EPA/600/A-96/1
Health Risk Assessment of Environmental Agents:
Incorporation of Emerging Scientific Information
Vicki L. Dellarco, William H. Farland, and Jeanette A. Wiltse
U.S. Environmental Protection Agency
National Center for Environmental Assessment
Office of Research and Development
Washington, D.C.
CORRESPONDENCE: Dr. Vicki L. Dellarco, U.S. Environmental Protection Agency,
National Center for Environmental Assessment (8601), 401 M St., S.W., Washington, DC
20460, USA; telephone: (202) 260-7336; FAX: (202) 260-0393; E-mail:
DeIlarco.Vicki@epamail.epa.gov.
DISCLAIMER: Although this article has been subjected to review and approved for
publication, it does not necessarily reflect the views and policies of the U.S.
Environmental Protection Agency. The opinions expressed within this article reflect the
views of the authors. The U.S. Government has the right to retain a nonexclusive royalty
free license in and to any copy right covering this article.
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Contents
L Introduction
IL Evolution of Hazard Assessment
A. Expanding Role of Mechanistic Information
B. Conditions of Hazard Expression
C. Variation in Human Susceptibility
D. Integrative Analysis of Cancer and Noncancer Health Effects
m. Trends in Dose-Response Assessment
A. Modeling in the Observed Range for Both Cancer and Noncancer Risks
B. The Range of Extrapolation for Cancer Risks
C. Modeling of Cancer Precursor Response Data
IV. Emerging Directions in Exposure Assessment
V. Emphasis on Risk Characterization
VI. Summary
References
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L Introduction
The objective of the U.S. Environmental Protection Agency's (EPA) risk
assessments are to support environmental decision making. Assessments of risks to
environmental agents serve not only the regulatory programs of the EPA but also State
and local agencies, as well as international communities that are addressing environmental
issues. The ingredients of health risk assessment include information on whether a
chemical produces adverse health effects, how the frequency of adverse effects changes
with dose, and to what degree and under what conditions people may be exposed as
pollutants travel in the environment. The primary sources of inforaiation forjudging
human risk are human epidemiologic and animal toxicological studies, and other empirical
information such as genotoxicity, structure-activity relationship, and exposure data. Risk
assessments rely on studies in animals because human data are not usually available. The
health-related information available on agents is typically incomplete. Moreover, health
risk assessments on environmental agents must usually address the potential for harm from
exposure levels found in the environment that are usually lower than concentrations at
which toxicity is found in laboratory animal or epidemiologic studies. Thus, the
extrapolations that are required to project human risk (i.e., from high to low doses, from
nonhuman species to human beings, from one route to another route of exposure)
inherently introduce uncertainty.
Given that extrapolations must be performed, risk assessment is complex and often
controversial. EPA develops risk assessment guidelines to provide staff and decision
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makers with guidance and perspectives necessaiy to develop and use effective health risk
assessments. Guidelines also encourage consistency in procedures to support decision
making across the many EPA programs. The following lists the risk assessment guidelines
that EPA has published:
• Carcinogenicity (1)(2)
• Mutagenicity (3)
• Developmental toxicity (4)
• Reproductive toxicity (5)
• Neurotoxicity (6)
• Exposure (7)
• Complex mixtures (8).
EPA recently proposed new cancer risk assessment guidelines to bring current and
relevant science into future assessments and to promote research that applies new
knowledge to specific pollutants. There have been significant gains in our understanding of
the cellular and subcellular processes that result in cancer, and these advances have
enabled research on the ways environmental contaminants act on cells to cause cancer.
These new guidelines will be discussed throughout this article as an illustration of how
new science is impacting and improving the characterization of potential human risk.
Health risk assessment practices are evolving on a number of fronts (see Table 1).
Risk analyses have historically relied to a large degree on observations of frank toxic
effects (e.g., tumors, malformations). Risk assessments are moving from this
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phenomenologic approach by identifying the ways environmental agents are changed
though metabolic processes, the dose at the affected organ system, and how an agent
produces its adverse effects at high doses and at low ones. This understanding of how an
agent produces its toxic effect is beginning to break down the dichotomy that has existed
between assessments of cancer and noncancer risks. Of equal importance, the "one-size-
fits-all" approach is being replaced by emphasizing the ascertainment of risk to susceptible
subpopulations. EPA recently put forth a new national agenda to protect children from
tone agents in the environment (9). In addition, to make risk assessments more
understandable and useful, there is an increased emphasis on risk characterization. Risk
characterization is the final output of the risk assessment process from which all preceding
analyses (i.e., from the hazard, dose-response, and exposure assessments) are tied
together to convey in nontechnical terms the overall conclusions about potential human
risk, as well as the rationale, strengths, and limitations of the conclusions.
This article discusses several trends occurring in risk assessment in the context of the
risk paradigm—hazard, dose-response, and exposure assessments and subsequent risk
characterization (see Figure 1). Chemical examples are provided to illustrate these
emerging directions in health risk assessment.
n. Evolution of Hazard Assessment
In its 1994 report about the use of science and judgment in risk assessment, the
National Research Council of the National Academy of Science recommended that EPA
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incorporate technical characterizations of risk that are both qualitative and quantitative in
its assessments (10). Thus, hazard identification as well as dose-response and exposure
analyses are changing by the increased emphasis on providing characterization discussions.
These technical characterizations essentially reveal the thought process that leads to the
scientific judgments of potential human risk. The technical hazard characterization
explains the extent and weight of evidence, major points of interpretation and rationale,
strengths and weaknesses of the evidence, and discusses alternative conclusions and
uncertainties that deserve serious consideration. The technical hazard characterization
along with those for the dose-response and exposure assessments are the starting
materials for the risk characterization process (see Section V) that completes the risk
assessment. As shown in Figure 2, this concept of technical hazard characterizations has
been incorporated into EPA's revised Guidelines for Carcinogen Risk Assessment (2).
