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Science and Decisions: Advancing Risk Assessment 5 Toward a Unified Approach to Dose-Response Assessment THE NEED FOR AN IMPROVED DOSE-RESPONSE FRAMEWORK Introduction to the Problem As described in Chapter 4, one of the urgent challenges to risk assessment is the evaluation of hazard and risk in a manner that is faithful to the underlying science, is consistent among chemicals, accounts adequately for variability and uncertainty, does not impose artificial distinctions among health end points, and provides information that is maximally useful for risk characterization and risk management. There have been efforts to harmonize dose-response methods for cancer and noncancer end points, but, as discussed below, criticisms have been raised regarding the validity of dose-response assessments for risk characterizations and management and regarding the treatment of uncertainty and variability in human sensitivity. This chapter examines the science governing dose-response assessment for a variety of end points (cancer and noncancer) and develops an integrative framework that provides conceptual and methodologic approaches for cancer and noncancer assessments. Current Framework Dose-response assessments for carcinogenic end points have been conducted very differently from noncancer assessments. For carcinogens, it has been assumed that there is no threshold of effect, and dose-response assessments have focused on quantifying the risk at low doses. The current Environmental Protection Agency (EPA) approach derives a “point of departure” (POD), such as the lower bound on the dose that results in an excess risk of 10% based on fitting of a dose-response model to animal bioassay data (EPA 2000a). After adjustment for animal-human differences in the dose metric, risk is assumed to decrease linearly with doses below the POD for carcinogens that are direct mutagens or are associated with large human body burdens (EPA 2005a). The population burden of disease or the population risk at a given exposure is estimated. In practice, EPA carcinogen assessments do
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Science and Decisions: Advancing Risk Assessment not account for differences among humans in cancer susceptibility other than from possible early-life susceptibility (see Chapter 4). For noncancer end points, it is assumed that homeostatic and defense mechanisms lead to a dose threshold1 (that is, there is low-dose nonlinearity), below which effects do not occur or are extremely unlikely. For these agents, risk assessments have focused on defining the reference dose (RfD) or reference concentration (RfC), a putative quantity that is “likely to be without an appreciable risk of deleterious effects” (EPA 2002a, p. 4-4). The “hazard quotient” (the ratio of the environmental exposure to the RfD or RfC) and the “hazard index” (HI, the sum of hazard quotients of chemicals to which a person is exposed that affect the same target organ or operate by the same mechanism of action) (EPA 2000b) are sometimes used as indicators of the likelihood of harm. An HI less than unity is generally understood as being indicative of lack of appreciable risk, and a value over unity indicates some increased risk. The larger the HI, the greater the risk, but the index is not related to the likelihood of adverse effect except in qualitative terms: “the HI cannot be translated to a probability that adverse effects will occur, and is not likely to be proportional to risk” (EPA 2006a). Thus, current RfD-based risk characterizations do not provide information on the fraction of the population adversely affected by a given dose or on any other direct measure of risk (EPA 2000a). That deficiency is present whether the dose is above the RfD (in which case the risk may be treated as nonzero but is not quantified) or below the RfD (in which case the risk can be treated as “unappreciable” or zero even though with some unquantified probability it is not zero). As in cancer dose-response assessment, the RfD is also derived from a POD, which could be a no-observed-adverse-effect level (NOAEL) or a benchmark dose (BMD). However, instead of extrapolating to a low-dose risk, the POD is divided by “uncertainty factors” to adjust for animal-human differences, human-human differences in susceptibility, and other factors (for example, data gaps or study duration). In a variant of the RfD approach to noncancer or low-dose nonlinear cancer risk assessment, the agency calculates a “margin of exposure” (MOE), the ratio of a NOAEL or POD to a projected environmental exposure (EPA 2000a, 2005b). The MOE is compared with the product of uncertainty factors; an MOE greater than the product is considered to be without appreciable risk or “of low concern,” and an MOE smaller than the product reflects a potential health concern (EPA 2000b). MOEs and RfDs are defined for durations of exposure (for example, acute, sub-chronic, and chronic) and may be defined for specific life stages (for example, developmental) (EPA 2002a). Recent refinements in risk-assessment methods in EPA have used mode-of-action (MOA)2 evaluations in dose-response assessment. EPA’s Guidelines for Carcinogen Risk Assessment (2005b) state that if a compound is determined to be “DNA reactive and [to] have direct mutagenic activity” or to have high human exposures or body burdens “near doses associated with key precursor events” (EPA 2005b, p. 3-21), a no-threshold approach is applied; risk below the POD is assumed to decrease linearly with dose. For carcinogens with sufficient MOA data to conclude nonlinearity at low doses, such as those acting through a cytotoxic MOA, the RfD approach outlined above for noncancer end points is applied (EPA 2005b), 1 More recent noncancer guidelines have abandoned the term threshold, noting the difficulty of empirically distinguishing dose-response relationships with true biologic thresholds from ones that are nonlinear at low doses (EPA 2005b, p. 3-24). 2 Following EPA 2005b (p. 1-10), the MOA 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 the adverse effect. “A ‘key event’ is an empirically observable precursor step that is itself a necessary element of the mode of action or is a biologically based marker for such an element.”
