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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES 4 Risk Assessment Methods for Determining Spacecraft Water Exposure Guidelines HUMAN exposure guidelines for toxic substances are established through a multiple-step process called risk assessment. The guidelines are set for concentrations that research predicts pose acceptable (usually negligible) risks of adverse health effects to humans under specified conditions of exposure. Quite often, the objective of risk assessment is to establish a daily exposure that is considered safe over a lifetime. For space travel, the anticipated durations are substantially less than a lifetime, but the absolute lifetime risk of adverse health effects is still the focus of the risk assessment. For adverse effects that are transitory and only mildly debilitating, the intent is to ensure that exposure to substances that cause such effects is restricted to amounts that will not impede the normal performance of duties aboard spacecraft. Although the process of risk assessment uses human data whenever possible, often from epidemiologic studies, it is not aimed at estimating relative risks in the usual epidemiologic sense. Risk assessment frequently involves extrapolation from conditions under which the data are derived by observation to an unobserved or unobservable exposure situation, and it focuses on absolute risk rather than relative risk. More often than not, because of the lack of suitable human data, risk assess-
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES ment is based on data from experiments with animals. The quality of the data has a major influence on the risk assessment, and meaningful extrapolation of experimental data to an applicable human situation presents significant challenges. Below is a review of the approaches to conducting risk assessments, as well as the subcommittee's recommended approach to deriving spacecraft water exposure guidelines (SWEGs). A discussion of the exposure conversions and uncertainty factors that should be considered in the calculations is also provided. HISTORICAL PERSPECTIVE Risk Assessment for Noncarcinogenic Effects For toxic effects other than cancer, the practice of risk assessment has been to set acceptable exposure by dividing no-observed-adverse-effect levels (NOAELs) obtained from human studies or animal experiments by a set of uncertainty factors (sometimes called “safety” factors). A NOAEL is the highest experimental dose for which no difference in the occurrence of an adverse effect is observed relative to a control group. The NOAEL-based approach has come to be associated with the presumed existence of threshold doses – doses below which specific toxic effects will not occur, even if exposure continues over a lifetime. The concept of threshold is supported by the observation that many organisms have detoxification mechanisms or repair capacities to compensate for some degree of damage and still maintain normal function (Klaassen and Eaton 1991). Exposure guidance levels that result from reducing NOAELs by uncertainty factors, called acceptable daily intakes or ADIs, are presumed to pose zero risk of the toxic effect in question. In many applications, two uncertainty factors of 10 have been thought to be adequate, the first to allow for possible increased sensitivity of humans to the toxic agent compared with experimental animals and the second to account for variations in susceptibility within the human population (Lehman and Fitzhugh 1954). In experiments for which a NOAEL is not established, only a lowest-observed-adverse-effect level (LOAEL) will be available for risk assessment. A LOAEL generally corresponds to a response in the range of 1-
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES 10%, and an uncertainty factor of 10 often is used to extrapolate from a LOAEL to a NOAEL, although some investigators indicate that a factor of 3-5 would be more appropriate (Abdel-Rahman and Kadry 1995). Ideally, the selection of the uncertainty factor depends on the slope of the dose-response curve. Barnes and Dourson (1988) identified two additional uncertainty factors that might be needed for deriving references doses (RfDs), which estimate a daily exposure to the human population that is likely to be without an appreciable risk of harm during a lifetime. These additional factors represent uncertainty with respect to exposure duration and to data quality. The size of each of several uncertainty factors is determined by the best judgment of the risk assessor; however, the U.S. Environmental Protection Agency (EPA) has suggested using a maximum of 3000 for the product of four uncertainty factors and a maximum of 10,000 for five uncertainty factors (Dourson 1994). Uncertainty factors involved in the calculation of SWEGs are discussed later in this chapter. Risk Assessment for Carcinogenic Effects It has been assumed traditionally that threshold doses do not exist for carcinogenic effects, particularly