A. Expanding Role of Mechanistic Data
Hazard assessment is moving beyond relying on traditional toxicology by using a
weight-of-evidence (WoE) approach that considers all relevant data and the mode of
action of the given agent. It is the sum of the biology of the organism and the chemical
properties of an agent that leads to an adverse effect. Thus, it is an evaluation of the entire
range of data (e.g., physical, chemical, biological, toxicological, clinical, and
epidemiological information) that allows one to arrive at a reasoned judgment of an
agent's potential to cause human harm. For example, EPA has proposed a major change in
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the way hazard evidence is weighed in reaching conclusions about the human carcinogenic
potential of environmental agents (2)(11). Rather than relying heavily on tumor findings,
the full use of all relevant information is promoted and an understanding of how the agent
induces tumors is emphasized. Under the proposed revisions to EPA's 1986 Guidelines for
Carcinogen Risk Assessment (1), a short WoE narrative is derived from the longer
technical hazard characterization. The WoE narrative is intended for risk managers and
other users, and it replaces the current six alphanumeric classification categories; A,
human carcinogen; B1/B2, probable human carcinogen; C, possible human carcinogen; D,
not classifiable, and E, evidence of noncarcinogenicity. This narrative explains in
nontechnical language the key data and conclusions, as well as the conditions for hazard
expression. Conclusions about potential human carcinogenicity are presented by route of
exposure. Contained within this narrative are simple likelihood descriptors that essentially
distinguish whether there is enough evidence to make a projection about human hazard
(i.e., known human carcinogen, should be treated as if known, likely to be a human
carcinogen, or not likely to be a human carcinogen) or whether there is insufficient
evidence to make a projection (i.e., the cancer potential cannot be determined because
evidence is lacking, conflicting, inadequate, or because there is some evidence but it is not
sufficient to make a projection to humans). Because one encounters a variety of data sets
on agents, these descriptors are not meant to stand alone; rather, the context of the WoE
narrative is intended to provide a transparent explanation of the biological evidence and
how the conclusions were derived. Moreover, these descriptors should not be viewed as
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classification categories (like the alphameric system), which often obscure key scientific
differences among chemicals. The new WoE narrative also presents conclusions about
how the agent induces tumors and the relevance of the mode of action to humans, and
recommends a dose-response approach based on the mode-of-action understanding (see
Section III.B), Some examples of how mechanistic information on chemicals has informed
risk assessments or provided a better basis for interpreting the meaning of efforts from
animal data and its relevance to humans are given in the following subsections.
1. a2n Nephropathy and Kidney Cancer
The development of male rat kidney tumors mediated by a ^-globulin is one of the
more thoroughly studied processes in cancer toxicology. Exposure to several agents, such
as 2,2,4-trimethylpentane (and unleaded gasoline) and af-limonene, have been reported to
result in an accumulation of protein droplets containing a2(l-gIobulin in the epithelial cells
of the proximal convoluted tubules of male rat kidneys (12)( 13)(14)( 15). This protein
accumulation is thought to result in renal cell injury and proliferation, and eventually renal
tubule tumors. Female rats and other laboratory animals do not accumulate this protein in
the kidney and, when exposed to alphas-globulin inducers, do not develop an increased
incidence of renal tubule tumors. The manner in which the human male responds to such
agents is uncertain. This mechanism appears to be specific to the rat given the results from
studies of other laboratory species, and given the high doses that are needed to produce an
effect in the male rat.
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In 1991, EPA concluded that the sequence of events proposed to link a2|1-globulin
accumulation to nephropathy and renal tubule tumors in the male rat is plausible, although
not totally proven; that the a2fl-globulin response following chemical administration
appears to be unique to the male rat; and that the male rat kidney response to chemicals
that induce a2(1-globulin is probably not relevant to humans for purposes of risk
assessment (15). However, when chemically induced a2jl-globuIin kidney tumors are
present, other tumors in the male rat and any tumor in other exposed laboratory animals
may be important in evaluating the carcinogenic potential of a given chemical. Some
investigators think that the issue of a2(1 nephropathy and kidney cancer is not resolved and
have proposed alternative hypothesis (16). Should significant new information on a2(1-
globulin kidney tumors become available, EPA will update its policy position accordingly.
2. Perturbation of Pituitary-Thyroid Homeostasis and Thyroid Cancer
The ways in which antithyroid compounds induce thyroid tumors are also reasonably
well understood, even though the precise molecular events leading to thyroid follicular cell
tumors are not totally described. Experimental findings in rodents have shown that
perturbation of hypothalamus-pituitary-thyroid homeostasis leads to elevated thyroid-
stimulating hormone (TSH) levels, which in turn results in increased DNA synthesis and
cell proliferation, and eventually to thyroid gland tumors (17)(1S)(19)(20). Thus, thyroid
tumors are secondary to a hormone imbalance. Agents with antithyroid activity include
sulfamethazine and other thionamides. There is uncertainty whether prolonged stimulation
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of the human thyroid by TSH may lead to cancer. Because this possibility cannot be
dismissed, it is presumed that chemicals that produce thyroid tumors in rodents may pose
a carcinogenic risk to humans. Humans (including other primates) are thought to be
substantially less sensitive than rats to this mechanism.
One factor that may account for the interspecific difference in sensitivity concerns
the influence of protein carriers of thyroid hormones in the blood. Rodent thyroid
hormones are more susceptible to removal from the body because of the lack of a high-
affinity binding protein, which humans possess (21). In the rat, there is chronic stimulation
of the thyroid gland by TSH to compensate for the increase turnover of thyroid hormones.
