally less overall for
28      most chemicals.  Another notable difference is that, post-weaning (about 1 year), children have a
29      higher metabolic rate than do adults (Renwick,  1998) and they may toxify or detoxify agents at a
30      correspondingly higher rate.
31            For a route-to-route exposure extrapolation,  the default option is that an agent that
32      causes internal tumors by one route of exposure will be carcinogenic by  another route if it is
33      absorbed by the second route to give an internal dose.  This is a qualitative option and is
34      considered to be public-health conservative.  The rationale is that for internal tumors an internal

        February 27, 2003                          A-6            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
  1      dose is significant no matter what the route of exposure.  Additionally, the metabolism of the
  2      agent will be qualitatively the same for an internal dose.  The issue of quantitative extrapolation
  3      of the dose-response relationship from one route to another is addressed case by case.
  4      Quantitative extrapolation is complicated by considerations such as first-pass metabolism, but it
  5      is approachable with empirical data. Adequate data are necessary to demonstrate that an agent
  6      will act differently by one route versus another route of exposure.
  7
  8      What Is the Correlation of the Observed Dose-Response Relationship to the Relationship at
  9      Lower Doses?
10             If sufficient data are available, a biologically based model for both the observed range
11      and extrapolation below that range may be used.  Although no standard biologically based
12      models are in existence, one may be developed if extensive data exist in a particular case and the
13      purpose of the assessment justifies the investment of the resources needed. The default
14      procedure for the observed range of data when a biologically based model is not used is to use a
15      curve-fitting model for incidence data.
16             In the absence of data supporting a biologically based model for extrapolation outside of
17      the observed range, the choice of approach is based on the view of mode of action of the agent
18      arrived at in the hazard assessment.
19             The basic default is to assume linearity and to use a linear default approach when the
20      mode of action information is supportive of linearity or mode of action is not understood.  The
21      linear approach is used when a view of the mode of action indicates a linear response, for
22      example, when a conclusion is made that an agent directly causes alterations in DNA, a kind of
23      interaction that not only theoretically requires one reaction but also is likely to be additive to
24      ongoing, spontaneous gene mutation. Other kinds of activity may have linear implications, for
25      example, linear rate-limiting steps that support a linear procedure also. The linear approach is to
26      draw a  straight line between a point of departure from observed data, generally, as a default, an
27      LED chosen to be representative of the lower end of the observed range, and the origin (zero
28      incremental dose, zero incremental response). This approach is generally considered to be
29      public-health protective.
30             The linear default is thought to generally provide an upper-bound calculation of potential
31      risk at low doses, for example, a 1/100,000 to 1/1,000,000 risk; the straight line approach gives
32      numerical results that are about the same as those from a linearized multistage procedure. This
33      upper bound is thought to be  public-health conservative at low doses for the range of human
34      variation, considering the typical Agency target range for risk management of 1/1,000,000 to

        February 27, 2003                          A-7             DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1      1/10,000, although it may not completely be so (Bois et al., 1995) if pre-existing disease or
 2      genetic constitution place a percentage of the population at risk from any exposure above zero to
 3      xenobiotics, natural or manmade.  The question of what may be the actual variation in human
 4      susceptibility is one that the NRC  (1994) report discussed, as did the NRC report on pesticides in
 5      children and infants (1993b).  NRC has recommended research on the question, and EPA and
 6      other agencies are conducting such research.  Given the current state of knowledge, EPA will
 7      assume that the linear default procedure adequately accounts for human variation unless there is
 8      case-specific information for a given agent that indicates a particularly susceptible subpopulation
 9      or lifestage, in which case the special information will be used.
10             When adequate data on mode of action show that linearity is not plausible and, provide
11      sufficient evidence to support a nonlinear mode of action for the general population and any
12      subpopulations of concern,  the default changes to a different approach—a reference
13      dose/reference concentration—that assumes that nonlinearity is more reasonable. The departure
14      point is again generally an LED when incidence data are modeled.
15            A sufficient basis to support this nonlinear procedure will include data on responses that
16      are key events integral to the carcinogenic process. This means that the point of departure
17      mostly will be from these precursor response data, for example, hormone levels or mitogenic
18      effects rather than tumor incidence data.
19            The mode of action may have specific implications to be considered for risk potential of
20      certain exposure scenarios.  For instance, stimulus of cell growth through hormonal or other
21      signal disruption or as a result of damage from toxicity are reversible if the exposure is for a
22      short time, because homeostasis brings a return to normal levels after cessation of exposure.
23      Another feature of a specific exposure scenario may be the exposure of a susceptible
24      subpopulation or lifestage.  If those exposed in a particular scenario wholly or largely comprise a
25      subpopulation or lifestage for whom evidence indicates a special susceptibility to the agent's
26      mode of action, this needs to be considered.
27             When the mode of action information indicates that the dose response may be adequately
28      described by both a linear and a nonlinear approach,  then the default is to present both the
29      linear analysis and the reference dose/reference concentration. An assessment may use both
30      linear and nonlinear approaches if linearity is not plausible and nonlinearity has support but a
31      mode of action is not defined or different responses are thought to result from different modes of
32      action or a response appears to be  very different at high and low doses due to influence of
33      separate modes of action. The results may be needed for assessment of combined risk from
34      agents that have common modes of action.