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Science and Decisions: Advancing Risk Assessment except when there is adequate evidence to support mechanistic modeling (there has been no such case). Another refinement in dose-response assessment has been the derivation of the RfD or low-dose cancer risk from a POD that is calculated using BMD methodology (EPA 2000a). In noncancer risk assessment, this approach has the advantage of making better use of the dose-response evidence available from bioassays than do calculations based on NOAELs. It also provides additional quantitative insight into the risk presented in the bioassay at the POD because for quantal end points the POD is defined in terms of a given risk for the animals in the study. EPA’s treatment of noncancer and low-dose nonlinear cancer end points is a major step by the agency in an overall strategy to harmonize cancer and noncancer approaches to dose-response assessment. Other aspects of this harmonization for the different end points include consideration of the same cross-species factors (EPA 2006b), and the same pharmacokinetic adjustments. EPA staff have also explored for noncancer end points dose-response modeling that results in probabilistic descriptions (for example, for acrolein, Woodruff et al. 2007) and that could be readily integrated into benefits evaluation (for thyroid-disrupting chemicals, Axelrad et al. 2005). But these approaches have not found their way into agency practice. Scientific, Technical, and Operational Problems with the Current Approach The committee recognizes EPA’s efforts to examine and refine dose-response assessment methodology and practice and the agency’s work to clarify its approaches and practices in guidelines and other documents (for example, EPA 2000a, 2002b, 2004, 2005b). A number of improvements over the last decade can be noted, such as the movement toward using MOA determinations and the application of BMD methods. However, the current framework has important structural problems, some of which have been exacerbated by recent decisions. Figure 5-1 presents an outline of the current framework for dose-response assessment and risk characterization in EPA and some major limitations in the framework, which are discussed below. Potential Low-Dose Linearity for Noncancer and “Nonlinear” Cancer End Points Thresholds are assumed for noncarcinogens and for carcinogens believed to operate through an MOA considered nonlinear at low doses. The rationale is that at levels below the threshold dose, clearance pathways, cellular defenses, and repair processes have been thought to minimize damage so that disease does not result. However, as illustrated in Figure 5-2, threshold determinations should not be made in isolation, inasmuch as other chemical exposures and biologic factors that influence the same adverse effect can modify the dose-response relationship at low doses and should therefore be considered. Nonlinear Cancer End Points The current determination of “nonlinearity” based on MOA assessment is a reasonable approach to introduce scientific evidence on MOA into cancer dose-response assessment. However, some omissions in this overall approach for low-dose nonlinear carcinogens could yield inaccurate and misleading assessments. For example, the current EPA practice of determining “nonlinear” MOAs does not account for mechanistic factors that can create linearity at low dose. The dose-response relationship can be linear at a low dose when an exposure contributes to an existing disease process (Crump et al. 1976, Lutz 1990). Effects
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Science and Decisions: Advancing Risk Assessment FIGURE 5-1 Current approach to noncancer and cancer dose-response assessment. of exposures that add to background processes and background endogenous and exogenous exposures can lack a threshold if a baseline level of dysfunction occurs without the toxicant and the toxicant adds to or augments the background process. Thus, even small doses may have a relevant biologic effect. That may be difficult to measure because of background noise in the system but may be addressed through dose-response modeling procedures. Human variability with respect to the individual thresholds for a nongenotoxic cancer mechanism can result in linear dose-response relationships in the population (Lutz 2001). In the laboratory, nonlinear dose-response processes—for example, cytotoxicity, impaired immune function and tumor surveillance, DNA methylation, endocrine disruption, and modulation of cell cycles—may be found to cause cancer in test animals. However, given the high prevalence of those background processes, given cancer as an end point, and given the multitude of chemical exposures and high variability in human susceptibility, the results may still be manifested as low-dose linear dose-response relationships in the human population (Lutz 2001). The possibility of low-dose linearity due to background is acknowledged
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Science and Decisions: Advancing Risk Assessment FIGURE 5-2 Value of physiologic parameter for three hypothetical populations, illustrating that population responses depend on a milieu of endogenous and exogenous exposures and on vulnerability of population due to health status and other biologic factors. Source: Adapted from Woodruff et al. 2007. Reprinted with permission; copyright 2007, Environmental Health Perspectives. in the EPA (2005b) Guidelines for Carcinogen Risk Assessment to a limited degree—for chemicals with high body burdens or high exposures—but has not been addressed in EPA assessments. And EPA practices do not call for systematic evaluation of endogenous and exogenous exposures or mechanisms that can lead to linearity. By segregating cancer and noncancer risk assessment, the current framework tends to place undue focus on “complete” carcinogens, ignoring contributions to ongoing carcinogenesis processes and the multifactorial nature of cancer. Chemicals that