This may render the rat more sensitive to disturbances in TSH levels. EPA has recently
proposed science policy guidance on the consideration of thyroid carcinogenesis in risk
assessment(20). Briefly, it is proposed that chemicals that produce rodent thyroid tumors
should be presumed to pose a hazard to humans; evaluations of human thyroid cancer risk
from long-term perturbations of pituitary-thyroid function in rodents should incorporate
considerations about potential interspecific differences in sensitivity and evaluate the
applicability of potential human exposure patterns in relation to the findings in animal
models. Dose-response approaches should be based on mode-of-action information;
application of nonlinear approaches are appropriate for those nonmutagenic chemicals
shown to cause a hormonal imbalance. However, those antithyroid compounds with
mutagenic activity need to be carefully evaluated on a case-by-case basis.
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3. Bladder Calculi and Tumors
Another situation for which the rat appears to be quantitatively more sensitive than
humans is the induction of bladder tumors secondaiy to bladder calculi-induced
hyperplasia. Cohen and Ellwein (22) reported that if the administered dose of a chemical
(e.g., for melamine, uracil, calcium oxalate, orotic acid, glycine) is below the level that
causes calculus formation, there is no increase in cell proliferation; consequently, there is
no increase in bladder tumors. Thus, calculus-forming compounds would have a threshold
of response. EPA has considered this in its assessment of melamine (23),
4. Formaldehyde and Nasal Tumors
The understanding of formaldehyde carcinogenicity has developed over a number of
years since Kerns et. al. (24) demonstrated that inhalation exposure to formaldehyde
caused nasal squamous cell carcinomas in mice and rats. In 1991, the carcinogenicity of
formaldehyde was reassessed using data from rats and monkeys: Levels ofDNA protein
cross-links (DPX) were evaluated with a linearized multistage (LMS) model (25). Using
DPX as a more precise measure of dose resulted in risk estimates that were significantly
lower than those derived by using external exposure only. Although the mechanisms of
formaldehyde carcinogenesis are not completely understood, data have continued to
provide additional insight into the cancer risk associated with low-dose exposure to
inhaled formaldehyde by defining more precisely the location of the nasal tumors in the rat,
determining rates of cell proliferation in the nose, and establishing the delivered dose (i.e.,
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levels of DPX) to the target tissue as well as rates of repair of DPXs after repeated
exposures (26)(27)(28)(29). Precursor response data also may have implications in the
estimation of risk to humans. In the rat, the dose-response relationships of induction of
nasal tumors and of cell proliferation correspond and are both highly nonlinear (28). DPXs
do not accumulate; and although the dose-response relationship is linear in the range of
tumor induction and increase cell replication, the slope is greater than at lower dose ranges
due to saturation of detoxification (26). Although formaldehyde is a mutagenic
carcinogen, the data on tumors, cellular kinetics, and molecular dosimetry indicate that the
dose-response relationship is not linear throughout the entire range, but is subject to an
upward curvature due to increased cell proliferation.
B. Conditions of Hazard Expression
As mentioned earlier, hazard assessment has expanded from simply identifying
adverse effects to fuller technical characterizations of a particular hazard. One dimension
critical to characterizing hazard potential is the concept of hazard expression (i.e., What
are the circumstances under which a particular hazard is expressed?). For example, an
agent may not carry the same hazard potential for different routes of exposure. Inhalation
exposure to vinyl acetate (600 parts per million) produces statistically significant increases
in nasal tumors in rats, where as no statistically significant increases in tumors are
observed when the compound is ingested orally via drinking water (30)(31). Likewise, a
compound's carcinogenicity may be dose limited. Although methylmercury has been
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shown to produce tumors in mice at high doses (32), it is unlikely to pose a hazard to
humans at low doses. Conditions of hazard expression may not only involve exposure
conditions (e.g., route, magnitude, or duration) but may depend on biological and
physiological processes.
Studies on metabolism may provide pertinent data about the circumstances that
affect hazard expression. The biotransformation of many chemicals to reactive compounds
is dependent on the presence of certain metabolic pathways (e.g., oxidative pathways
involving P450 cytochromes or conjugation pathways involving glutathione S-transferases).
For example, 1,3-butadiene is carcinogenic in rats and mice, with mice being more
sensitive to tumor induction than rats (33)(34). It is thought that the carcinogenic potential
of 1,3-butadiene is dependent on metabolic activation to reactive metabolites, which
interact with DNA. For example, metabolism of 1,3-butadiene to reactive epoxides is
substantially greater in mice than in rats (35)(36)(37). Although it has been reported that
humans exposed to 1,3-butadiene show a higher incidence of chronic leukemia (38), the
available metabolic studies suggest that humans may not be as highly susceptible as mice.
Thus, metabolizing enzymes can account for different susceptibilities among species.
Other biological factors that can result in differences in sensitivity include age, sex, or
preexisting diseases. These factors that may contribute to special sensitivity to a given
agent as discussed further in the following section.
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C. Variation in Human Susceptibility
Certain individuals may be at an increased risk because their activity patterns
increase their exposure or because their proximity to a source means higher exposures to
environmental contaminants. Humans also may vary in their susceptibility to toxicity
because of preexisting disease conditions or differences in age, gender, metabolism, or
genetic makeup. For example, a number of studies have shown the role of carcinogen-
metabolizing enzyme polymorphisms in cancer susceptibility (reviewed in Ref. (39)), of
which the most convincing is for the association of the GSTM1 homozygous genotype
and the CYP1A1 rare alleles with lung cancer in Japanese (40)(41). Gene-environmental
interactions have also been shown to be important to an elevated risk for developmental
defects. For example, genetic variation of transforming growth factor-alpha and maternal
smoking have been associated with increased risk for delivering infants with cleft lip or
palate (42)(43). Human responses may vary due to environmental exposures during
different periods of the life cycle. Exposures of the fetus or neonate may disrupt
developing systems, thereby resulting in increased sensitivity. EPA has consider in its risk
assessments subgroups with a high sensitivity to environmental pollutants, as evinced by
the National Ambient Air Quality Standards for air pollutants and lead. Two examples are
discussed in the following subsections.