        February 27, 2003                         A-8            DRAFT FINAL - DO NOT CITE OR QUOTE

-------
 1            A default option is made that cumulative dose received over a lifetime, expressed as a
 2     lifetime average daily dose, is an appropriate measure of dose. This assumes that a high dose of
 3     such an agent received over a shorter period of time is equivalent to a low dose spread over a
 4     lifetime. This is thought to be a relatively public-health-protective option and has empirical
 5     support (Monro, 1992). An example of effects of short-term, high exposure that results in
 6     subsequent cancer development is treatment of cancer patients with certain chemotherapeutic
 7     agents.  An example of cancer from long-term exposure to an agent of relatively low potency is
 8     smoking.  When sufficient information is available to indicate that the carcinogenic mode of
 9     action supports a nonlinear dose-response approach, a different approach may be used. In these
10     cases, short-term exposure estimates (several days to several months) may be more appropriate
11     than the lifetime average daily dose, and both agent concentration and duration are likely to be
12     important, because such effects are generally observed to be reversible at cessation of very short-
13     term exposure.
       February 27,2003                          A-9            DRAFT FINAL-DO NOT CITE OR QUOTE

-------
                                          REFERENCES


Allen, BC; Crump, KS; Shipp, AM. (1988) Correlation between carcinogenic potency of chemicals in animals and
humans. Risk Anal 8:531-544.

Ames, BN; Gold, LS. (1990) Too many rodent carcinogens: mitogenesis increases mutagenesis. Science
249:970-971.

Ashby, J; Tennant, RW. (1991) Definitive relationships among chemical structure, carcinogenicity and mutagenicity
for 301 chemicals tested by the U.S. NTP. Mutat Res 257:229-306.

Ashby, J; Tennant, RW. (1994) Prediction of rodent carcinogenicity for 44 chemicals: results. Mutagenesis 9:7-15.

Ashby, J; Doerrer, NG; Flamm.'FG; et al. (1990) A scheme for classifying carcinogens. Regul Toxicol Pharmacol
12:270-295.

Ashby, J; Brady, A; Elcombe, CR; et al. (1994) Mechanistically based human hazard assessment of peroxisome
proliferator-induced hepatocarcinogenesis. Hum Exper Toxicol 13:1-117.

Barrett, JC. (1992) Mechanisms of action of known human carcinogens. In: Mechanisms of carcinogenesis in risk
identification. IARC Sci Pubs No. 116, 115-134. International Agency for Research on Cancer, Lyon, France.

Barrett, JC. (1993) Mechanisms of multistep carcinogenesis and carcinogen risk assessment. Environ Health
Perspect 100:9-20.

Barrett, JC; Lee, TC. (1992) Mechanisms of arsenic-induced gene amplification.  In: Kellems, RE, ed. Gene
amplification in mammalian cells: a comprehensive guide. New York: Marcel Dekker.

Baylin, S; Bestor, TH. (2002) Altered methylation patterns in cancer cell genomes: causes or consequence? Cancer
Cell 1:299-305.

Bayly, AC; Roberts, RA; Dive, C. (1994) Suppression of liver cell apoptosis in vitro by the nongenotoxic
hepatocarcinogen and peroxisome proliferator nafenopin. JCell Biol 125:197-203.

Bellamy, COC; Malcomson, RDG; Harrison, DJ; et al. (1995) Cell death in health and disease: the biology and
regulation of apoptosis. Seminars in Cancer Biology, Apoptosis in Oncogenesis and Chemotherapy 6:3-16.

Biggs, PJ; Warren, W; Venitt, S; et al. (1993) Does a genotoxic carcinogen contribute to human breast cancer? The
value of mutational spectra in unraveling the etiology of cancer. Mutagenesis 8:275-283.

Birnbaum, LS; Fenton, SE. (2003) Cancer and developmental exposure to endocrine disrupters. Environ Health
Perspect (in press).

Birner, G; Albrecht, W; Neumann, HG. (1990) Biomonitoring of aromatic amines. Ill: hemoglobin binding and
benzidine and some benzidine congeners. Arch Toxicol 64(2):97-102.

Blair, A; Burg, J; Foran, J; et al. (1995) Guidelines for application of meta-analysis in environmental epidemiology.
Regul Toxicol Pharmacol 22:189-197.

Bois, FY; Krowech, G; Zeise, L. (1995) Modeling human interindividual variability in metabolism and risk: the
example of 4-aminobiphenyl. Risk Anal 15:205-213.

Calabrese, EJ. (1986) Age and susceptibility to toxic substances. New York: Winter-Interscience Publication, John
Wiley and Sons, Inc.

Callemen, CJ; Ehrenberg, L; Jansson, B; et al. (1978) Monitoring and risk assessment by means of alkyl groups in
hemoglobin in persons occupationally exposed to ethylene oxide.  J Environ Pathol Toxicol 2:427^142.

Caporaso, N; Hayes, RB; Dosemeci, M; et al. (1989) Lung cancer risk, occupational exposure, and the debrisoquine
metabolic phenotype. Cancer Res 49:3675-3679.


February 27,2003                              R-l              DRAFT FINAL - DO NOT CITE OR QUOTE

-------
Cavenee, WK; Koufos, A; Hansen, MF. (1986) Recessive mutant genes predisposing to human cancer. Mutat Res
168:3-14.