those considered to result from genotoxicity. For this reason, it has been considered infeasible to establish low exposure limits that correspond to zero risk. Instead, beginning with the pioneering work of Mantel and Bryan (1961), attempts have been made to estimate carcinogenic risks on a precise, quantitative basis, to estimate exposures that produce very low, but nonzero, cancer risks. These efforts have involved fitting mathematical models to experimental data and extrapolating downward to predict risks at doses well below the experimental range. The mathematical model most frequently used for low-dose extrapolation is a variation of the multistage model of Armitage and Doll (1960), commonly expressed as P(d) = 1 − exp(−q0 −q1 d −q2d2 − . . . − qkdk) P(d) is the probability of developing cancer during a lifetime of exposure at a dose d of a carcinogen, and q0, q1, q2, . . . , qk are nonnegative
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES constants that are estimated via regression analysis of cancer data (usually animal data) at k or more dose levels. Ideally, d is a measure of target tissue dose, but most often in practice d is a measure of external exposure. According to the multistage theory, a malignant cancer cell develops in stages from a single stem cell through a series of biologic events (mutations) that occur in a specific order. Assuming that the rates of transition between two or more stages in the multistage model are linearly related to target tissue dose, the dose-response curve for the multistage model is linear at low doses (Crump et al. 1976). Low-dose linearity is generally assumed for chemical carcinogens that operate through direct interaction with genetic material. When carcinogenesis occurs by other mechanisms, low-dose linearity might not be applicable. Data developed in recent years suggest that some carcinogens, especially those whose mechanisms of action involve cytotoxicity or disruption of hormonal homeostasis, exhibit practical threshold doses below which the risk of cancer is negligible (Page et al. 1997; Hill et al. 1998). However, if there is a nonzero background cancer risk and if the mechanism of the nongenotoxic carcinogen is the same as the background mechanism, then this “additivity” of cancer risk still implies linearity at very low doses for dose-response relationships that are strictly increasing. Hence, linear extrapolation has been widely used in low-dose cancer risk assessment in the absence of clear information to dictate a different course of action (OSTP 1985; EPA 1996a). Risk assessments that deviate from the use of linear extrapolation require considerable data to ensure that the traditional default approach is not applicable. Uncertainties in the process of establishing acceptable exposures have been handled differently for carcinogenic and noncarcinogenic effects. For example, instead of a factor of 10 for interspecies uncertainty, a factor derived from a power function of body weight often is used for interspecies conversion (EPA 1992). Also, in general, no uncertainty factor is used for human variation in sensitivity to a substance's carcinogenic effects. However, variation in the experimental data is a source of uncertainty that is recognized for carcinogenic effects through the use of statistical confidence limits instead of central estimates.
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES RECOMMENDED APPROACH TO RISK ASSESSMENT Exploiting Similarities of Historical Approaches Gaylor (1983) was among the first to point out the practical similarities between low-cancer-risk dose based on linear extrapolation and those that would result from the reduction of cancer NOAELs by uncertainty factors. In light of Gaylor's observation that the NOAEL for cancer often corresponds to a central estimate of risk of approximately 10−2 (1%), then reducing such a cancer NOAEL by an overall uncertainty factor of 100, 1000, or 10,000 would result in the same dose that would be obtained by linear extrapolation to a risk level of 10−4, 10−5, or 10−6, respectively (Kodell and Park 1995). Conversely, if the true response rate at the NOAEL for a noncarcinogenic effect is acknowledged to be other than zero, say around 1%, then the application of linear extrapolation for a noncarcinogenic effect to estimate a dose with a risk level k orders of magnitude lower would be equivalent to dividing the NOAEL by an uncertainty factor of 10k. The functional equivalence of the two approaches has been highlighted by Wilson (1997). Despite the apparent practical similarities between the two opposing approaches to risk assessment, little has been done until recently to unify them. Proponents of low-dose linear extrapolation have questioned the presumption by NOAEL proponents that zero-risk limits (thresholds) can be established based on experimental observations; proponents of the NOAEL-uncertainty factor approach have questioned the presumption by modeling proponents that precise risks can be attached to doses below the observed experimental range. Recently, however, proposals have been advanced for the unification of risk assessment procedures for carcinogenic and noncarcinogenic effects (Purchase and Auton 1995; Crump et al. 1996; Gaylor et al. 1999). There is a movement to place less emphasis on numerical estimates of risk of cancer below the data range, and to place more emphasis on estimation of risk of noncancer effects within the data range. The objective is to combine the best features of the two methods into a unified approach to setting safe exposure for all types of toxic effects. Exploration and development of refined models for low-dose extrapolation is not discouraged. Rather, as biologic processes are better un-