1. Methylmereury and Neurobehavorial Effects in Children
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Mercury is ubiquitous and persistent in the environment. It occurs in both natural
(e.g., volcanoes, soils, wildfires) and industrial (e.g, coal combustion, mining, waste
incineration) sources. A form of mercury that is particularly hazardous to humans is
methylmercury. A primary pathway of human exposure is by consuming fish that have
accumulated methylmercury. Microorganisms in the sediment of the earth's waters can
convert mercury into methylmercury. It is well established that methylmercury is a
neurotoxin (44). The developing nervous system of the fetus is especially sensitive to the
effects of methylmercuiy. Animal and human studies indicate that in utero exposure to
methylmercury can potentially result in adverse neurobehavioral effects on children.
To protect sensitive subpopulations (e.g., infants exposed pre- and postnatally), in
1995 EPA established a reference dose (i.e., a quantitative estimate of levels expected to
be without effects) of 1 * 10~4 mg/kg/day based on available human studies in Iraq (45).
This study was based on 81 infant-mother pairs that had consumed seed grain that had
been fumigated with methylmercury. The results of two recent epidemiologic studies of
fish-eating populations—one in the Seychelles Islands and the other in the Faeroe
Islands—are anticipated to shed further light on the dose-response issues associated with
the oral intake of methylmercury intake via contaminated food. It should be noted, like
exposure to lead, the neurological effects associated with low exposures to methylmercury
may be subtle and delayed, thus making it difficult to identify in young children. Lead is
one of the best studied examples of prenatal exposure and it subsequent affects on
cognitive and behavioral development of young children (46). EPA as well as other
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Federal agencies have published strategy documents in an effort to reduce children's
exposure to lead (47)(48)(49).
2. Air Pollution and Respiratory Effects in the Elderly and Children
The elderly (65 years and older) make up another population susceptible to
environmental pollution. For example, several morbidity (e.g., hospital admissions) and
mortality studies provide evidence that the elderly (especially those with underlying
respiratory or cardiac diseases) are more susceptible to the short- and long-term effects of
particulate air pollution than are young healthy adults (50X51)(52)(53). Particulate air
pollution might aggravate the severity of preexisting chronic respiratory or cardiac
diseases. Approximately 40% of people over 75 years old have some form of heart
disease, 35% have hypertension, and 10% have chronic obstructive pulmonary disease
(e.g., asthma) (53). Also, the elderly have had more cumulative exposure over their life
span and hence more opportunity to accumulate particles or damage in their lungs.
Although there is an association of short-term, low-level ambient exposure to particulate
matter and excess mortality or morbidity among the elderly, the biological plausibility of
these findings remains unclear. The few studies available also suggest that children,
particularly those with preexisting respiratory diseases, may be potentially more
susceptible than the general population to the pulmonary effects of air pollution (53)(54).
(
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D. Integrative Analysis of Cancer and Noncancer Health Effects
In evaluating health risks posed by environmental agents, EPA considers both cancer
and noncancer effects. Some of the noncancer effects specifically considered are
developmental and reproductive toxicity, neurotoxicity, immunotoxicity, and respiratory
toxicity, as well as systemic organ toxicities. Historically, assessments have been done
separately and very differently for cancer and noncancer health effects. An important
direction in assessments of environmental agents is to provide more integrated
characterizations of cancer and noncancer health effects. The dichotomy between cancer
and noncancer is beginning to break down with a better undemanding of the mechanisms
of toxicity. Also, the quantitative approaches are merging as discussed in Section HI. The
underlying basis for certain noncancer toxicities and cancer may have several
commonalties. For example, chemically induced toxicity can cause cell death. Surviving
cells may then compensate for that injury by increasing cell proliferation (hyperplasia),
which may underlie many types of toxic responses. If this proliferative activity continues
unchecked, it may result in tumors. Chemicals may modulate or alter gene expression via
receptor interactions. Thus, receptor-mediated pathways may play a role in both
carcinogenesis and other organ system toxicities. For example, 2,3,7,8-
tetrachlorodibenzo-p-dioxin and dioxin-like compounds bind to the Ah receptor, which
may represent the first step in a series of events leading to cellular and tissue changes in
normal biological processes. Thus, dioxin (and dioxin-like compounds) may exert its
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carcinogenic, immunologic, and reproductive effects via Ah receptor-dependent events
(55)(56)(57).
EPA is attempting to integrate combined human health and ecological risk
assessments to ensure that decision makers at all levels have an integrated view of risk,
which is essential to making sound decisions. Human health and ecological assessments
make use of similar data. For example, studies of piscivorous birds that have consumed
methylmercury-contaminated fish show neurobehavioral effects similar to those of
exposed human beings (58)(59). A recent concern has been raised in the news (e.g.,
Esquire and The New Yorker> January 1996) and among scientists about the accumulation
in the environment of chemicals (e.g., pesticides like DDT/DDE and kepone, certain
polychlorinated biphenyls) that may mimic natural sex hormones. There have been several
reports suggesting that a decline in sperm number in human males over the last 50 years
(60), as well as effects on male reproduction in wildlife species (e.g., male alligators
exposed to pesticides in Florida's Lake Apolka with reduced genitalia). For example, DDE
(1,1,1 -trichloro-2,2-bis(p-chlorophenyl)ethane)—which was shown to cause reproductive
failure (due to eggshell thinning) in birds over two decades ago—has been shown to
inhibit androgen binding to the androgen receptor, which may account for its account for
its ability to alter male reproductive development (61). Because wildlife species and
domestic animals share the same environment with humans and are in the human food
web, these nonhuman species serve as sentinels for potential human health risks posed by
environmental contaminants (for review see Ref.(62)).