Chang, CC; Jone, C; Trosko, JE; et al. (1988) Effect of cholesterol epoxides on the inhibition of intercellular
communication and on mutation induction in Chinese hamster V79 cells.  Mutat Res 206:471-478.

Chen, C; Farland, W. (1991) Incorporating cell proliferation in quantitative cancer risk assessment: approaches,
issues, and uncertainties. In: Butterworth, B., Slaga, T., Farland, W., et al., eds. Chemical induced cell proliferation:
implications for risk assessment. New York: Wiley-Liss, pp. 481^199.

Choy, WN. (1993) A review of the dose-response induction of DNA adducts by aflatoxin B2 and its implications to
quantitative cancer-risk assessment. Mutat Res 296:181-198.

Clayson, DB; Mehta, R; Iverson, F. (1994) Oxidative DNA damage—the effects of certain genotoxic and
operationally non-genotoxic carcinogens. Mutat Res 317:25^12.

Cohen, SM. (1995) Role of urinary physiology and chemistry in bladder carcinogenesis. Fd Chem Toxicol
33:715-30.

Cohen, SW; Ellwein, LB. (1990) Cell proliferation in carcinogenesis. Science 249:1007-1011.

Cohen, SM; Ellwein, LB. (1991) Genetic errors, cell proliferation and carcinogenesis. Cancer Res 51:6493-6505.

Cohen, SM; Purtilo, DT; Ellwein, LB. (1991) Pivotal role of increased cell proliferation in human carcinogenesis.
Mod Pathol 4:371-375.

Connolly,  RB; Andersen, ME. (1991) Biologically based pharmacodynamic models: tools for toxicological research
and risk assessment.  Ann Rev Pharmacol Toxicol 31:503-523.

Cresteil, T. (1998) Onset of xenobiotic metabolism in children: toxicological implications.  Food Addit Contam 15,
Supplement 45-51.

D'Souza, RW; Francis, WR; Bruce, RD; et al.  (1987) Physiologically based pharmacokinetic model for ethylene
chloride and its application in risk assessment. In: Pharmacokinetics in risk assessment: drinking water and health.
Vol. 8. Washington,  DC: National Academy Press.

Enterline,  PE; Henderson, VL; Marsh, GM. (1987) Exposure to arsenic. Amer J Epidemiol 125:929-938.

Executive  Order 13045 (1997). Protection of children from environmental health risks and safety risks, issued
April 21,1997.

Fearon, E; Vogelstein, B. (1990) A genetic model for colorectal tumorigenesis. Cell 61:959-967.

Fisher, RA. (1950) Statistical methods for research workers. Edinburgh, Scotland: Oliver and Boyd.

Flynn, GL. (1990) Physicochemical determinants of skin absorption. In: Gerriry, TR, Henry, CJ, eds. Principles of
route to route extrapolation for risk assessment. New York: Elsevier Science; pp. 93-127.

Garfinkel, L; Silverberg, E. (1991) Lung cancer and smoking trends in the United States over the past 25 years.
Cancer41:137-145.

Gaylor, DW; Zheng, Q. (1996) Risk assessment of nongenotoxic carcinogens based on cell proliferation/death rates
in rodents. Risk Anal 16(2):221-225.

Gaylor, DW; Kodell, RL; Chen, JJ; et al. (1994) Point estimates of cancer risk at low doses. Risk Anal
14(5):843-850.

Gibson, DP; Aardema, MJ; Kerckaert, GA; et al. (1995) Detection of aneuploidy-inducing carcinogens in the Syrian
hamster embryo (SHE) cell transformation assay. Mutat.Res 343:7-24.

Ginsberg,  GL. (2003) Assessing cancer risks from short-term exposures in children. Risk Anal 23(l):19-34.



February 27, 2003                              R-2               DRAFT FINAL - DO NOT CITE OR QUOTE

-------
Goddard, MJ; Murdoch, DJ; Krewski, D. (1995). Temporal aspects of risk characterization. Inhal Toxicol
7:1005-1018.

Goldsworthy, TL; Hanigan, MH; Pilot, HC. (1986) Models of hepatocarcinogenesis in the rat-contrasts and
comparisons. CRC Crit Rev Toxicol 17:61-89.

Goodman, JI; Counts, JL. (1993) Hypomethylation of DNA: A possible nongenotoxic mechanism underlying the
role of cell proliferation in carcinogenesis. Environ Health Perspect 101 Supp. 5:169-172.

Greenland, S. (1987) Quantitative methods in the review of epidemiologic literature. Epidemiol Rev 9:1—29.

Gulezian, D; Jacobson-Kram, D; McCullough, CB; et al. (2000) Use of transgenic animals for carcinogenicity
testing: considerations and implications for risk assessment. Toxicol Pathol 28:482^199.

Halmes, NC; Roberts, SM; Tolson, JK; et al. (2000) Reevaluating cancer risk estimates for short-term exposure
scenarios. Toxicol Sci 58:32-42.

Hammand, EC. (1966) Smoking in relation to the death rates of one million men and women. In: Haenxzel, W., ed.
Epidemiological approaches to the study of cancer and other chronic diseases. National Cancer Institute Monograph
No. 19. Washington, DC.