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES derstood, it is expected that improved mathematical models for risk assessment will evolve. Several promising new approaches are discussed later in this chapter. However, the usual data that are available for risk assessment do not permit precise estimates of risk to be made at doses below the data range. For this reason, the risk assessment methodology presented here emphasizes model fitting within the data range for carcinogenic and noncarcinogenic effects. Benchmark-Dose Approach to Setting SWEGs It is important that dose-response data are adequate to establish a NOAEL. However, various authors have documented limitations of the NOAEL as a basis for establishing acceptable exposure (Munro and Krewski 1981; Crump 1984; Kimmel and Gaylor 1988). The determination of the NOAEL is limited by the number and distribution of doses and by sample sizes; using the NOAEL as a basis for setting exposure limits ignores dose-response information. As an alternative to the NOAEL, Crump (1984) proposed use of a benchmark dose (BMD) – a statistical lower confidence limit on a dose that is estimated to correspond to a low level of excess risk above background in the range of 1-10% (ED01 to ED10; EDp is an effective dose that yields a response of p). Because of its accounting for experimental variation, the BMD could be lower than the NOAEL and thus could result in lower acceptable exposure limits after it has been reduced by uncertainty factors. Experimental variation, however, is an important source of uncertainty that has been neglected heretofore in risk assessment for noncarcinogenic effects. The BMD originally was defined as a statistical lower confidence limit on the EDp, for 0.01 ≤ p ≤ 0.10. In addition to the original suggestion of Crump (1984), observations by other investigators also argue for establishing the BMD to correspond to the response range between 1% and 10%. As observed by Gaylor (1992) and Allen et al. (1994a), the incidence of fetal malformation at the NOAEL in typical teratology studies often exceeds 1%. Leisenring and Ryan (1992) argue that the average risk at the NOAEL for quantal data could easily be as much as 10%, depending on the experimental design and the shape of the dose-
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES response curve. In an analysis of 486 developmental toxicity studies, Allen et al. (1994a) conclude that the average NOAEL approximated a lower 95% confidence limit on the ED05. Several investigators recommend the ED01 as an anchor point for risk estimates for carcinogenic effects (Van Ryzin 1980; Farmer et al. 1982; Gaylor et al. 1994). The intent is to avoid dependence on particular mathematical models, which is most apparent at doses below the ED01 (Krewski and Van Ryzin 1981). EPA has proposed the ED10 as a point of departure for cancer risk assessment (EPA 1996a). It is recommended that, for chemicals for which there are sufficient dose-response data, a BMD corresponding to a 1% risk (BMD01) be used instead of the NOAEL and that a BMD corresponding to a 10% risk (BMD10) be used instead of the LOAEL. Like the NOAEL and LOAEL, the BMD 01 and BMD10 are merely starting points for establishing safe exposures, but they have more precise definition and determination. Like the NOAEL and LOAEL, they are meant to correspond to very low risk. These BMDs should serve as starting points for setting acceptable human exposures to substances for all types of toxic effects, whether carcinogenic or noncarcinogenic. In the process of setting the exposure levels, BMDs must be modified by appropriate conversion factors and reduced by appropriate uncertainty factors, as will be discussed in subsequent sections. The resulting exposure guidance levels do not have specific risk connotations attached to them, but they are simply expected to reflect adequate safety. When sufficient data are available, the unified BMD-based method for calculating acceptable human exposures is recommended for determining maximum contamination in water aboard spacecraft – spacecraft water exposure guidelines (SWEGs). The BMD approach is an evolving strategy that will assist in the calculation of SWEGs when adequate data are available. At the current stage of development of the BMD, the recommended method for establishing SWEGs is to determine the lower-confidence, model-based likelihood of a BMD01 level and apply appropriate uncertainty factors if necessary. This approach represents a recommended decision process to establish acceptable guidelines, but others, such as the lower confidence limit of a BMD 10 or central estimates of the BMD, might be more useful for data that are available. Further evolution of BMD methodology should be moni-