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IIL Trends in Dose-Response Assessment
Historically, dose-response assessment has been done very differently for cancer and
noncancer health effects. For nearly two decades, EPA has modeled tumor risk by a
default approach based on the assumption of low-dose linearity. To estimate human cancer
risk, the LMS model was applied, which extrapolates risk as the 95% upper-bound
confidence interval (1)(63)(64). The standard practice for noncancer health assessment has
assumed the existence of a threshold for adverse effects. Acceptable exposures for
chemicals causing noncancer effects have been estimated by applying uncertainty factors
(UFs) to a determined no-observed-adverse-effect level (NOAEL), which is the highest
dose at which no adverse effects have been detected. If a NOAEL cannot be established,
then a lowest-observed-adverse-effect level (LOAEL) is determined for the critical effect.
The UFs may be as much as 10 each and are intended to account for limitations in the
available data, such as human variation, interspecific differences, lack of chronic data, or
lack of certain other critical data. In the reference concentration (RfC) method, the
composite UF for interspecific differences is 3 because of dosimetric adjustments (65)(66).
The NOAEL (or LOAEL) is divided byUFs o establish a reference dose (RfD) for oral
exposures or an RfC for inhalation exposures, which is an estimate (with uncertainty
spanning perhaps an order of magnitude) of daily exposure (RfD) and continuous
exposure (RfC) that is likely to be without an appreciable risk of deleterious effects during
a lifetime (66)(65)(67)(68)(69). RfDs and RfCs are not derived using composite UFs
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greater than 10,000 and 3,000, respectively. The NOAEL can be compared with the
human exposure estimate to derive a margin of exposure.
A. Modeling in the Range of Observation for Both Cancer and Noncancer Risks
With recent proposals to model response data in the observable range to derive
points of departure1 both for cancer and noncancer endpoints (2)(44), EPA health risk
assessment practices are beginning to come together. The modeling of observed response
data to identify points of departure in a standard way will help to harmonized cancer and
noncancer dose-response approaches and permit comparisons of cancer and noncancer
risk estimates.
1. Benchmark Dose Approach; Noncancer Assessment
The traditional NOAEL approach for noncancer risk assessment has often been a
source of controversy and has been criticized in several ways. For example, experiments
involving fewer animals tend to produce larger NOAELs and, as a consequence, may
produce larger RfDs or RfCs. The reverse would seem more appropriate in a regulatory
context because larger experiments should provide greater evidence of safety. The focus
of the NOAEL approach is only on the dose that is the NOAEL, and the NOAEL must be
one of the experimental doses. Moreover, it also ignores the shape of the dose-response
'Point of departure is conceptually similar to benchmark dose, which has been used for noncancer assessment,
(
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curve. Thus, the slope of the dose response plays little role in determining acceptable
exposures for human beings. These and other limitations prompted development of the
alternative approach of applying uncertainty factors to a benchmark dose (BMD) rather
than to a NOAEL (70). Essentially, the BMD approach folly uses all of the experimental
data to fit one or more dose-response curves for critical effects that are, in turn, used to
estimate a BMD that is typically not far below the range of the observed data. The BMD
approach allows for a more objective approach in developing allowable human exposures
across different study designs encountered in noncancer risk assessment.
The BMD is defined as a statistical lower confidence limit (CL) on the dose
producing a predetermined level of change in adverse response (BMR) compared with the
response in untreated animals (70). The choice of the BMR is critical. For quantal
endpoints, a particular level of response is chosen (1%, 5%, or 10%). For continuous
endpoints, the BMR is the degree of change from controls and is based on what is
considered a biologically significant change. The methods of CL calculation and choice of
CL (90%, 95%) are also critical. The choice of extra risk versus additional risk is based to
some extent on assumptions about whether an agent is adding to the background risk.
Extra risk is viewed as the default because it is more conservative. Several RfCs and an
RfD based on the BMD approach are included in the EPA's Integrated Risk Information
System (IRIS) Database.2 These include methylmercury based on delayed postnatal
can be accessed via the Internet at http://vvww.epa.gov/ngispgm3/IRIS/index.html, or call (513) 569-7254
( for more information.
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development in humans, carbon disulfide based on neurotoxicity, 1,1,1,2-tetrafluoroethane
based on testicular effects in rats, and antimony trioxide based on chronic pulmonary
interstitial inflammation in female rats. It should be noted that the BMD approach is still
under discussion and development. The BMD approach is further discussed in Refs. (70),
(71), (72), (73).
2. Two-Step Process for Cancer Dose-Response Assessment
EPA recently proposed to replace its method for extrapolating low-dose cancer risk
by applying the LMS procedure. Instead, it would apply a two-step process that
distinguishes between what is known (i.e., the observed range of data) and what is not
known (i.e., the range of extrapolation) (2)(11). Thus, the first step involves modeling
response data in the empirical range of observation (Figure 3). The proposed guidelines
indicate a preference for modeling with a biologically based (74) or case-specific model.
Because the parameters of these models require extensive data, it is anticipated that the
necessary data to support these models will not be available for most chemicals and that
modeling in the observed range will probably be done most often with an empirical curve-
fitting approach. A point of departure is determined from this modeling. A standard point
of departure was proposed (and which is subject to public comment) as the lower 95% CL
on a dose associated with 10% extra risk (LED10). Other points of departure may be
appropriate (e.g., if a response is observed below an increase in response at 10%). The
objective is to determine the lowest reliable part of the dose-response curve for the
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beginning the second step of the process—the extrapolation range (discussed in the next
section). For some data sets (e.g., certain continuous data), estimating an LOAEL or
NOAEL may be more suitable than determining a point of departure.
