Risk assessment dose—response thresholds, estimation

For all toxic effects other than carcinogenicity, a threshold in the dose-response curve is assumed. The lowest NOAEL from all available studies is assumed to be the approximate threshold for the groups of subjects (humans or animals) in which toxicity data were collected. Alternatively, a benchmark dose (BMD) may be estimated from the observed dose-response curve, and used as the point-of-departure for risk assessment (see below and Box). 

The 95% confidence limits of the estimate of the linear component of the LMS model, /, can also be calculated. The 95% upper confidence limit is termed qi and is central to the US-EPA s use of the LMS model in quantitative risk assessment, as qi represents an upper bound or worst-case estimate of the dose-response relationship at low doses. It is considered a plausible upper bound, because it is unlikely that the tme dose-response relationship will have a slope higher than qi, and it is probably considerably lower and may even be zero (as would be the case if there was a threshold). Lfse of the qj as the default, therefore, may have considerable conservatism incorporated into it. The values of qi have been considered as estimates of carcinogenic potency and have been called the unit carcinogenic risk or the Carcinogen Potency Factor (CPF). 

In classifying waste, deterministic responses generally should be of concern only for hazardous chemicals (see Section 3.2.2.1). Therefore, the only important issue for risk assessment is the most appropriate approach to estimating thresholds for induction of responses in humans. The primary concern here is that consistent approaches should be used for all substances that induce deterministic effects. NCRP s recommendation that nominal thresholds in humans should be estimated using the benchmark dose method and a safety factor of 10 or 100, depending on whether the data were obtained in a study in humans or animals (see Section 6.1.2.1), is intended to provide consistency in estimating thresholds for all substances that cause deterministic effects. 

In many respects, the foundations and framework of the proposed risk-based hazardous waste classification system and the recommended approaches to implementation are intended to be neutral in regard to the degree of conservatism in protecting public health. With respect to calculations of risk or dose in the numerator of the risk index, important examples include (1) the recommendation that best estimates (MLEs) of probability coefficients for stochastic responses should be used for all substances that cause stochastic responses in classifying waste, rather than upper bounds (UCLs) as normally used in risk assessments for chemicals that induce stochastic effects, and (2) the recommended approach to estimating threshold doses of substances that induce deterministic effects in humans based on lower confidence limits of benchmark doses obtained from studies in humans or animals. Similarly, NCRP believes that the allowable (negligible or acceptable) risks or doses in the denominator of the risk index should be consistent with values used in health protection of the public in other routine exposure situations. NCRP does not believe that the allowable risks or doses assumed for purposes of waste classification should include margins of safety that are not applied in other situations. 

For food allergens, validated animal models for dose-response assessment are not available and human studies (double-blind placebo-controlled food challenges [DBPCFCs]) are the standard way to establish thresholds. It is practically impossible to establish the real population thresholds this way. Such population threshold can be estimated, but this is associated with major statistical and other uncertainties of low dose-extrapolation and patient recruitment and selection. As a matter of fact, uncertainties are of such order of magnitude that a reliable estimate of population thresholds is currently not possible. The result of the dose-response assessment can also be described as a threshold distribution rather than a single population threshold. Such distribution can effectively be used in probabilistic modeling as a tool in quantitative risk assessment (see Section 15.2.5)... 

Two examples of alternative approaches to cancer risk assessment would be estimations based on threshold-response (EPA, 2005a) and benchmark dose modeling (EPA, 1995, 2000). As a practical matter, if the proposed basis of safety relies on a threshold or mode-of-action characterization to dismiss or mitigate animal tumor data, PDA would reconunend that the safety narrative clearly discuss the scientific rationale and present all relevant data for consideration. In the absence of adequate evidence to the contrary, PDA presumes that certain assumptions are appropriately protective of safety, namely that (i) the induction of tumors in animals is relevant to human... 

Dose-response assessment follows the hazard identification in the risk assessment process. In dose-response assessment, an adverse effect is presumed to either exhibit a threshold or not in the dose-response curve. Depending on the nature of this curve, different approaches are employed to estimate the risk posed by the potential toxic agent. 

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. 

A few court decisions, however, have been more skeptical of the linear model. Eor example, the U.S. EPA s use of the linear, no-threshold model in its risk assessment for drinking water chlorinated byproducts was rejected by the court because it was contrary to evidence suggesting a nonlinear model that had been accepted by both the U.S. EPA and its Science Advisory Board (CCC 2000). On the other hand, the U.S. OSHA s departure from the linear, no-threshold model in its formaldehyde risk assessment was likewise rejected by the court (lU 1989). The court held that the U.S. OSHAhad improperly used the maximum likelihood estimate (MLE) rather than the upper confidence limit (UCL) to calculate risk, and the UCL but not the MLE model was consistent with a linear dose-response assumption. The court held that the U.S. OSHA had failed to justify its departure from its traditional linear, no-threshold dose-response assumption. 

Quantitative risk assessment requires extrapolation from results of experimental assays conducted at high dose levels to predicted effects at lower dose levels which correspond to human exposures. The meaning of this high to low dose extrapolation within an animal species will be discussed, along with its inherent limitations. A number of commonly used mathematical models of dose-response necessary for this extrapolation, will be discussed. Other limitations in their ability to provide precise quantitative low dose risk estimates will also be discussed. These include the existence of thresholds incorporation of background, or spontaneous responses modification of the dose-response by pharmacokinetic processes. 

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