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES tored and appropriate alterations in the approach should be made as warranted. In the absence of sufficient data, or when special circumstances dictate, the recommended default procedure for determining SWEGs is essentially the NOAEL-based procedure currently in use for setting maximum contamination levels in air aboard spacecraft – spacecraft maximum allowable concentrations (SMACs) (NRC 1992; James and Gardner 1996). BMD CALCULATION Central Estimate Versus Confidence Limit Estimating the BMDp involves fitting a dose-response model to observed data and calculating the dose level that corresponds to an excess response, p, above background. Because the estimation of benchmark doses does not stray far from the observed data range, the choice of model might not be critical. As pointed out by Krewski and Van Ryzin (1981), fitted dose-response models for quantal toxicity data do not differ appreciably at responses above 1%. However, as much as possible, knowledge of the biologic mode of action should be used in modeling the dose-response data (Andersen et al. 2000; Wiltse and Dellarco 2000). Clearly, the validity of the observed dose-response data for risk assessment must be ascertained before BMDp estimation begins. It is desirable that methods used to fit dose-response models to observed data include provisions for calculating statistical confidence limits, because experimental variation is a source of uncertainty that must be considered. Instead of using a formal statistical lower confidence limit on a BMDp as a starting point, one could calculate a central estimate of the BMDp, and reduce it by an uncertainty factor to account for experimental variation. The result would be the same, but the expression of the lower confidence limit on the BMDp via an uncertainty factor for experimental variation provides explicit information regarding the magnitude of this source of uncertainty. The uncertainty factor would be just one of several that would be used to reduce the central estimate to an acceptable exposure guidance level (T.B. Starr, TBS Associates, personal communication, 1997). Thus, the use of confidence
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES limits instead of central estimates is intended to capture the experimental uncertainty rather than to provide “better” estimates. This topic is discussed further later in this chapter. Estimating BMDp for Various Toxic Effects Traditional methods of dose-response modeling for binomially distributed random variables can be used to estimate carcinogenic effects and other quantal toxic responses (lethality, some mutagenic responses) for which subjects are assumed to respond independently from one another. Maximum likelihood estimation is a commonly accepted method of fitting a variety of mathematical dose-response models, including the multistage model, the probit model, or the Weibull model (Crump 1979; Zeise et al. 1987). The maximum likelihood method essentially identifies values of a model's parameters that have the highest likelihood of being correct, given the observed data used to fit the model. Generally, the only data available for modeling will be crude, lifetime incidences. If, however, data on time to occurrence of effects are available, the use of a model that can exploit this additional information is encouraged (e.g., Lensing and Kodell 1995). Maximum likelihood estimation procedures have been worked out for fitting dose-response models for quantal effects that are assumed to be correlated between subjects. Chen and Kodell (1989), Ryan (1992), Allen et al. (1994a,b), and Krewski and Zhu (1995) all have proposed methodology for calculating BMD p for toxicity data that are overdispersed with respect to simple binomial variation. For continuous data, such as that arising in neurotoxicity studies, the definition of frank, adverse effects is not straightforward. Such data often are described well by normal (Gaussian) or lognormal distributions. Hence, modeling continuous responses on a probability scale to estimate the dose corresponding to a specified probability, p, of an adverse effect (BMDp) is difficult. However, methods of risk assessment for such data have been developed (Gaylor and Slikker 1990; Kodell and West 1993; Crump 1995; Kavlock et al. 1995; Bosch et al. 1996), including provisions for calculating BMD. Hence, BMDp for continuous, quantitative toxic responses can be calculated. Appendix B provides examples of BMD estimation.