may increase human cancer risk by contributing to an underlying process are handled essentially as noncarcinogens even though they may be integral to the carcinogenic process. The dichotomy increases the burden of judging which chemicals are carcinogens rather than accepting the variety of carcinogenic MOAs and incorporating them into a comprehensive risk assessment. Noncancer End Points Similarly, noncarcinogens can exhibit low-dose linearity, for example, when there is considerable interindividual variability in susceptibility and each individual has his or her own threshold, especially when an underlying disease (such as cardiopulmonary disease) can interact with the toxicant (such as particulate matter [PM] or ozone). Schwartz et al. (2002) made the argument for the absence of a population threshold for mortality effects of PM. Other factors that support nonthreshold dose-response relationships for noncarcinogens include The observation of dose-response relationships with no apparent thresholds for subtle, common adverse end points, such as IQ loss or neurobehavioral deficits associated with lead or methylmercury exposures—an observation that continues to be made even as investigators probe for effects at smaller exposures (Axelrad et al. 2007). Those effects occur at lower doses than frank toxicity and are expected to become a more common basis of
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Science and Decisions: Advancing Risk Assessment dose-response assessment as increasingly subtle end points are studied with more sensitive tests (for example, tests based on -omics) or epidemiologically. The fact that in receptor-mediated events, even at very low doses a chemical can occupy receptor sites and theoretically perturb cell function (such as signal transduction or gene expression) or predispose the cell to other toxicants that bind to or modulate the receptor system (such as organochlorines and the aryl hydrocarbon receptor or endocrine disruptors and hormonal binding sites) (Brouwer et al. 1999; Jeong et al. 2008). The observation that exposures that perturb or accelerate background endogenous disease processes and add to background endogenous and exogenous exposures may not show evidence of a threshold, as described above (“Nonlinear Cancer End Points”). There are multiple toxicants (for example, PM and lead) for which low-dose linear concentration-response functions rather than thresholds have been derived for noncancer end points. The current EPA framework treats them as exceptions (implicitly if not explicitly) and does not provide methods and practices for readily assessing the dose-response relationship for cases in which thresholds are not apparent or not expected, for example, because of background additivity. As discussed in this chapter, for critical end points driving the risk characterization at low doses, such cases may be common, and a new framework and practice are needed. Another problem posed by the current noncancer framework is that the term uncertainty factors is applied to the adjustments made to calculate the RfD to address species differences, human variability, data gaps, study duration, and other issues. The term engenders misunderstanding: groups unfamiliar with the underlying logic and science of RfD derivation can take it to mean that the factors are simply added on for safety or because of a lack of knowledge or confidence in the process. That may lead some to think that the true behavior of the phenomenon being described may be best reflected in the unadjusted value and that these factors create an RfD that is highly conservative. But the factors are used to adjust for differences in individual human sensitivities, for humans’ generally greater sensitivity than test animals’ on a milligrams-per-kilogram basis, for the fact that chemicals typically induce harm at lower doses with longer exposures, and so on. At times, the factors have been termed safety factors, which is especially problematic given that they cover variability and uncertainty and are not meant as a guarantee of safety. The Need for Evaluation of Background Exposures and Predisposing Disease Processes Dose-response assessments for noncancer and nonlinear cancer end points are generally performed without regard to exposure to other chemicals that affect the same pathologic processes or the extent of pre-existing disease in the population. The need to address chemicals that have “a common mechanism of toxicity” in a cumulative risk assessment has been established for pesticides under the Food Quality Protection Act (FQPA) of 1996 (EPA 2002b, p. 6). EPA (2002b) provides a useful example, but it was driven principally by the explicit requirements of the FQPA, and few noncarcinogens are evaluated in this way. Furthermore, dose additivity has been observed at relatively low doses for various endocrine-related toxicities with similar and dissimilar mechanisms of action (for example, Gray et al. 2001; Wolf et al. 2004; Crofton et al. 2005; Hass et al. 2007; Metzdorff et al. 2007). Dosing animals with two chemicals that have different MOAs at their NOAELs resulted in a significant adverse response, which suggested dose additivity (as when two chemicals at subthreshold doses lead to an effect). In practice, a common implicit assumption is effect