B. The Range of Extrapolation for Cancer Risk
The second step involves extrapolation below the range of observation. As
mentioned earlier, a biologically based or case-specific model is preferred for extrapolating
low-dose risk. If the available data do not permit such approaches, the proposed
guidelines provide for several default extrapolation approaches (linear, nonlinear, or both),
which begin with the point of departure. The extrapolation default approach that is taken
should be based on the mode-of-action understanding about the agent. As discussed
earlier, the understanding of the underlying biological mechanisms as they vary from
species to species, from high dose to low dose, and from one route of exposure to another
drives the choice of the most appropriate extrapolation approach. Thus, in the new
guidelines, the dose-response extrapolation procedure follows conclusions about mode of
action in the hazard assessment. The term mode of action is deliberately chosen in these
new guidelines in lieu of mechanism to indicate using knowledge that is sufficient to draw
a reasonable working conclusion without having to know the processes in detail, as the
term mechanism might imply. Although an induced adverse effect may result from a
complex and diverse process, a risk assessment must operationally dissect the presumed
23
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critical events, at least those that can be measured experimentally, to derive a reasonable
approximation of human risk.
1. Default Extrapolation Approaches
The LMS procedure of the 1986 guidelines (1) for extrapolating risk from upper-
bound confidence intervals is no longer recommended as the linear default in the 1996
proposed guidelines (2). The linear default in the new guidelines is a straight-line
extrapolation to the origin (i.e., zero dose, zero extra risk) from the point of departure
(i.e., the LED10) identified in the range of observed data (Figure 3). The new linear default
approach does not imply unfounded sophistication as extrapolation with the LMS
procedure does. The linear default approach would be considered for agents that directly
affect growth control at the DNA level (e.g., carcinogens that directly interact with DNA
and produce mutations). There might be modes of action other than DNA reactivity that
are better supported by the assumption of linearity. When inadequate or no information
exists to explain the carcinogenic mode of action of an agent, the linear default approach
would be used as a science policy choice in the interest of public health. Likewise, a linear
default would be used if evidence demonstrates the lack of support for linearity (e.g., lack
of direct DNA reactivity and mutagenicity) and there is also an absence of sufficient
information on another mode of action to explain the induced tumor response. The latter is
also a public health protective policy choice.
*'
t
24
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Although the understanding of the mechanisms of induced carcinogenesis likely will
never be complete for most agents, there are situations for which evidence is sufficient to
support an assumption of nonlinearity. Because it is experimentally difficult to distinguish
modes of actions with true "thresholds" from others with a nonlinear dose-response
relationship, the proposed nonlinear default procedure is considered a practical approach
to use without the necessity of distinguishing sources of nonlinearity. In the 1996
proposed cancer guidelines (2), the nonlinear default approach begins at the identified
point of departure and provides a margin-of-exposure (MoE) analysis rather than
estimating the probability of effects at low doses (Figure 3). The MoE analysis is used to
compare the point of departure with the human exposure levels of interest. The MoE is
the point of departure divided by the environmental exposure of interest. The key
objective of the MoE analysis is to describe for the risk manager how rapidly responses
may decline with dose. A shallow slope suggests less reduction than a steep one. The
steepness of the slope of the dose-response curve is also an important consideration in
noncancer risk assessments applying the BMD approach. Information on factors such as
the nature of response being used for point of departure (i.e., tumor data or a more
sensitive precursor response) and biopersistence of the agent are important to consider in
the MoE analysis. As a default assumption for two of these points, a numerical factor of
no less than 10 each may be used to account for human variability and for interspecific
differences in sensitivity when humans may be more sensitive than animals. When human
25
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are found to be less sensitive than animals, a default factor of no smaller than 0.1 may be
used to account for this.
A nonlinear default position must be consistent with the understanding of the agent's
mode of action in causing tumors. For example, a nonlinear default approach would be
taken for an agent's causing tumors as a secondary consequence of organ toxicity or
induced physiological disturbances (e.g., antithyroid agents that perturb pituitary-thyroid
homeostasis, as discussed earlier). Because there must be a sufficient understanding of the
agent's mode of action to take the nonlinear default position, it is anticipated that the
modeling of precursor responses to tumor development will play mi important role in
providing support for nonlinearity, or modeling may actually be used instead of tumor data
for determining the point of departure for the MoE analysis (see Section HI.C).
There may be situations for which it is appropriate to consider both linear and
nonlinear default procedures. For example, an agent may produce tumors at multiple sites
by different mechanisms. In another case, for example, when it is apparent that an agent is
both DNA reactive and highly active as a promoter at higher doses, both linear and
nonlinear default procedures may be used to distinguish between the events operative at
different portions of the dose-response curve and to consider the contribution of both
phenomena. For example, formaldehyde, which was discussed earlier, is DNA reactive at
low doses and active as a promoter at higher doses (i.e., concentrations of formaldehyde
that cause cytotoxicity and increased cell proliferation are also carcinogenic in the nose).
26
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There may be situations for which there is insufficient data to provide high
confidence in a conclusion about any single mode of action of a given agent and for which
different mechanisms may be operating at the different sites of tumor induction. Although
the available data generally supports nonlinearity, a linear mechanism (e.g., a mutagenic
metabolite for one of the tumor sites) cannot be entirely dismissed. Both defaults are
conducted and a discussion of the degree of confidence in each is provided to the risk
manager. The linear default may be viewed as conservative (i.e., likely to overestimate the
risk at low exposures), and it might be more appropriate for screening analyses. The
nonlinear default may be viewed as more representative of the risk given the growth-
promoting potential and toxicity of the given agent
C. Modeling of Precursor Response Data
The proposed EPA cancer guidelines (2) call for modeling of not only tumor data in
' the observable range but other responses thought to be important precursor events in the
carcinogenic process (e.g., DNA adducts, gene or chromosomal mutation, cellular
proliferation, hyperplasia, hormonal or physiological disturbances, receptor binding). The
modeling of important precursor response data makes extrapolation based on default
procedures, discussed earlier, more meaningful by providing insights into the relationships
of exposure and tumor response below the observable range. In addition, modeling of
nontumor data may provide support for selecting a certain extrapolation procedure (linear
vs. nonlinear). If the nontumor endpoint is believed to be part of a continuum that leads to
27
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tumors, such data could then be used to extend the dose-response curve below the
observed tumor response to provide insight into the low-dose response range. For
example, studies using DNA adducts can be conducted with doses overlapping with the
observed tumors down to environmental exposure levels. Several studies have
demonstrated the merit of examining the relationship between DNA adduct concentration
and tumor incidence for more accurate low-dose extrapolations (reviewed in Ref. (75)).