Hanahan, D; Weinberg, RA. (2000) The hallmarks of cancer. Cell 100:57-70.

Harris, CC; Hollstein, M. (1993) Clinical implications of the p53 tumor suppressor gene. N Engl. J Med
329:1318-1327.

Haseman, JK. (1983) Issues: a reexamination of false-positive rates for carcinogenesis studies. Fundam Appl
Toxicol 3:334-339.

Haseman, JK. (1984) Statistical issues in the design, analysis and interpretation  of animal carcinogenicity studies.
Environ Health Perspect 58:385-392.

Haseman, JK. (1985) Issues in carcinogenicity testing: dose selection. Fundam Appl Toxicol 5:66-78.

Haseman, JK. (1990) Use of statistical decision rules  for evaluating laboratory animal carcinogenicity studies.
Fundam Appl Toxicol 14:637-648.

Haseman, JK. (1995) Data analysis: Statistical analysis and use of historical control data. Regul Toxicol Pharmacol
21:52-59.

Hatch, EE, Palmer, JR, Titus-Ernstoff, L, Noller, KL et al. (1998) Cancer risk in women exposed to
diethylstilbestrol in utero. JAMA 280: 630-634.

Hattis, D. (1990) Pharmacokinetic principles for dose-rate extrapolation of carcinogenic risk from genetically active
agents. Risk Anal 10:303-316.

Hayward, JJ; Shane, BS; Tindall, KR; et al. (1995) Differential in vivo mutagenicity of the carcinogen-
noncarcinogen pair 2,4- and 2,6-diaminotoluene. Carcinogenesis 10:2429-2433.

Herbst, AL, Ulfelder, H, Poskanzer, DC. (1971) Adenocarcinoma of the vagina: association of maternal stilbestrol
therapy with tumor appearance in young women. N Engl J Med 284:878-881.

Hill, AB. (1965) The environment and disease: association or causation? Proc  R Soc Med 58:295-300.

Hoel,  DG; Kaplan, NL; Anderson, MW. (1983) Implication of nonlinear kinetics on risk estimation in
carcinogenesis. Science 219:1032-1037.

Holliday, R. (1987) DNA methylation and epigenetic  defects in carcinogenesis. Mutat Res 181:215-217.

Huff,  JE. (1993) Chemicals and cancer in humans: first evidence in experimental animals. Environ Health Perspect
100:201-210.
February 27, 2003                               R-3               DRAFT FINAL - DO NOT CITE OR QUOTE

-------
Huff, JE. (1994) Chemicals causally associated with cancers in humans and laboratory animals. A perfect
concordance. In: Carcinogenesis. Waalkes, MP, Ward, JM, eds., New York: Raven Press; pp. 25-37.

Hulka, BS; Margolin, BH. (1992) Methodological issues in epidemiologic studies using biological markers. Am J
Epidemiol 135:122-129.

IARC (International Agency for Research on Cancer). (1994) IARC monographs on the evaluation of carcinogenic
risks to humans. Vol.  60, Some Industrial Chemicals. Lyon, France: IARC; pp. 13-33.

IARC. (1999) The use of short- and medium-term tests for carcinogens and data on genetic effects in carcinogenic
hazard evaluation. Lyon, France.

ILSI (International Life Sciences Institute). (1992). Similarities & differences between children & adults;
implications for risk assessment." Washington, DC: ILSI Press.

ILSI. (1997) Principles for the selection of doses in chronic rodent bioassays. Foran, JA, ed. Washington, DC: ILSI
Press.

ILSI. (2001) Proceedings of workshop on the evaluation of alternative methods for carcinogenesis testing. Toxicol
Pathol  29:1-351.

IPCS (International Programme on Chemical Safety). (1999) IPCS workshop on developing a conceptual framework
for cancer risk assessment, 16-18 February 1999, Lyon, France, IPCS/99.6. IPCS, World Health Organization,
Geneva.

Ito, N; Shirai, T; Hasegawa, R. (1992) Medium-term bioassays for carcinogens. In: Vainio, H, Magee, PN,
McGregor, DB, et al., eds. Mechanisms of carcinogenesis in risk identifications. International Agency for Research
on Cancer, Lyon, France; pp. 353-388.

Jones, PA. (1986) DNA methylation and  cancer. Cancer Res 46:461-466.

Kehrer, JP. (1993) Free radicals as mediators of tissue injury and disease. Crit Rev Toxicol 23:21-48.

Kelsey, JL; Thompson, WD; Evans, AS. (1986) Methods in observational epidemiology. New York: Oxford
University Press.

Kimbell, JS; Subramaniam, RP; Gross, EA; Schlosser, PM; Morgan, KT. (2001) Dosimetry modeling of inhaled
formaldehyde: comparisons of local flux predictions in the rat, monkey and human nasal passages. Toxicol Sci
64(1):100-110.

Kinzler, KW; Vogelstein, B. (2002) Colorectal tumors. In: Vogelstein, B; Kinzler, KW, eds. The genetic basis of
human cancer. New York: McGraw-Hill.

Kinzler, KW; Nilbert, MC; Su, L-K; et al. (1991) Identification of FAP locus genes from chromosome 5q21. Science
253:661-665.