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Science and Decisions: Advancing Risk Assessment additivity—two subthreshold doses yield a nonresponse because neither produces a response on its own. Consideration of chemicals that have a common MOA has not included how endogenous and other chemicals, not the direct subjects of testing and evaluation by regulatory agencies, affect the human dose-response relationship. The recent EPA draft dibutyl phthalate (DBP) assessment is an example in which there was an opportunity to consider cumulative exposure to the various agents that can contribute to the antiandrogen syndrome seen with phthalates, but the impact of even other phthalates on the DBP dose-response relationship was not taken into account in setting the draft RfD (EPA 2006c). In the application of such an assessment, DBP exposures above the RfD would be treated as posing some undefined extra degree of risk and DBP exposures below the RfD would, without further guidance from the agency, potentially be treated as riskfree without regard to the presence of other antiandrogen exposures. Risk-Assessment Outcomes Needed for Risk Evaluation and Benefit Analysis The end products of noncancer (and nonlinear cancer) assessments in the current paradigm (exposure-effect quotients that qualitatively indicate potential risk—MOEs, RfDs, and RfCs, Figure 5-1) are inadequate for benefit-cost analyses or for comparative risk analyses. MOEs and RfDs as currently defined do not provide a basis for formally quantifying the magnitude of harm at various exposure levels. Therefore, the committee finds the 2005 Guidelines for Carcinogen Risk Assessment movement toward RfDs and away from an expression of risk posed by nonlinear carcinogens problematic. Similarly, although noncancer risk assessment has moved to a BMD framework that makes better use of evidence than an approach based on NOAELs and lowest observed-adverse-effect levels (LOAELs), the paradigm remains one of defining an RfD or RfC without any sense of the degree of population risk reduction that would be found in moving from one dose to another dose. A probabilistic approach to noncancer assessment, similar to how cancer risks are expressed, would be much more useful in risk-benefit analysis and decision-making. The current threshold-nonthreshold dichotomy creates an inconsistent approach for bringing toxicology and risk science into the decision-making process. That paradigm has other unintended consequences. For example, the linear-extrapolation exercise for carcinogens and lack of consideration of linearity for noncarcinogens and “nonlinear” carcinogens create a high bar of evidence for carcinogen identification and reduce the consideration of the possibility of noncancer end points for carcinogens. More generally, the many noncancer health end points are generally given little weight in benefit-cost analyses or other analytically driven decision frameworks in part because of the nature of the resulting qualitative risk characterization. In the general case in which an intervention reduces exposures from above the RfD to below the RfD, it is particularly unfortunate to fail to quantify this benefit. It might be possible, through economic valuation (willingness-to-pay or contingent-valuation) studies, to estimate the benefits of moving N members of the population from exposure above the RfD to exposure below the RfD, but it would be more straightforward and intelligible to directly estimate the benefits of such an exposure and risk reduction. The current approach also does not address the benefits of lowering exposures that are already below the RfD or the benefits of lowering exposures from above the RfD to an exposure level that is still above the RfD, both of which, if understood to be associated with a nonzero probability of harm, also need valuation. The framework described below provides a means of generating the data needed for such analyses.
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Science and Decisions: Advancing Risk Assessment Limitations of the Current Approach for Low-Dose Linear Cancer End Points EPA assumes that the linear default approach for dose-response assessment provides “an upper-bound calculation of potential risk at low doses,” which is “thought to be public-health protective at low doses for the range of human variation” (EPA 2005b, p. A-9). EPA (2005b) noted that the National Research Council reports (NRC 1993, 1994) generally discussed the variability in human susceptibility to carcinogens and that EPA and other agencies were conducting research on the issue. The committee finds that although the precise degree of human variability is not known, the upper statistical bound derived from fits to animal data does not address human variation, as discussed below. Further, with few exceptions (EPA 2001a), the current practice embeds an implicit assumption that it is zero. This is not credible and is increasingly unwarranted as more and more studies document the substantial interindividual variation in the human population (see Chapter 4). According to EPA, “the linear default procedure adequately accounts for human variation unless there is case-specific information for a given agent or mode of action that indicates a particularly susceptible subpopulation or lifestage, in which case the special information will be used” (EPA 2005b, p. A-9). That implies that in general the linear-extrapolation procedure will overestimate the risk to an extent that will account for the underestimation bias related to the omission of human heterogeneity. EPA provides no evidence to support that assumption and in essence establishes a default (no variability in susceptibility) that is unsubstantiated (see Chapter 6 for discussion of “missing” defaults). There are three main steps in deriving human cancer risk from animal bioassay data: adjusting animal doses to equivalent human doses, deriving the POD by fitting a mathematical model to the data, and linearly extrapolating from the POD to lower doses. The default animal-to-human adjustment is based on metabolic differences due to the roughly 200- to 2,000-fold differences in body sizes and is set at a median value without accounting for the large qualitative uncertainty, in any particular application, of the humans being more sensitive than the animal or vice versa. The lower bound on the POD merely accounts for the uncertainty in the model fitted to data from the fairly homogeneous animals used in studies. If the true dose-response relationship for an agent is indeed linear, the statistical lower confidence limit (for example, the BMD lower confidence limit [BMDL]) associated with a POD (for example, the BMD) provides a small increment of “conservatism”—typically not more than a factor of 2 (Subramaniam et al. 2006). That is highly unlikely to account for variation in susceptibility in cancer in a large exposed human population (see Chapter 4). If, instead, the true dose-response relationship is nonlinear, treating it as linear might introduce enough “conservatism” to offset the underestimation of risk in people of above-average susceptibility, but the degree to which the high-dose-based estimate is in error would preferably be analyzed separately. The practice of assuming no human variation in response to compounds for which linearity is applied is simplistic and inconsistent with the manner in which noncancer assessments are conducted. Many factors can cause the cancer response to be highly variable in the population, including age, sex, genetic polymorphisms, endogenous disease processes, lifestyle, and coexposure to other xenobiotics common in the human environment (see “Variability and Vulnerability in Risk Assessment” in Chapter 4). Some of those factors, especially pharmacokinetics and early age, are beginning to be considered in a few cancer risk assessments, but much more emphasis needs to be placed on describing the ranges of susceptibility and risk. Other Limitations of the Current Approach One cross-cutting issue for all end points is the degree to which dose-response characterization is done in data-poor cases. Often, a compound on which information is sparse is
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Science and Decisions: Advancing Risk Assessment not addressed in a quantitative risk assessment and operationally can be treated as though it posed no risk of regulatory importance. That is unlikely to describe the situation adequately or to be helpful in setting research priorities. An approach to that problem is described in Chapter 6. In addition, any analysis must grapple with the best approach for integrating data from multiple studies and on multiple end points. There has been a tendency in risk assessment to pick a single dataset with which to describe risk, in part because it leads to straightforward rationales that are easy to explain, understand, and communicate. However, the direction toward better understanding of uncertainty, human variability, and more accurate assessment necessarily involves increasing complexity and integration of evidence from disparate sources. It also may involve constructing dose-response relationships based on evidence from a variety of study types (such as cancer bioassays and in vitro studies). Also, a given exposure to a particular chemical may affect multiple end points, and a risk description based on one tumor site or effect may fall short of conveying the overall risk posed by the substance. In summary, the committee finds multiple scientific and operational limitations in the current approach for both cancer and noncancer risk assessments. The following section describes a means for addressing many of the issues by developing a unified framework for toxicity assessment that incorporates variability and uncertainty more completely and provides quantitative risk information on cancer and noncancer end points alike. A UNIFIED FRAMEWORK AND APPROACH FOR DOSE-RESPONSE ASSESSMENT The committee finds that the underlying science is more consistent with a new conceptual framework for dose-response modeling and recommends that the agency adopt a unified framework. Figure 5-3a illustrates the underlying dose-response principles for the framework, which includes background processes and exposures in considering risks on the individual and population scales. Figure 5-3a shows that an individual’s risk from exposure to an environmental chemical is determined by the chemical itself, by concurrent background exposures to other environmental and endogenous chemicals that affect toxicity pathways and disease processes, and by the individual’s biologic susceptibility due to genetic, lifestyle, health, and other factors. How the population responds to chemical insults depends on individual responses, which vary among individuals. Clearly, background exposures and biologic susceptibility factors differ substantially between animals and humans, and there can be more confidence in dose-response descriptions that consider and account for background exposure and biologic susceptibility of populations for which risks are being estimated. Figure 5-3b provides a depiction of individual and population risk that formally takes these factors into account. The shape of the population dose-response relationship at low doses is inferred from an understanding of individual dose-response relationships, which in turn are based on consideration of background exposure and biologic susceptibility on human heterogeneity. An upper bound on the population dose-response relationship would be derived to express uncertainty in the population dose-response relationship. For compounds whose effects show a linear dose-response relationship, this upper bound is not the same as the familiar upper bound derived by fitting dose-response models to animal bioassay data. The latter upper bound measures only a very small aspect of uncertainty: that due to sampling variability and the statistical fit to animal data. Here, the committee envisions a more comprehensive description of uncertainty that accounts for other aspects, such as uncertainty in cross-species extrapolation. The dose of the environmental chemical that poses, say, a risk above background (“extra risk”) of 10−5 in a population, could be described by a probability distribution that reflects
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Science and Decisions: Advancing Risk Assessment FIGURE 5-3a New conceptual framework for dose-response assessment. Risk posed by environmental chemical is determined from individual’s biologic makeup, health status, and other endogenous and exogenous exposures that affect toxic process; differences among humans in these factors affect shape of population dose-response curve.