However, when using DNA adducts (as a dosimeter) to extend the observable range, it is
important to have a reasonable understanding of the target cell and the adduct involved in
the carcinogenic process. In addition, changes in cell proliferation rates can cause a steep
upward curvature of the dose-response curve, and thus need to be factored into the
evaluation of risk. The role of cell proliferation in changing the cancer dose-response
curve has been shown for 2-acetylaminofluorene for bladder tumors (76) and for
formaldehyde for nasal tumors (28).
Precursor response data may be modeled and used for extrapolation instead of the
available tumor data. Currently, it is not anticipated that precursor response data will be
used in lieu of tumor data for many compounds because of the more stringent conditions
that must be demonstrated. To be acceptable for extrapolation, the mode of action and the
role the precursor event plays in the carcinogenic process must be understood.
Furthermore, the precursor response should be considered to be more informative of the
agent's carcinogenic risk. Precursor data should be from in vivo experiments and from
repeat dosing experiments over an extended period of time; precursor data are most
28
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valuable if they are built into the design of the cancer bioassay. It is anticipated that the
modeling of precursor response data will come into play predominantly for the nonlinear
default approach, which must be based on a reasonable understanding of the agent's mode
of action in causing tumors. The most likely situations for which prepursor response data
are used to estimate risk involve those mechanisms for which tumor development is
secondary to toxicity or disruption of a physiological process. For example, hyperplasia
might be used in lieu of tumor data to extrapolate risk for a bladder carcinogen that causes
calculi to form in the urine, or TSH levels might be used for a thyroid carcinogen that
perturbs hypothalamus-pituitary-thyroid homeostasis. Alterations in TSH or thyroid
hormone levels may result in other disease consequences. Early responses in the
continuum of events that lead to organ pathology or resultant diseases, such as liver
enzyme changes and liver histopathology, respiratory irritation, and respiratory tract
damage, have been a consideration in noncancer risk assessment (66). Thus, the
consideration of precursor response data in health risk assessment is not a new concept.
IV. Emerging Directions in Exposure Assessment
Exposure is defined as the contact of a chemical, physical, or biological agent with
the outer boundary of an organism (7). Application of exposure data to the field of risk
assessment has grown in importance since the early 1970s because of greater public,
academic, industrial, and government awareness of chemical pollution problems in the
environment. In environmental health assessment one attempts to address the question of
29
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how many people are exposed to a pollutant and to how much. Information about the
\
distribution of exposure to determine the causes of exposures for high risk groups is a key
element in the development of cost-effective mitigation strategies. In addition, information
is needed on body burden and related factors in the general population to provide a
baseline for interpreting the public health significance of measured exposures from site- or
source-specific investigations. For example, body burden levels of environmental
pollutants can put people near the linear part of the dose-response curve, even for a dose-
response curve that is nonlinear,
A current trend in health risk assessment is to assess cumulative total exposures and
risks to multiple environmental agents, through multiple pathways and routes. People are
exposed to many chemicals via different pathways during their lives. Multichemical
exposures are ubiquitous (e.g., air and soil pollution from municipal incinerators, leakage
from hazardous waste facilities and uncontrolled waste sites, drinking water containing
chemical substances formed during disinfections). Because of the difficulties in assessing
multiple exposures, assessments have tended to focus on a single chemical and often on a
single pathway of exposure. Little is known about whether exposure to one chemical or
class of chemicals is correlated with exposure to other chemicals; and even less is known
about the combined risks associated with multiple exposures. Thus, risk assessments of
mixtures usually involve substantial uncertainties. A common risk assessment practice is to
evaluate toxicological properties of the components of mixture and assume that similar
effects are additive. However, some research indicates that toxicological interactions
30
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among chemicals can be antagonistic or synergistic. Pharmacokinetic studies or newer
technologies using transgenic animals (fish or rodents) may make studies of mixtures (e.g.,
binary, tertiary, or quantinary combinations of chemicals) more practical than traditional
toxicology animal bioassays. Moreover, research using in vitro or in vivo eukaryotic
models of the combined effects of mixtures of environmental contaminants on elements of
cell cycle control—including growth, death, and differentiation—may provide insight into
combined risk of chemicals representative of mixtures that are found in environmental
media.
V. Emphasis on Risk Characterization
Risk assessment is an integrative process that culminates ultimately into a risk
characterization summary. Risk characterization is the final step of the risk assessment
process in which all preceding analyses (from hazard assessments to dose-response
assessments to exposure assessments) are tied together to convey the overall conclusions
about potential human risk). This component of the risk assessment process characterizes
the data in nontechnical terms, explaining the key issues and conclusions of each
component of the risk assessment and the strengths and weaknesses of the data. Risk
characterization is the product of risk assessment that is used in risk management
decisions. The current emphasis on risk characterization is illustrated by recent
publications by the EPA and the National Academy of Science/National Research Council
(77)(78).
31
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VI. Summary
Compared with traditional approaches to health risk assessment, ongoing activities
to assess the risk of environmental agents are including a more complete discussion of the
issues and an evaluation of all relevant information, promoting the use of mode-of-action
information to reduce the uncertainties associated with using experimental data to
characterize and project how human beings will respond to certain exposure, conditions.
