The following HTML text is provided to enhance online
readability. Many aspects of typography translate only awkwardly to HTML.
Please use the page image
as the authoritative form to ensure accuracy.
Review of the Environmental Protection Agency’s Draft IRIS Assessment of Tetrachloroethylene
nonlinear shape of the dose-response relationship, the variation in unit risk calculated by the models would be much greater. Even in the case of MCL in male rats, the risk obtained by linear extrapolation to 1.5 × 10-5 mEq/kg per day varied by up to several orders of magnitude among the same four models (Table 5B-2). Therefore, choosing a multistage model on the basis that risks with other models at a POD are similar is difficult to justify.
More detail would have been helpful in a few of EPA’s analyses of uncertainties. For example, EPA’s assessment of uncertainties under different model forms (multistage, Weibull, log-probit, and log-logistic) used bootstrap simulations. The results show variation in extra risk spanning orders of magnitude at the low dose of 1.5 × 10-5 mEq/kg per day (bootstrap mean, 9.172 × 10-7 to about 1.078 × 10-3 in Table 5B-2) among the models despite their comparable goodness of fit to the dataset on MCL in male rats. Details about the bootstrap methods and scheme would facilitate appropriate understanding of the bootstrap distributions. For example, what was the number of bootstrap replications? What bootstrap method was used to simulate the distribution of extra risk? The committee views EPA’s consideration of uncertainty due to different forms of the dose-response relationship highly valuable, and it encourages EPA to extend such quantitative evaluation to all candidate datasets so that a fuller array of uncertainties can be assessed.
The committee notes that EPA discusses uncertainties in detail. However, the discussion typically focuses on individual sources without an in-depth illustration of the propagation of the uncertainties and their cumulative effect on the final risk estimate. That limitation is in part the result of qualitative treatment of uncertainties in many instances, notably concerning MOA, the choice of bioassay, and human variations. New methods that allow probabilistic quantification of the overarching uncertainty and of the variation in the final risk estimate are emerging (see Chapter 12). The capability to quantify the full range of overarching uncertainties associated with risk estimates facilitates separation of the science of risk assessment from risk-management decision-making. The committee encourages EPA to consider recommendations in Science and Decisions (NRC 2009) regarding uncertainty and variability.