State-of-the-Science Workshop Report: Issues and Approaches in Low-Dose: Response Extrapolation for Environmental Health Risk Assessment

• Published in: Environmental health perspectives 2009-02, Vol.117 (2), p.283-287
• Main Authors: White, Ronald H., Cote, Ila, Zeise, Lauren, Fox, Mary, Dominici, Francesca, Burke, Thomas A., White, Paul D., Hattis, Dale B., Samet, Jonathan M.
• Format: Article
• Language: English
• Subjects: Animal models; Animals; Cancer; Copyrights; Criteria; Disease models; Dosage; Dose response relationship; Dose-Response Relationship, Drug; Ecological risk assessment; Environmental agencies; Environmental aspects; Environmental Exposure - adverse effects; Environmental Pollutants - adverse effects; Environmental risk assessment; Epidemiology; Exposure; Extrapolation; Health; Health risk assessment; Human; Humans; Maryland; Mathematical extrapolation; Mode of action; Multidisciplinary; Neoplasms; Pollutants; Public policy; Risk; Risk assessment; Risk Assessment - methods; Thresholds; Uncertainty; United States; United States Environmental Protection Agency; Workshops
• ISSN: 0091-6765; 1552-9924
• DOI: 10.1289/ehp.11502

Low-dose extrapolation model selection for evaluating the health effects of environmental pollutants is a key component of the risk assessment process. At a workshop held in Baltimore, Maryland, on 23-24 April 2007, sponsored by U.S. Environmental Protection Agency and Johns Hopkins Risk Sciences and Public Policy Institute, a multidisciplinary group of experts reviewed the state of the science regarding low-dose extrapolation modeling and its application in environmental health risk assessments. Participants identified discussion topics based on a literature review, which included examples for which human responses to ambient exposures have been extensively characterized for cancer and/or noncancer outcomes. Topics included the need for formalized approaches and criteria to assess the evidence for mode of action (MOA), the use of human versus animal data, the use of MOA information in biologically based models, and the implications of interindividual variability, background disease processes, and background exposures in threshold versus nonthreshold model choice. Participants recommended approaches that differ from current practice for extrapolating high-dose animal data to low-dose human exposures, including categorical approaches for integrating information on MOA, statistical approaches such as model averaging, and inference-based models that explicitly consider uncertainty and interindividual variability.