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES EXPOSURE CONVERSION Target Tissue Dose Toxic substances sometimes require some form of metabolic activation to exert their adverse health effects, which might range from direct, short-term, target tissue toxicity to carcinogenesis. If metabolic activation can be characterized adequately by a pharmacokinetic model, then the dose delivered to the target should be used instead of the administered dose, for purposes of dose-response modeling to estimate BMD. Although the use of delivered dose rather than administered dose can be expected to lead to more accurate predictions of risk, pharmacokinetic modeling could actually lead to additional uncertainty, if physiologically based pharmacokinetic models with many parameters are used for tissue dosimetry (Farrar et al. 1989; Portier and Kaplan 1989). Hence, the question of whether to use target tissue dose or administered dose for dose-response modeling depends on the degree of confidence that can be placed in the pharmacokinetic model. Differences in Duration For toxic effects that are believed neither to accumulate nor to increase in adversity over time, a single exposure level for a toxicant can be used for SWEGs of different durations. However, for many toxic end points, an adjustment of the exposure will be required when extrapolating from one duration to another. Whenever possible, such extrapolation should use substance-specific, time response information, which can be in the form of an empirical mathematical relationship between exposure concentration and duration. For example, ten Berge et al. (1986) investigated the relationship between concentration and exposure time based on mortality data from 20 acute studies of locally and systemically acting inhalation toxicants. Using probit analysis, they found that the relationship CN× T = K provided a good explanation of the relationship between concentration and duration. C is the concentration of the agent, T is the duration of exposure, and K is a constant. The value of N was generally greater than 1 and had an average value of approximately 1.8. (In fact, they found that the relation-
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES ship Cn × Tm = k described the data well; the average value of n was approximately 3.5 and the average value of m was approximately 2.0. The expression Cn × Tm = k is actually equivalent to CN × T = K, where N = n/m and K = k1/m. Alternatively, the ten Berge rule could be expressed as C ×TM=K, with M = m/n and K = k1/n.) The simplest form of ten Berge's formula is C × T = K, commonly known as Haber's rule, for inhalation toxicants. In the absence of chemical-specific information on the relationship between concentration and duration, Haber's rule often has been used as a default approach for making conversions for different (relatively short) durations of exposure. In its guidelines for the establishment of SMACs for airborne contaminants, the NRC (1992) urged caution in the use of this simple approach, and, for noncarcinogenic effects, the NRC subcommittee on SMACs has been reluctant to endorse its use for converting doses derived from longer term exposures to doses that would apply for shorter term exposures (see also James and Gardner 1996). However, like the NRC Subcommittee on Emergency Exposure Guidance Levels (NRC 1986), the subcommittee on SMACs does consider the use of C × T = K appropriate for extrapolating between two exposures that are relatively short term with respect to clearance or repair rate. Also, in the absence of definitive information, the subcommittee on SMACs has endorsed this approach for converting doses corresponding to shorter term exposures to doses corresponding to longer term exposures, although each substance must be considered individually with respect to the applicability of Haber's rule. A simple comparison of ten Berge's rule to Haber's rule is given in Table 4-1, using N = 2, where the reference concentration is 50 parts per million (ppm) with a duration of 2 days (d). Conversions are made for 1-d and 4-d exposures. For N > 1, ten Berge's rule will give smaller concentrations than will Haber's rule in converting to shorter durations. It will give larger concentrations than will Haber's rule in converting to longer durations. The National Advisory Committee for Acute Exposure Guideline Levels for Hazardous Substances (NAC/AEGL Committee) (EPA 1997) uses the relationship CN× T = K proposed by ten Berge et al. (1986) to make conversions for different exposure durations in the setting of AEGLs. This relationship should be used whenever possible in making duration conversions when setting SWEGs for water contaminants
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES of SWEGs, all observed toxic effects are considered, including mortality, morbidity (functional impairment), reproductive toxicity, genotoxicity, carcinogenicity, neurotoxicity, immunotoxicity, hepatotoxicity, and respiratory toxicity. For effects that are considered relevant to humans, generally the most sensitive effect determines the SWEG. That is, for a given chemical, potential SWEGs are calculated for a specific exposure duration in space (1, 10, 100, or 1000 d) using data on a variety of toxic end points. Based on the critical significance of the health effect identified, the lowest of those potential SWEGs is then chosen as the SWEG for that substance for that duration of exposure. However, any potential SWEG that is within a factor of 3 of the lowest potential SWEG is also considered a determining factor of that SWEG. Comparisons with Established Values All documents used to establish previous industrial or public-health exposure guidance levels for water contaminants should be reviewed before SWEG values are set for NASA. In particular, previous NRC documents on acceptable exposures in drinking water (e.g., NRC 