Dataset Information

A Unified Probabilistic Framework for Dose-Response Assessment of Human Health Effects.

ABSTRACT:

Background

When chemical health hazards have been identified, probabilistic dose-response assessment ("hazard characterization") quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework.

Objectives

We developed a unified framework for probabilistic dose-response assessment.

Methods

We established a framework based on four principles: a) individual and population dose responses are distinct; b) dose-response relationships for all (including quantal) endpoints can be recast as relating to an underlying continuous measure of response at the individual level; c) for effects relevant to humans, "effect metrics" can be specified to define "toxicologically equivalent" sizes for this underlying individual response; and d) dose-response assessment requires making adjustments and accounting for uncertainty and variability. We then derived a step-by-step probabilistic approach for dose-response assessment of animal toxicology data similar to how nonprobabilistic reference doses are derived, illustrating the approach with example non-cancer and cancer datasets.

Results

Probabilistically derived exposure limits are based on estimating a "target human dose" (HDMI), which requires risk management-informed choices for the magnitude (M) of individual effect being protected against, the remaining incidence (I) of individuals with effects ? M in the population, and the percent confidence. In the example datasets, probabilistically derived 90% confidence intervals for HDMI values span a 40- to 60-fold range, where I = 1% of the population experiences ? M = 1%-10% effect sizes.

Conclusions

Although some implementation challenges remain, this unified probabilistic framework can provide substantially more complete and transparent characterization of chemical hazards and support better-informed risk management decisions.

SUBMITTER: Chiu WA

PROVIDER: S-EPMC4671238 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Publications

A Unified Probabilistic Framework for Dose-Response Assessment of Human Health Effects.

Chiu Weihsueh A WA Slob Wout W

Environmental health perspectives 20150522 12

<h4>Background</h4>When chemical health hazards have been identified, probabilistic dose-response assessment ("hazard characterization") quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework.<h4>Objectives</h4>We developed a unified framework for probabilistic dose-response assessment.<h4>Methods</h4>We established a framework based on four p ...[more]

PMID: 26006063

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Project description:BackgroundIn quantitative chemical risk assessment, a reference value is an estimate of an exposure to a chemical that is "likely to be without appreciable risk." Because current "deterministic" approaches do not quantitatively characterize the likelihood or severity of harm, the National Academies has recommended using reference values derived from a risk-specific dose that are treated as random variables, with probability distributions characterizing uncertainty and variability.ObjectivesIn order to build familiarity and address issues needed for routine and standardized derivation of probabilistic risk-specific dose distributions, a case example applying the unified probabilistic framework presented in Chiu and Slob (2015) is developed for acrolein. This case study is based on an updated systematic evidence map of literature (Keshava et al., 2020) identifying nasal lesions reported in Dorman et al. (2008) as the most appropriate endpoint and study for reference value derivation.MethodsThe probability distribution was calculated for the risk-specific dose, which in this implementation of the approach was calculated for the dose at which 1% of the human population is estimated to experience minimal lesions, and a probabilistic reference value was computed as the 5th percentile of this distribution. A deterministic reference value was also derived for comparison, and a sensitivity analysis of the probabilistic reference value was conducted investigating alternative assumptions for the point of departure type and exposure duration.ResultsThe probabilistic reference value of 6 × 10-4 mg/m3 was slightly lower than the deterministic reference value of 8 × 10-4 mg/m3, and the risk-specific dose distribution had an uncertainty spanning a factor of 137 (95th-5th percentile ratio). Sensitivity analysis yielded slightly higher probabilistic reference values ranging between 9 × 10-4 mg/m3 and 2 × 10-3 mg/m3.ConclusionsUsing a probabilistic approach for deriving a reference value allows quantitative characterization of the severity, incidence, and uncertainty of effects at a given dose. The results can be used to inform risk management decisions and improve risk communication.

Dataset Information

A Unified Probabilistic Framework for Dose-Response Assessment of Human Health Effects.

Background

Objectives

Methods

Results

Conclusions

Publications

A Unified Probabilistic Framework for Dose-Response Assessment of Human Health Effects.

Similar Datasets

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