Kraus, AL; Munro, 1C; Orr, JC; et al. (1995) Benzoyl peroxide: an integrated human safety assessment for
carcinogenicity. Regul Toxicol Pharmacol 21:87-107.

Krewski, D;  Van Ryzin, J. (1981) Dose response models for quantal response toxicity data. In: Csorgo; Dawson;
Rao; et al., eds. Statistics and related topics. Amsterdam: North-Holland, pp. 201-231.

Krewski, D;  Murdoch, DJ; Withey, JR. (1987) The application of pharmacokinetic data in carcinogenic risk
assessment. In: Pharmacokinetics in risk assessment: drinking water and health. Vol. 8. Washington, DC: National
Academy Press; pp. 441—468.

Levine, AJ; Perry, ME; Chang, A; et al. (1994) The 1993 Walter Hubert lecture: the role of the p53 tumor-
suppressor gene in tumorigenesis. Br J Cancer 69:409-416.

Lijinsky, W. (1993) Species differences in carcinogenesis. In Vivo 7:65-72.

Lilienfeld, AM; Lilienfeld, D. (1979) Foundations of epidemiology, 2nd ed. New York: Oxford University Press.


February 27, 2003                              R-4              DRAFT FINAL - DO NOT CITE OR QUOTE

-------
Littlefield, NA; Farmer, JH; Gaylor, DW. (1980) ED01 study. J Environ Pathol Toxicol 3:17.

Maltoni, C; Lefemine, G; Ciliberti, A; et al. (1981) Carcinogenicity bioassay of vinyl chloride monomer: a model of
risk assessment on an experimental basis. Environ Health Perspect 41:3-29.

Maronpot, RR; Shimkin, MB; Witschi, HP; et al. (1986) Strain A mouse pulmonary tumor test results for chemicals
previously tested in National Cancer Institute Carcinogenicity test. J Natl Cancer Inst 76:1101-1112.

Marsman, DS; Popp, JA. (1994) Biological potential of basophilic hepatocellular foci and hepatic adenoma induced
by the peroxisome proliferator, Wy-14,643. Carcinogenesis 15:111—117.

Mausner, JS; Kramer, S. (1985) Epidemiology, 2nd ed. Philadelphia: W.B. Saunders.

McConnell, EE. (1992) Comparative response in carcinogenesis bioassay as a function of age at first exposure. In:
Guzelian, P; Henry, CJ; Olin, SS, eds. Similarities and difference between children and adults: implications for risk
assessment. Washington, DC: ILSI Press; pp. 66-78.

McConnell, EE; Solleveld, HA; Swenberg, JA; et al. (1986) Guidelines for combining neoplasms for evaluation of
rodent carcinogenesis studies. JNatl Cancer Inst 76:283-289.

McMichael, AJ. (1976) Standardized mortality ratios and the "healthy worker effect": scratching beneath the
surface. J Occup Med 18:165-168.

Melnick, RL, Huff, JE, Barrett, JC, Maronpot, RR, Lucier, G, Portier, CJ. (1993) Cell proliferation and chemical
carcinogenesis: A symposium overview. Mol Carcinog 7:135-138.

Miller, RW. (1995) Special susceptibility of the  child to certain radiation-induced cancers. Environ Health Perspect
103(suppl 6):41-44.

Monro, A. (1992) What is an appropriate measure  of exposure when testing drugs for Carcinogenicity in rodents?
Toxicol Appl Pharmacol 112:171-181.

Moolgavkar, SH; Knudson, AG. (1981) Mutation and cancer: a model for human carcinogenesis. J Natl Cancer Inst
66:1037-1052.

Morrison, V; Ashby, J. (1994) A preliminary evaluation of the performance of the muta™ mouse (lacZ) and Big
Blue™ (lacl) transgenic mouse mutation assays. Mutagenesis 9:367-375.

Murdoch, DJ; Krewski, D; Wargo, J. (1992) Cancer risk assessment with intermittent exposure. Risk Anal
12(4):569-577.

Murrell, JA; Portier, CJ; Morris, RW. (1998) Characterizing dose-response I: critical assessment of the benchmark
dose concept. Risk Anal 18(l):13-25.

NRC (National Research Council). (1983) Risk assessment in the federal government: managing the process.
Committee on the Institutional Means for Assessment of Risks to Public Health, Commission on Life Sciences,
NRC. Washington, DC: National Academy Press.

NRC. (1990) Health effects of exposure to low levels of ionizing radiation (BEIR V). Washington, DC: National
Academy Press.

NRC. (1993a) Issues in risk assessment. Committee on Risk Assessment Methodology. Washington, DC: National
Academy Press.

NRC. (1993b) Pesticides in the diets of infants and children. Washington, DC: National Academy Press.

NRC. (1994) Science and judgment in risk assessment. Washington, DC: National Academy Press.

NRC. (1996) Understanding risk: informing decisions in a democratic society. Washington, DC: National Academy
Press.
February 27, 2003                              R-5               DRAFT FINAL - DO NOT CITE OR QUOTE

-------
NRC. (2002) Estimating the public health benefits of proposed air pollution regulations. Washington, DC: National
Academy Press.

NTP (National Toxicology Program). (1984) Report of the ad hoc panel on chemical carcinogenesis testing and
evaluation of the National Toxicology Program, Board of Scientific Counselors. Washington, DC: U.S. Government
Printing Office. 1984-421-132:4726.