1987b) and water contaminant limits established by EPA, both the maximum contaminant limits and the health advisories (EPA 1996b), provide important reference points for comparison. Such comparisons are not simply to mimic guidance levels set by other entities, but to determine whether the SWEGs that are set in response to NASA's special needs are reasonable in light of previously set concentrations. Finally, the NRC documents on SMACs must be reviewed to ensure compatibility of standards for water with those for air (NRC 1994; 1996a,b; 2000). Any significant differences between exposure levels should be discussed and justified, which would include an evaluation of the approaches and data used to derive the guidance levels. ALTERNATIVE APPROACHES This section describes several approaches that are under development for setting acceptable exposure guidelines for toxic substances. These approaches are valid to consider when setting SWEGs, although they generally require more data than are readily available. Progress
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES in the development of these refined approaches should be monitored, so that they can be included as appropriate in the process of setting SWEGs. Integrated PBPK and BBDR Models Just as the multistage model of Armitage and Doll (1960) replaced the earliest susceptibility models, probit and logit, as the primary basis for carcinogenic risk assessment, in recent years more refined biologically based dose-response (BBDR) models have been proposed as replacements for the multistage model. The most popular is the two-stage clonal expansion model of Moolgavkar and colleagues (e.g., Moolgavkar and Luebeck 1990), and extensions thereof (Portier and Kopp-Schneider 1991; Zheng et al. 1995). The BBDR model characterizes the important role of cellular proliferation in cancer. There has been a strong belief that, with sufficient biologic data on the components of the cancer process, complex BBDR models will provide the means for estimating risks below the dose-response range based on biologic knowledge rather than on assumptions. Concomitant with the refinement of BBDR models has been the development of ever more sophisticated physiologically based pharmacokinetic (PBPK) models, which have been used to obtain better estimates of target tissue doses for risk assessment (Andersen et al. 1993; Kohn et al. 1993). In some cases, this has led to significant modification of risk assessments originally based on the linearized multistage model (e.g., Starr 1990). However, it is only recently that PBPK and BBDR models have been fully integrated into the risk assessment process. Although the results are still the subject of scientific debate, the recent reassessment of TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin) by EPA (1998) used a fully integrated PBPK-BBDR model to estimate risk of liver cancer in rats. Whether this refined approach will provide more reliable estimates of cancer risk below the experimental dose range is open to question. Nevertheless, the results should be carefully scrutinized to determine whether that is the appropriate direction for risk assessment to take. In the rare case that such data are available for this refined modeling, the exercise certainly should be carried out, and the results should be compared against the general procedure outlined above for setting SWEGs, before SWEG are set. In addition to more refined biologic models for carcinogenesis, there
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES have been isolated attempts to develop BBDR models for noncancer effects, specifically for developmental toxicity (Freni and Zapisek 1991; Shuey et al. 1994, 1995; Leroux et al. 1996) and neurotoxicity (Slikker et al. 1998). Ordinal Regression A technique called ordinal regression has been proposed as a way to combine data on various toxic effects into a single analysis. The method was first proposed by Hertzberg and Miller (1985) and was later refined by Guth et al. (1991). With ordinal regression, health effects are first assigned to severity categories based on the reported information and consideration of biologic and statistical significance. The aggregate group of subjects at any particular dose and duration of exposure is classified as giving evidence of a specific severity of response. Models such as the logistic regression model are applied with the severity code as the dependent variable and the exposure concentration, duration of exposure, and species as the independent variables. The method allows incorporation of quantal and quantitative data, and it enables the simultaneous analysis of data from many studies. One trade-off is the loss of target-organ toxicity. The output from ordinal regression is especially useful in that, for any level of severity, it can provide a concentration-by-duration profile (central estimates and confidence limit estimates) for any amount of risk. That capability is particularly useful for making duration conversions, because approaches such as the concentration-by-time conversion are not required. Furthermore, if sufficient human data are available to include in the regression analysis, then interspecies uncertainty is reduced. The ordinal regression method continues to be refined and to be applied to specific toxicants (Simpson et al. 1996), but the complexities of the model fitting appear to make it infeasible for routine use. Nevertheless, whenever possible, the method ought to be applied, and the results should be compared against the general procedure outlined above for obtaining SWEGs before SWEG values are set. Most if not all applications of ordinal regression have been restricted to acute toxic effects, specifically excluding carcinogenic effects. Whether all types of toxic effects, including cancer, can be modeled simultaneously using ordinal regression is still undetermined.