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Science and Decisions: Advancing Risk Assessment FIGURE 5-3b Risk estimation and description under the new conceptual framework for dose-response assessment. Risk estimates are based on inferences made from human, animal, MOA, and other data and understanding of possible background processes and exposures. Ideally, population dose-response relationship and uncertainty (represented by upper 95% bound) and dose-response relationships for sensitive members of population are described. (As explained in text, upper 95% confidence bound on risk is not same as upper-bound estimate generated in current cancer risk assessments.) Mean estimate of population risk can be derived from understanding of individual risk.
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Science and Decisions: Advancing Risk Assessment CONCLUSIONS AND RECOMMENDATIONS Conclusions This chapter reviews the current paradigm for characterizing the dose-response relationships of compounds for both cancer and noncancer end points and supports the following conclusions: Separation of cancer and noncancer outcomes in dose-response analysis is artificial because noncancer end points can occur without a threshold or low-dose nonlinearity on the population level and in some cases on the individual level. Similarly, the MOA for carcinogens varies and requires a flexible but consistent analytic framework. The separation not only is scientifically unjustified but leads to undesirable risk-management outcomes, including inadequate attention to noncancer end points, especially in benefit-cost analyses. The current formulation of the RfD is problematic because of its application as a determinant of risk vs no risk of regulatory importance, and it lacks a quantitative description of the risk at different doses. It hinders risk-risk and risk-benefit comparisons and riskmanagement decision-making and does not make the best possible use of available scientific evidence. Cancer risk assessment typically lacks a quantitative description of interindividual variability. That leads to an incomplete description of the range of risk possible in the population. Noncancer risk assessment addresses interindividual variability, but cancer risk assessment typically does not; this reflects the implicit default assumption that human cancer susceptibility does not vary (see Chapters 4 and 6). The argument that the linear dose-response extrapolation procedure covers the omission (EPA 2005b) is unsupported and presents a separate consideration that should not be confused with the need to describe risk differences among individuals in addition to high-dose–low-dose extrapolation. The approach adopted in the current carcinogen guidelines (EPA 2005b) that considers variability only when a sensitive subpopulation can be identified for a particular chemical is limited by a lack of chemical-specific data. It also ignores the appreciable scientific knowledge of human interindividual variability in sensitivity (see, for example, Table 4-1), which can form the basis of general assumptions regarding variability when chemical-specific data are absent. The supplemental guidance regarding children (EPA 2005c) is an important step in the right direction, but variability in the general population should also be addressed. Uncertainty factors are generally used to make adjustments whose accuracy is unknown. The uncertainty factors comprise elements of the adjustment for uncertainty and variability. The default factors should be replaced with distributions that separate the elements transparently. Default distributions that characterize PK and PD variability, cross-species dose adjustments, and adjustments for the lack of sensitive studies will be needed as starting points that can be improved as the research advances. The committee considers that the term safety factor, to characterize uncertainty factors in noncancer risk assessments, is inappropriate and misleading. The term uncertainty factor is also inappropriate as it does not reflect the variability and adjustment elements that the factor represents. The underlying scientific and risk-management considerations point to the need for unification of cancer and noncancer approaches in which chemicals are put into a common analytic framework regardless of type of outcome. There are core differences among end points, but in this analytic framework a dose corresponding to a specified increase in risk in the population could be derived for both cancer and noncancer end points, and this would
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Science and Decisions: Advancing Risk Assessment add transparency and quantitative insight to risk-management decisions. Among other changes, this would involve a redefinition of the RfD. The committee acknowledges that the risk estimates and risk specific RfDs derived from this methodology will often be uncertain. This would nonetheless be an improvement over the RfDs derived from the traditional BMD and uncertainty factor approach. The results are more transparent, presenting variability and uncertainty, and are more amenable to refinements as better data are obtained. Further, quantification of risk (along with the attendant uncertainty) not only at the RfD but along the dose continuum is an important advance for risk benefit analysis. The committee finds that a common analytic framework best reflects the underlying science. The main elements of this framework are shown in Figure 5-8 and include Systematic assessments of the MOAs, vulnerable populations, and background exposures and disease processes that may affect a chemical’s human dose-response relationships and human vulnerability. This includes an evaluation of the potential background exposures and processes (for example, damage and repair processes, disease, and aging) that interact with a chemical’s MOAs and thus contribute to variability in and vulnerability to the toxicant response and that can result in a population dose-response relationship that is linear at low doses. Selection of a conceptual model for individual and population dose-response relationships. The following three are described in the chapter: Low-dose nonlinear individual response, low-dose linear population response with background dependence. Low-dose nonlinear individual and population response independent of background. Low-dose linear individual and population response. Selection of a conceptual model and dose-response method that best reflects MOA and background considerations and the form of risk characterization needed for risk management. Where feasible, methods that result in quantitative descriptions of risk and uncertainty should be selected. The key advantages of the framework are Risk descriptors that are quantitative and probabilistic. The RfD would be redefined as a risk-specific dose (for example, the dose associated with a 1 in 100,000 risk of a particular end point), and the risk could be estimated at doses above and below the RfD. This would allow all end points to be more formally incorporated into risk-tradeoffs and benefit-cost analyses. Characterization of variability and uncertainty for critical end points. This would address concerns about population heterogeneity in risk and inform value-of-information and other priority-setting analyses that require quantitative uncertainty estimates. The sources of variability and uncertainty and their quantitative contributions in the derivation of risk estimates would be more transparent. This would in turn enable the quantitative characterization of uncertainties in such benefits. A means to quantitatively describe health benefits from changes in exposure. This would enable the direct comparisons of costs of these changes with the benefits accruing from them. The basis for more flexibility in decision-making. The risk manager can use the risk specific RfD in the same manner the current RfD is used in regulatory decision-making. However, additional quantitative risk information can accompany the RfD, including risk and uncertainty estimates above and below the RfD. This will enable a more robust consideration of options and trade-offs in risk-risk and risk-benefit analyses.