OECD (Organization for Economic Cooperation and Development). (1981) Guidelines for testing of chemicals.
Carcinogenicity studies. No. 451. Paris, France.

OMB (Office of Management and Budget). (2002) Guidelines for ensuring and maximizing the quality, objectivity,
utility, and integrity of information disseminated by federal agencies. Federal Register 67(36):8451-8460. Available
from: httn:/Avww.cpa.gov/oci/qiialityguidclincs/fr22fc02-l 17.htm.

OSTP (Office of Science and Technology Policy). (1985) Chemical carcinogens: review of the science and its
associated principles. Federal Register 50:10372-10442.

Peltomaki, P; Aaltonen, LA; Sisonen, P; et al. (1993) Genetic mapping of a locus predisposing human colorectal
cancer. Science 260:810-812.

Peto, J. (1992)  Meta-analysis of epidemiological studies of carcinogenesis. In: Mechanisms of carcinogenesis in risk
assessment. IARC Sci. Pubs. No. 116, Lyon, France; pp.  571-577.

Peto, J; Darby, S. (1994) Radon risk reassessed. Nature 368:97-98.

Peto, R; Gray, R; Brantom, P; et al. (1984) Nitrosamine carcinogenesis in 5120 rodents: chronic administration of
sixteen different concentrations of NDEA, NDMA, NPYR and NPIP in the water of 4440 inbred rats, with parallel
studies on NDEA alone of the effect of age of starting (3,6, or 20 weeks) and of species (rats, mice or hamsters).
IARC Sci Publ 57:627-665.

Pinkerton, KE; Joad, J. (2000) The mammalian respiratory system and critical windows of exposure for children's
health. Environ Health Perspect 108(suppl):457-462.

Portier, C. (1987) Statistical properties of a two-stage model of carcinogenesis. Environ Health Perspect 76:125-131.

Rail, DP. (1991) Carcinogens and human health: part 2. Science 251:10-11.

Regulatory Toxicology and Pharmacology.  (1996) 24:126-40

Renwick, AG. (1998) Toxicokinetics in infants and children in relation to the ADI and TDI. Food Addit Contam 15,
Suppl 17-35.

Rice, JM. (1979) Problems and perspective in perinatal carcinogenesis: a summary of the conference. NCI Monogr
51:271-278.

Rothman, KT. (1986) Modem Epidemiology. Boston: Little, Brown and Company.

Rouse, J; Jackson, SP. (2002) Interfaces between the detection, signaling, and repair of DNA damage. Science
297:547-551.

Shelby, MD; Zeiger, E. (1990) Activity of human carcinogens in the Salmonella and rodent bone-marrow
cytogenetics tests. Mutat Res 234:257-261.

Sisk, SC; Pluta, LJ; Bond, JA; et al. (1994) Molecular analysis of lacl mutants from bone marrow of B6C3F1
transgenic mice following inhalation exposure to 1,3-butadiene. Carcinogenesis 15(3):471-477.

Snedecor, GW; Cochran, WG.  (1967) Statistical methods, 6th ed. Ames, Iowa: Iowa State University Press.

Spalding, JW; French, JE; Stasiewicz, S;  Furedi-Machacek, M; Conner, F; Tice, RR; Tennant, RW. (2000)
Responses of transgenic mouse lines p53(+/-) and Tg.AC to agents tested in conventional carcinogenicity bioassays.
Toxicol Sci 53(2)213-223.



February 27, 2003                              R-6               DRAFT FINAL - DO NOT CITE OR QUOTE

-------
Stiteler, WH; Knauf, LA; Hertzberg, RC; et al. (1993) A statistical test of compatibility of data sets to a common
dose-response model. Regul Toxicol Pharmacol 18:392^402.

Subramaniam, RP; Asgharian, B; Freijer, JI; Miller, FJ; Anjilvel, S. (2003) Analysis of differences in particle
deposition in the human lung. Inhalation Toxicol 15:1-21.

Swierenga, SHH; Yamasaki, H. (1992) Performance of tests for cell transformation and gap junction intercellular
communication for detecting nongenotoxic carcinogenic activity. In: Mechanisms of carcinogenesis in risk
identification. IARC Sci. Pubs. No.  116, Lyon, France; pp. 165-193.

Tarone, RE. (1982) The use of historical control information in testing for a trend in proportions. Biometrics
38:215-220.

Taylor, JH; Watson, MA; Devereux, TR; et al. (1994) p53 mutation hotspot in radon-associated lung cancer. Lancet
343:86-87.

Tennant, RW. (1993) Stratification of rodent carcinogenicity bioassay results to reflect relative human hazard. Mutat
Res 286:111-118.

Tennant, RW; French, JE; Spalding, JW. (1995) Identifying chemical carcinogens and assessing potential risk in
short-term bioassays using transgenic mouse models. Environ Health Perspect 103:942-950.

Tennant, RW; Stasiewicz, S; Mennear, J; et al. (1999) Genetically altered mouse models for identifying carcinogens.
In: McGregor, DB; Rice, JM; Venitt, S, eds. The use of short- and medium-term tests  for carcinogens and data on
genetic effects in carcinogenic hazard evaluation. Lyon, France: International Agency for Research on Cancer.

