Extrapolation dose-response

Hazard characterization is a quantitative or semi-quantitative evaluation of the nature, severity, and duration of adverse health effects associated with biological, physical, or chemical agents that may be present in food. The characterization depends on the nature of the toxic effect or hazard. Eor some hazards such as genotoxic chemicals, there may be no threshold for the effect and therefore estimates are made of the possible magnitude of the risk at human exposure level (dose-response extrapolation). 

Dose-Response Extrapolation Models. A dose-response model is simply a hypothetical mathematical relationship between dose-rate and probability of response. For example, the simplest form of such a model asserts that probability of tumor initiation is a linear multiple of dose-rate (provided the dosage is well below the organism s acute effect threshold for the substance in question). In general, we will express dose-response models as follows ... 

Statistical models. A number of statistical dose-response extrapolation models have been discussed in the literature (Krewski et al., 1989 Moolgavkar et al., 1999). Most of these models are based on the notion that each individual has his or her own tolerance (absorbed dose that produces no response in an individual), while any dose that exceeds the tolerance will result in a positive response. These tolerances are presumed to vary among individuals in the population, and the assumed absence of a threshold in the dose-response relationship is represented by allowing the minimum tolerance to be zero. Specification of a functional form of the distribution of tolerances in a population determines the shape of the dose-response relationship and, thus, defines a particular statistical model. Several mathematical models have been developed to estimate low-dose responses from data observed at high doses (e.g., Weibull, multi-stage, one-hit). The accuracy of the response estimated by extrapolation at the dose of interest is a function of how accurately the mathematical model describes the true, but unmeasurable, relationship between dose and response at low doses. 

In estimating the cumulative risk of a chemical in LCA, dose-response extrapolations can be based on toxicological benchmarks. Such a benchmark approach is considered more appropriate for use in comparative assessment contexts, such as in an LCA study. Benchmarks are an exposure measure associated with a consistent change in response, such as the 10% or even the 50% effect level. Regulatory-based measures do not necessarily provide a consistent risk basis for comparison, as they were often never developed for use in such a comparative context or to facilitate low dose-response extrapolation. Other data differences include the use of median, rather than extreme, data in the fate and exposure modeling, as well as the consideration of safety factors only as part of the uncertainty assessment and not as an integral part of the toxicological effects data. 

Male rat renal tubule tumors arising as a result of a process involving a2u-globulin accumulation do not contribute to the qualitative weight-of-evidence that a chemical poses a human carcinogenic hazard. Such tumors are not included in dose-response extrapolations for the estimation of human carcinogenic risk."... 

The most puzzling issue of all concerns the human being to whom we intend to extrapolate. If the issue of interspecies extrapolation concerns qualitative inferences only, then it is safe to talk generically about human beings , because it is likely that most people will respond, at some dose, to the toxic effects of a substance. But much experience tells us that the dose at which people respond varies among them some people are much more sensitive than others and will exhibit responses to the same chemical at lower doses. To make matters worse, people who are most sensitive to the effects of one chemical may not be among the most sensitive responders to another chemical that exerts its effects by a different mechanism. Discussions of dose-response extrapolation to humans need to take into account the variability in sensitivity among members of the human population. 

How the problems of selecting the appropriate animal result for dose—response extrapolation across species and of estimating the threshold dose for a broad human population are resolved in the risk assessment process will be explored in the next chapter. What has been covered here sets the stage for that discussion. 

Wiltse, J. A., and Dellarco, V. L. (2000). U.S. Environmental Protection Agency s revised guidelines for carcinogen risk assessment Evaluating a postulated mode of carcinogenic action in guiding dose-response extrapolation. Mutat Res 464, 105-115. 

EPA (2005b). Science Issue Paper Mode of carcinogenic action for cacodylic add (Dimethylarsinic add, DMA[v]) and Recommendations for dose response extrapolation. Prepared by Health Effeds Division, Office of Pesticides Programs, US Environmental Protection Agency. 1-201, http //www.epa.gov/ oppsrrdl/reregistration/cacodylic acid/dma moa.pdf. 

US EPA (2005d). Science Issue Paper Mode of Carcinogenic Action for Cacodylic Acid (Dimethylarsinic Acid, DMA(V)) and Recommendations for Dose Response Extrapolation. Office of Pesticide Programs, Health Effects Div, http //www.epa.gov/oppsrrdl/reregistration/cacodylic acid/, 201p., July 26 (accession date, August 18, 2005). 

White, R. H., Cote, I., Zeise, L., Fox, M., Dominici, F, Burke, T. A., White, P. D., Hattis, D. B., and Samet, J. M. (2009). State-of-the-Science Workshop Report Issues and approaches in low-dose-response extrapolation for environmental health risk assessment. Environ Health Perspect 117(2), 283-287. 

Table IV. Cougarison of Virtually Safe Doses (VSD) Leading to an Excess Risk of 10 for Various Dose-Response Extrapolation Models (models applied to data from (41)...

The next question to be addressed was that of the mathematical model to be used for the extrapolation. Most particularly, would one model do for all effects or was more than one required This is obviously particularly a problem with cancer. Various models have been proposed for cancer, but there has been little consideration of the use of dose/response extrapolation for effects other than cancer the safety factor approach is assumed adequate. For reasons given above, the Committee did not agree. 

Critics of dose/response extrapolation point out that the choice of model makes relatively large differences in the estimated probability at a given low dose. This is true, especially if the extreme models are included in the comparison. If only the Armi-tage-Doll, the Weibull, and the gamma are included, the differences are not too impressive. 

Polycyclic aromatic hydrocarbons are capable of forming adducts with DNA in cells. Exposure to PAHs from creosote were measured in the personal work areas of coke oven workers in the Czech Republic (Lewtas et al. 1997). Measured levels of DNA adducts in white blood cells of a nonoccupationally exposed population were well correlated with the low to moderate environmental exposures. The DNA adducts of the coke oven workers who were exposed to carcinogenic PAHs at levels of <5->200,000 ng/m3 (<0.005->200 pg/m3) did not correlate well with the exposure levels. These authors concluded that various mechanisms were responsible for the lower DNA-binding potency at the higher exposure levels, precluding the use of a linear model for dose-response extrapolation in risk assessment. 

Appropriate doses are being used so that a dose-response extrapolation will be valid... 

Figure 14. Comparative dose-response extrapolations for a carcinogen M, multistage model W, Weilbull model L, logit model G, gamma multi-hit model P, probit model. Note how models that fit this data equally well at high doses can produce very different results when extrapolated to low doses (ADB, 1992).

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