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Science and Decisions: Advancing Risk Assessment The key disadvantages of the framework are The need for increased analysis to consider in detail the background factors that may add to the exposure in question and that may contribute to variability. This can increase the complexity of the analysis and pose a challenge for communicating the analysis and its results. Training will be needed for both risk assessors and risk managers. The agency has already included some elements of the framework in a few assessments (for example, EPA 2001b; EPA 2004), and explored other elements in case studies (for example, Axelrad et al. 2005; Woodruff et al. 2007). EPA laboratories also conduct research that is supportive of the characterizations envisioned by the committee. Thus, EPA has internal capacity for the development of these methods. Realizing full use will take further development and staff training. The risk assessment community external to the agency provides several examples that are cited above and is also a resource for developing further cases and expanding the methodology. The agency also has considerable expertise translating risk information and using it in decision-making. Approaches currently used in risk management may have to be adapted to make full use of the new information and risk managers may need to be trained on how to best use the new and different risk characterizations. Because of the limitations of data on which some elements of the framework would be built, this necessarily entails development of defaults. Depending on the level of analysis, that would provide incentives for chemical-specific information on background exposures, interaction with baseline aging and disease processes, and interindividual variability. It comes at a time when toxicology and risk-assessment resources are already challenged by the expanding role of risk assessment in decision-making and the lack of basic toxicology information on many chemicals. However, it also comes at a time of rapid scientific and technologic innovation in the biologic sciences and testing that can be developed to support novel and improved approaches (NRC 2006d, 2007a,b). Establishing reasonable and scientifically supported default approaches (such as linear extrapolation to low dose for chemicals that are subject to background additivity) and default distributions (such as interindividual variability) to implement the framework will encourage research and a healthy discussion of the science that underpins risk assessment. The resulting default approaches are part of the anticipated advances in the use of defaults in risk assessment described in Chapter 6. The process of establishing the defaults will bring about a better understanding of how chemical-specific information should be used to inform toxicity assessment and low-dose extrapolation. Recommendations The committee has divided its recommendations on the unified framework into shortand long- term recommendations. If the short term recommendations are implemented, the committee envisions significant progress in the next 2-5 years. The time horizon for substantial progress for the long term recommendations is further out, 10-20 years. Short-Term Recommendations The committee recommends the phase-in of the unified framework for dose-response assessment as new chemicals are assessed or old ones are reassessed for Integrated Risk Information System or program offices or incorporated in comparative or cost-benefit analyses. The initial test cases should be used as a proof of concept. The committee recommends a flexible approach in which different conceptual models can be applied in the unified frame-
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work, as illustrated by the three conceptual models presented in this chapter. This approach would involve Incorporation of probabilistic and distributional methods into dose-response analysis for agents believed to have low-dose nonlinear responses and the later redefinition of the RfD on the basis of the probabilistic description. Evaluation of each chemical in terms of MOA, background exposure and disease processes, and vulnerable populations. This would add a step to the dose-response analysis in which background exposures and vulnerabilities of the target population are analyzed and used to decide between analytic options based on conceptual models, according to the unified framework outlined in Figure 5-8. Incorporation of background additivity to account for Additional sources of exposure to the same chemical or to similarly acting chemicals (including endogenous sources). Chemical MOA interaction with relevant disease or aging processes that lead to a background vulnerability distribution. Development of defaults and guidance for assessing the MOA, background exposure and disease processes, and vulnerable populations, and selection of conceptual model. The committee recommends that cancer and noncancer responses be assumed to be linear as a default. An alternative analytic option (conceptual model 2) is available for cases in which it can be shown that background is unlikely to be an important contributor to risk, according to the recommended evaluation of MOAs and background. Formal introduction of human variability into cancer dose-response modeling and risk characterization. This will require chemical-specific distributions or the use of default variability distributions. The committee recommends that as the distributions are being developed, EPA use a default for interindividual variability that assumes a lognormal distribution and immediately begin to explicitly address human variability in cancer response estimates. A reasonable assumption would be that the 95% upper-bound