Tinwell, H; Ashby, J. (1991) Activity of the human carcinogen MeCCNU in the mouse bone marrow mironucleus
test. Environ Molec Mutagen 17:152-154.

Todd, GC. (1986) Induction of reversibility of thyroid proliferative changes in rats given an antithyroid compound.
Vet Pathol 23:110-117.

Tomatis, L; Aitio, A; Wilbourn, J; et al. (1989) Human carcinogens so far identified. Jpn J Cancer Res 80:795-807.

U.S. Environmental Protection Agency (U.S. EPA). (1986a) Guidelines for carcinogen risk assessment.  Federal
Register 51(185):33992-34003. Available from: http://www.ena.gov/ncea/raf/.

U.S. EPA. (1986b) Guidelines for mutagenicity risk assessment. Federal Register 51(185):34006-34012. Available
from: http://cfpub.cpa.gov/ncea/raf/rccordisplay.cfrn?deid=23160.

U.S. EPA. (1989) Summary of the second workshop carcinogenesis bioassay with the dermal route. May 18-19,
1988, Research Triangle Park, NC. EPA/560/6-89/003, available from NTIS, 5284 Port Royal Road, Springfield,
VA 22161 (703-487-4650).

U.S. EPA. (1991a) Guidelines for developmental toxicity risk assessment. Federal Register 56(234):63798-63826.
Available from: http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=23162.

U.S. EPA. (1991b) Alpha-2u-globulin: association with chemically induced renal toxicity and neoplasia in the male
rat. Risk Assessment Forum, Washington, DC. EPA/625/3-91/019F.

U.S. EPA. (1992a) Guidelines for exposure assessment. Federal Register 57(104):22888-22938. Available from:
http://cfpuh.epa.gov/ncea/raf/recorclisplav.cfiri7deidH5263.

U.S. EPA. (1992b) Draft report: a cross-species scaling factor for carcinogen risk assessment based on equivalence
of mg/kg3/4/day. Federal Register 57(109):24152-24173.

U.S. EPA. (1994) Methods for derivation of inhalation reference concentrations and application of inhalation
dosimetry. Office of Health and Environmental Assessment, Environmental Criteria and Assessment Office,
Research Triangle Park, NC. EPA/600/8-90/066F.

U.S. EPA. (1995) Policy for risk characterization. Memorandum of Carol M. Browner, Administrator, March 21,
1995, Washington, DC. Available from: http://www.epa.gov/osp/spc/2riskchr.htm.


February 27, 2003                               R-7              DRAFT FINAL - DO NOT CITE OR QUOTE

-------
U.S. EPA. (1996a) Guidelines for reproductive toxicity risk assessment. Federal Register 61(212):56274-56322.
Available from: http://cfpiilxepa.gov/ncea/raf/recordisplay.cfm?deid==2838.

U.S. EPA. (1996b) Comparison of the effects of chemicals with combined perinatal and adult exposure vs. Adult
only exposure in carcinogenesis studies. Office of Pesticide Programs, October 1996.

U.S. EPA. (1997a) A proposed OPP policy on determining the need for perinatal carcinogenicity testing on a
pesticide. Office of Pesticide Programs, 14 August 1997.

U.S. EPA. (1997b) A set of scientific issues being considered by the Agency in connection with the criteria for
requiring in-utero cancer studies.  Office of Pesticide Programs.  FIFRA Scientific Advisory Panel.  September 1997
meeting report. Available from: http://www.CDa.uov/pcsticides/SAP/archivc/september/finalsep.htiTi.

U.S. EPA. (1997c) Exposure factors handbook. National Center for Environmental Assessment, Washington, DC.
EPA/600/P-95/002F. Available from: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfi-n?deid=12464.

U.S. EPA. (1997d) Policy for use of probabilistic analysis in risk assessment. Memorandum of Fred Hansen, Deputy
Administrator, May 15, 1997. Available from: http://www.epa. gov/osp/spc/probpol .htm.

U.S. EPA. (1997e) Guiding principles for Monte Carlo analysis.  Risk Assessment Forum, Washington, DC.
EPA/630/R-97/001. Available from: http://cfpub.cpa.gov/ncca/raf/recordisplay.cfm?deid=29596.

U.S. EPA. (1998a) Assessment of thyroid follicular cell tumors.  Risk Assessment Forum, Washington, DC.
EPA/630/R-97/002. Available from: http://cfpub.cpa.gov/ncca/raf/rccordisplav.cfm?deid=13102.

U.S. EPA. (1998b) Guidelines for neurotoxicity risk assessment. Federal Register 63(93):26926-26954. Available
from: hltp://cfpub.cpa.gov/ncca/raf/rccordisplav.cfm?dcid=12479.

U.S. EPA. (1998c) Health effects test guidelines: OPPTS 870.4300 combined chronic toxicity/carcinogenicity.
Office of Prevention, Pesticides and Toxic Substances, Washington, DC. EPA/712/C-98/212. Available from:
http://www.epa.gov/opptsfrs/OPPTS  HarmonJ7ed/870 Health Effects Test Guidelines/Series/

U.S. EPA. (1998d) EPA's rule writer's guide to Executive Order 13045. Available from:
http://yosemite.epa.gov/ochp./ochpweb.nsf/content/whatwe regulate.htm

U.S. EPA. (1999a) Guidelines for carcinogen risk assessment (review draft). Risk Assessment Forum, Washington,
DC. NCEA-F-0644. Available from:  http://www.epa.gov/ncea/raf./cancer.htm.

