State-of-the-Science workshop report: issues and approaches in low-dose-response extrapolation for Environmental Health Risk Assessment

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From: Environmental Health Perspectives(Vol. 117, Issue 2)
Publisher: National Institute of Environmental Health Sciences
Document Type: Report
Length: 5,511 words

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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. Key words: dose--response function, environmental health, low-dose extrapolation, risk assessment, workshop report. Environ Health Perspect 117:283-287 (2009).doi:10.1289/ehp.11502 available via[Online 19 September 2008]


Over the past half-century, methodologic advances have provided an increasingly strong quantitative basis for estimating the human health risks associated with exposures to environmental contaminants. Estimation of the dose--response function is one of four critical elements of the now paradigmatic approach to health risk assessment developed in 1983 by the National Research Council (NRC 1983). Establishing dose--response functions frequently requires extrapolating limited amounts of data from high-concentration animal toxicologic studies to the relatively lower concentrations typically experienced by humans. Statistical methods, known as "low-dose extrapolation" models, have been developed for this purpose, and their merits and limitations have been debated since the earliest efforts in environmental contaminant risk assessment.

Recent advancements in statistical methods have allowed for more robust epidemiologic evaluation of very large populations exposed to environmental pollutants at ambient concentrations, thus providing information that informs low-dose extrapolation issues. In studied populations, thresholds have not generally been observed for cancer or, more notably, noncancer outcomes. This observation derives primarily from studies of radiation (NRC 1999, 2005), secondhand tobacco smoke [U.S. Department of Health and Human Services (U.S. DHHS) 2004], nitrogen and sulfur oxides [U.S. Environmental Protection Agency (EPA) 2008a, 2008b], particulate matter (U.S. EPA 2006b), ozone (U.S. EPA 2006a), and lead (U.S. EPA 2006c). These studies have spurred reconsideration of the cancer and noncancer paradigms used to extrapolate dose--response relationships for the relatively low doses of environmental toxicants typically encountered in the ambient environment.

The U.S. EPA and the Johns Hopkins Risk Sciences and Public Policy Institute (RSPPI) organized a workshop, titled "State-of-the-Science Workshop: Issues and Approaches in Low Dose--Response Extrapolation for Environmental Health Risk Assessment," held 23-24 April 2007 in Baltimore, Maryland. Participants included 17 experts from diverse disciplines, including toxicology, biostatistics, human biology,...

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Gale Document Number: GALE|A194529425