This emphasis on mechanisms is to promote research and testing to improve the scientific
basis of health risk assessment and stimulate thinking on how such information can be
applied. As the science continues to evolve the practice and policies of risk assessment
will reflect these advances.
32
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Figure Captions
Figure 1. The elements of the risk paradigm: health risk assessment is organized by the
paradigm put forward by the National Academy of Sciences (79)(10), which defines four
types of analysis: hazard assessment, dose-response assessment, exposure, and risk
characterization.
Figure 2. The risk characterization process: the framework of the EPA 1996 Proposed
Guidelines for Carcinogen Risk Assessment (2) is based on the paradigm put forth by the
National Academy of Sciences (10). This framework puts an emphasis on
characterizations of hazard, dose-response, and exposure-assessments. These technical
characterizations integrate the analyses of hazard, dose-response and exposure, explain the
weight of evidence and strengths and weaknesses of the data, as well as discusses the
issues and uncertainties surrounding the conclusions. The technical characterizations
themselves are integrated into the overall conclusions of risk which are presented in a risk
characterization summary (from (2)(11)).
Figure 3. Dose-Response Assessment: the current trend for dose-response (DR)
assessment of cancer and noncancer endpoints is to begin with modeling response data in
the observable range (2)(70). In the of the EPA 1996 Proposed Guidelines for
Carcinogen Risk Assessment (2) DR is proposed as a two-step process; in the first step,
response data are modeled in the range of observation, and in the second step, the point of
<•'
33
-------
departure below the range of observation is determined. The LED10 (effective dose
corresponding to the lower 95% limit on a dose associated with 10%increase in response)
is proposed as a point of departure for extrapolation to the origin as the linear default or
for a margin of exposure analysis as the nonlinear default (from (2)(11)).
34
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Hazard Assessment
]|f, fkf ^A^yT^rjEvsj^i^' - r -
(C^i!oio>yji!>£. "vs.Giv <- c
'b v^.f *c", wpffuTi?!;
Dose-Response Assessment
Exposure Assessment
Figure 1.
Risk Characterization
-------
Technical
Hazard
Characterization
Technical
Exposure
Characterization
mm | m a
Technical
Dose-Response
Characterization
Risk Characterization Process
EXPOSURE
ASSESSMENT
DOSE-RESPONSE
ASSESSMENT
HAZARD
ASSESSMENT
WoE Narrative and Descriptors
¦Ml m i
Risk
Characterization
Summary
Integrative
Analysis
Figure 2.
-------
Extrapolation Range
(D
CO
c
o
Q.
CD
a:
0
CO
as
o
c
10%-
0%L
Human
Exposure
of Interest
6^
0 extra risk
MoE
Figure 3.
Observed Range
¦A
Dose
-------
Table 1. Current Trends in Health Risk Assessment
Historical Approach
Phenomenological studies
Separate assessments and
approaches for cancer and
noncancer risks
Risk to general population
Single chemical exposure and
single pathway
Risk characterization
Emerging Emphasis
Mechanism studies
Integrative health assessments
and harmonization of approaches
for cancer and noncancer risks
Risk to sensitive subpopulations
Multiple chemical exposure via
multiple pathways
More expanded characterizations
of human risk
-------
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1
TECHNICAL REPORT DATA
{Please read Instructions on the revtnt before complt >
1. REPORT NO.
EPA/600/A-96/133
2.
3
i
4. title and subtitle
Health Risk Assessment of Environmental Agents:
Incorporation of Emerging Scientific Information
B. REPORT DATE
$. PERFORMING ORGANIZATION CODE |
EPA/600/021 j
7. AUTMORISI
Vickie L. Dellarco, William
Wi Use
H. Far land, and
Jeanette A.
6. PERFORMING ORGANIZATION REPORT NO.
NCEA-I-0186 '
i i
9. PERFORMING ORGANIZATION NAME AND ADDRESS
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC 20460
10. PROGRAM ELEMENT NO. |
11 CON TRACT/GRANT NO. j
j
12, SPONSORING AGENCY NAME AND ADDRESS
13. TYPE Of REPORT AND PERIOD COVERED
Book Chapter ,
•
14. SPONSORING AGENCY CODE j
f
15. SUPPLEMENTARY NOTES i
I
I
16. ABSTRACT
Health risk assessment practices are evolving on a number of fronts. Risk analyses have historically relied to a large degree on
observations of frank toxic effects. Risk assessments are moving from this phcnomenologic approach by identifying the ways :
environmental agents ore changed through metabolic processes, the dose at the affected organ system, and how an agent produces 1
its toxic effect is beginning to break down the dichotomy that existed between assessments of cancer and noncanccr risks. Of equal
importance, the "one-size-fits-all" approach is being replaced by emphasizing the ascertainment of risk to susceptible
subpopulations. EPA recently put fonh a new national agenda to protect children from toxic agents in the environment (I). In
addition, to make risk assessments more understandable and useful, there is an increased emphasis on risk characterization. Risk
characterization is the final output of the risk assessment process from which all preceding analyses (i.e., from the hazard, dose-
response, and exposure assessments) are tied together to convey in nontechnical terms the overall conclusions about potential
human risk, as well as the rationale, strengths, and limitations of the conclusions. This article discusses several trends occurring in
risk assessment in the context of the risk paradigm-hazard, dose-response, and exposure assessments and subsequent risk
characterization. Chemical examples arc provided to illustrate these emerging directions in health risk assessment.
17.
KEY WORDS AND OOCUMENT ANALYSIS
a. descriptors
b.lOENTIFIERS/OPEN ENDED TERMS
c. COS ATI Field/Group
18. DISTRIBUTION STATEMENT
19. SECURITY CLASS (This Report)
Unclassified
21, NO. OF PAGES
Release to the Public
20. SECURITY CLASS /This page!
llnrlassifiprf
22. PRICE
EPA F erm 2220—1 (R«v. A—77) previous edition is obsolete
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