U.S. EPA. (1999b) Review of revised sections of the proposed guidelines for carcinogen risk assessment. Science
Advisory Board, Washington, DC. EPA/SAB/EC-99/015. Available from: http://www.epa.gov/ncea/raf/canccr.htm.

U.S. EPA. (1999c) Cancer risk coefficients for environmental exposure to radionuclides: federal guidance report no.
13. Office of Air and Radiation. EPA/402/R-99/001. Available from: http://www.cpa.gov/radiation/federal.

U.S. EPA. (2000a) Science Policy Council handbook: peer review. Office of Research and Development, Office of
Science Policy, Washington, DC. EPA/100/B-98/001. Available from: http://www.epa.gov/osp/spc/prhandbk.pdf.

U.S. EPA. (2000b) U.S. EPA. Science Policy Council handbook: risk characterization. EPA Science Policy Council,
Washington, DC. EPA/1 OO/B-00/002. Available from: http://www.epa.gov/osp/spc/rchandbk.pdf

U.S. EPA. (2000c) Supplementary guidance for conducting health risk assessments of chemical mixtures. Risk
Assessment Forum, Washington, DC. EPA/630/R-00/002. Available from:
http://cfpub.epa.gov7ncca''rat7recordisplay.cfin?dcid=20533.

U.S. EPA. (2000d) Guidance for data quality assessment: practical methods for data analysis. Office of
Environmental Information, Washington, DC. EPA/600/R-96/084. Available from:
http://\vwvv.cpa.gov/qiialitv/qs-docs/g9-final.pdf.

U.S. EPA. (2002a) Guidelines for ensuring and maximizing the quality, objectivity, utility and integrity for
information disseminated by the Environmental Protection Agency. Office of Environmental Information,
Washington, DC. EPA/260/R-02/008. Available from: http://mvw.epa.gov/oei/qualitvguidclines/iridex.ritml.


February 27, 2003                               R-8               DRAFT FINAL - DO NOT CITE OR QUOTE

-------
U.S. EPA. (2002b) A review of the reference dose and reference concentration process (external review draft). Risk
Assessment Forum, Washington, DC. EPA/630/P-02/002A. Available from:
http://cfnub.epa. gov/ncea/raf7recordisplav.cfm?deid=51717.

U.S. EPA. (2002c) Workshop on the benefits of reductions in exposure to hazardous air pollutants: developing best
estimates of dose-response functions. Science Advisory Board, Washington, DC. EPA/S AB-EC/WKSHP/02/001.
Available from: http://wvvw.cpa.gov/sciencel/fiscal02.htm.

U.S. EPA. (2002d) Child-specific exposure factors handbook (interim report). EPA/600/P-00/002B. Office of
Research and Development, National Center for Environmental Assessment, Washington, DC, 448 pp. Available
from: http://cfpub.cpa.gov/ncca/cfm/rccordisplay.cfm?deid=55145.

U.S. EPA. (2003) Supplemental guidance for assessing cancer susceptibility from early-life exposure to carcinogens
(external review draft). Risk Assessment Forum, Washington, DC. Available from:
http://www.epa.gov/ncca/raF/cance^OOS.htm.

Vainio, H; Magee, P; McGregor, D; et al. (1992) Mechanisms of carcinogenesis in risk identification. IARC Sci.
Pubs. No. 116. Lyon, France: IARC.

Van Sittert, NJ; De Jong, G; Clare, MG; et al. (1985) Cytogenetic, immunological, and hematological effects in
workers in an ethylene oxide manufacturing plant. Br J Indust Med 42:19-26.

Vater, ST; McGinnis, PM; Schoeny, RS; et al. (1993) Biological considerations for combining carcinogenicity data
for quantitative risk assessment. Regul. Toxicol Pharmacol 18:403^18.

Vesselinovitch, SD; Rao, KVN; Mihailovich, N. (1979) Neoplastic response of mouse tissues during perinatal age
periods and its significance in  chemical carcinogenesis. NCI Monogr 51:239.

Vogelstein, B; Fearon, ER; Hamilton, SR; et al. (1988) Genetic alterations during colorectal-tumor development. N
EngJ Med 319:525-532.

Whysner, J; Williams, GM. (1996) Saccharin mechanistic data and risk assessment: urine composition, enhanced
cell proliferation, and tumor promotion. Pharmacol Ther 71: 225:252.

Woo, YT; Arcos, JC. (1989) Role of structure-activity relationship analysis in evaluation of pesticides for potential
carcinogenicity. In: Ragsdale, NN; Menzer, RE, eds. Carcinogenicity and pesticides: principles, issues, and
relationship. ACS Symposium Series No. 414. San Diego: Academic Press; pp. 175-200.

Yamasaki, H. (1995) Non-genotoxic mechanisms  of carcinogenesis: Studies of cell transformation and gap
junctional intercellular communication. Toxicol Lett 77:55-61.
February 27, 2003                               R-9              DRAFT FINAL - DO NOT CITE OR QUOTE

-------