person is about 10-50 times as sensitive as the median person. The committee recommends that EPA develop case studies to explore the use of the new unified framework. The goal of the case studies would not be simply to compare the results of the current approach and new framework. Rather, the case studies would be used to explore and gain experience with the framework in the MOA, vulnerability, and background assessments; using improved information on variability (for example, genetic polymorphisms, disease, and aging-related vulnerabilities) and coexposures in RfD derivation; incorporating variability into cancer risk analysis; and quantitative uncertainty characterizations of dose-response relationships. The committee recommends that EPA gather information from epidemiology, the pharmaceutical literature, and clinical toxicology and use it to develop default interhuman variability PK and PD distributions. Some possible approaches are outlined in Table 5-1. The committee recommends that the agency develop default-adjustment distributions that quantitatively characterize the adjustments and key uncertainties typical in dose-response assessment, including cross-species extrapolation in PK and PD and extrapolations among dose route, dosing intervals (for example, subchronic to chronic), and data gaps. Some possible approaches are outlined in Table 5-1. Maximum use of existing human datasets is encouraged. Studies with well-defined exposure information, such as biomarker measurements on individuals, could be examined to understand the heterogeneity in response. Such datasets could be used to build variability distributions that may be applicable to sets of chemicals (with similar structure, MOA, target sites, and effects) and increase understanding of interhuman PD variability.
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Science and Decisions: Advancing Risk Assessment The agency should develop formal guidance for dose-response analysis under the unified framework. For example, guidance will be needed for the conduct of background vulnerability and exposure assessments, MOA evaluation, default dose-response modeling, nondefault chemical specific analyses. The committee recommends as default distributions are developed for the different adjustments used in dose-response assessment, they should be assigned accurate labels (such as human variability distribution). This should lessen the opportunity for transferring to the new default distributions the misunderstanding commonly associated with use of the term uncertainty factor. Over the next 5 years, the committee recommends that EPA further develop the issue of vulnerability by gathering data and developing a broad array of human-vulnerability information from the biomedical literature, focusing on diseases that are likely to interact with the MOAs of prevalent-exposure and high-priority chemicals (for example, pulmonary, cardiovascular, hepatic, and renal diseases and various cancers). This could involve working with clinicians, biochemists, epidemiologists, and other biomedical specialists to develop preclinical-disease biomarkers as upstream indicators of vulnerability to toxicant MOAs. Long-Term Recommendations The committee recommends that EPA expand its research on the issues of vulnerability and susceptibility. The agency could conduct studies itself and coordinate with other agencies for more in-depth research on the determinants of vulnerability and the development of approaches for more accurate consideration of vulnerability in agency assessments. This could involve using epidemiologic studies to explore how the response to toxicants may be affected by pre-existing diseases and vulnerabilities in the population. Biomarkers of vulnerability and effect could be developed for applications as predictive screens in exposed populations. When analyzed with exposure biomarkers, they could be used to assess human exposure-response relationships and interindividual variability. Regional and national datasets, such as those from National Health and Nutrition Examination Surveys and environmental and public-health tracking, could be used to evaluate whether people with background vulnerability or background exposure are at increased risk of the effects of exposure to toxicants. This work could lead to vulnerability distributions for use in dose-response assessment. Pharmacogenetic and polymorphism probes could be incorporated into epidemiologic studies to explore key interindividual susceptibility factors and their frequency in the population. Animal models, such as genetically modified knockout mice, could be used to define the functional importance of particular genes and their polymorphisms in determining risk. The committee recommends computational research that applies systems-biology techniques to analyze how -omics end points might inform the development of distributions outlined in Table 5-1. For example, analyzing data from high-throughput screens with genomics end points may result in interpretable upstream indicators of disease vulnerability. The biochemical processes that lead to pathologic conditions or functional loss could be described by continuous parameters that may be suitable as disease biomarkers in the population. These approaches could also provide interpretable biochemical end points reflective of key steps in a toxicant’s MOA. The committee recommends exploration into interactions of exposures to chemicals that have similar or different MOAs but affect the same toxicologic process. Such research should improve understanding of issues related to background additivity. The research would also affect approaches to mixtures and combined exposures and to the question of whether it
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