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES Change-Point Dose-Response Models In a practical sense, replacing a NOAEL with a BMDp is scientifically justified, in light of the studies reported above that have documented nonzero risk (risk = p > 0, for 0.01 ≤ p ≤ 0.10) associated with NOAELs. In a theoretical sense, however, replacing a NOAEL with a BMDp is inconsistent, because a NOAEL is intended to represent a dose with true zero risk – a threshold. In theory, then, if it were possible to estimate reliably a true threshold dose by way of a mathematical model, it would make sense to replace the NOAEL with this estimated threshold dose, instead of the BMDp. There is research into the use of so-called change-point dose-response models for risk assessment, where the change-point is a dose value that determines where the model changes from a constant response model to a dose response model. Hence, the change-point is a threshold dose, which is a parameter estimated as part of the modeling exercise. It must be emphasized that any estimate of a threshold from current BMD dose-response models is entirely empirical and has no biological basis. If change-point models are shown to be practical, then the guidelines for basing SWEGs on BMDps should be revisited to evaluate the feasibility of using change-points instead of BMDps for presumed threshold effects. However, the use of estimated change-points for threshold effects and BMDps for nonthreshold effects would destroy the unity of the proposed approach for all types of toxic effects, including threshold and nonthreshold effects. SUMMARY Using the process of risk assessment to establish SWEGs involves several important steps. Although the intent here has been to provide guidance for implementing this step-by-step process, it must be emphasized that scientific judgment is critical at every step, and it should be the overriding factor throughout the process. Scientific judgment is based on the aggregate of biologic information. Because the process involves a series of extrapolations, each with its own degree of uncertainty, attempting to identify exposures to which specific, low amounts of risk can be attached is not recommended. Instead, emphasis is placed on establishing concentrations that are judged to be reasonably safe for human exposure, based on the best scientific infor-
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METHODS FOR DEVELOPING SPACECRAFT WATER EXPOSURE GUIDELINES mation and judgment available. This approach to establishing SWEGs is in line with current thinking on risk assessment, which is moving away from emphasizing numerical estimates of risk for extremely low exposures and is moving toward simply identifying exposures for which the risk of adverse human health effects is judged to be negligible, regardless of whether such effects are carcinogenic or not. REFERENCES Abdel-Rahman,M.S., and A.M. Kadry. 1995. Studies on the use of uncertainty factors in deriving RfDs. Hum. Ecol. Risk Assess. 1(5):614-624. ACGIH (American Conference of Governmental Industrial Hygienists) . 1991. Documentation of the Threshold Limit Values and Biological Exposure Indices, 6th Ed. Cincinnati, OH: American Conference of Governmental Industrial Hygienists. Allen, B.C., K.S. Crump, and A.M. Shipp. 1988. Correlation between carcinogenic potency of chemicals in animals and humans. Risk Anal. 8(4):531-544. Allen, B.C., R.J. Kavlock, C.A. Kimmel, and E.M. Faustman. 1994a. Dose-response assessment for developmental toxicity. II. Comparison of generic benchmark dose estimates with no observed adverse effect levels. Fundam. Appl. Toxicol. 23(4):487-495. Allen, B.C., R.J. Kavlock, C.A. Kimmel, and E.M. Faustman. 1994b. Dose-response assessment for developmental toxicity. III. Statistical models. Fundam. Appl. Toxicol. 23(4):496-509. Andersen, M.E., J.J. Mills, M.L. Gargas, L. Kedderis, L.S. Birnbaum, D. Neubert, and W.F. Greenlee. 1993. Modeling receptor-mediated processes with dioxin: Implications for pharmacokinetics and risk assessment. Risk Anal. 13(1):25-36. Andersen, M.E., M.E. Meek, G.A. Boorman, D.J. Brusick, S.M. Cohen, Y.P. Dragan, C.B. Frederick, J.I. Goodman, G.C. Hard, E.J. O'Flaherty, and D.E. Robinson. 2000. Lessons learned in applying the U.S. EPA proposed cancer guidelines to specific compounds. Toxicol. Sci. 53(2):159-172. Armitage, P., and R. Doll. 1960. Stochastic models for carcinogenesis. Pp. 19-38 in Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 4, J. Neyman, ed. Berkeley, CA: University of California Press. Baird, S.J.S., J.T. Cohen, J.D. Graham, A.I. Shlyakhter, and J.S. Evans. 1996. Noncancer risk assessment: A probabilistic alternative to current practice. Hum. Ecol. Risk Assess. 2(1):79-102. Barnes, D.G., and M. Dourson. 1988. Reference dose (RfD): Description and
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Representative terms from entire chapter: