Literature DB >> 27654007

Part II: Quantitative Evaluation of Choices Used in Setting Noncancer Chronic Human Health Reference Values Across Organizations.

Elizabeth Holman1, Royce Francis2, George Gray3.   

Abstract

Environmental and public health organizations, including the World Health Organization (WHO) and the U.S. Environmental Protection Agency (USEPA), develop human health reference values (HHRV) that set "safe" levels of exposure to noncarcinogens. Here, we systematically analyze chronic HHRVs from four organizations: USEPA, Health Canada, RIVM (the Netherlands), and the U.S. Agency for Toxic Substances and Disease Registry. This study is an extension of our earlier work and both closely examines the choices made in setting HHRVs and presents a quantitative method for identifying the primary factors influencing HHRV agreement or disagreement.(1) We evaluated 171 organizational comparisons, developing a quantitative method for identifying the factors to which HHRV agreement (that is, when both organizations considering the same data set the identical HHRV values) is most sensitive. To conduct this analysis, a Bayesian belief network was built using expert judgment, including the specific science policy choices analysis made in the context of setting an HHRV. Based on a sensitivity of findings analysis, HHRV agreement is most sensitive to the point of departure value, followed by the total uncertainty factor (UF), critical study, critical effect, animal model, and point of departure approach. This analysis also considered the specific impacts of individual UFs, with the database UF and the subchronic-to-chronic UF being identified as primary factors impacting the total UF differences observed across organizations. The sensitivity of findings analysis results were strengthened and confirmed by frequency analyses evaluating which choices most often disagreed when the HHRV and the total UF disagreed.
© 2016 Society for Risk Analysis.

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Keywords:  Reference dose; risk assessment; science policy

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Year:  2016        PMID: 27654007     DOI: 10.1111/risa.12699

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  2 in total

1.  Classification schemes for carcinogenicity based on hazard identification serve science and society.

Authors:  Dana Loomis; Kathryn Z Guyton; Kurt Straif; Christopher P Wild
Journal:  Regul Toxicol Pharmacol       Date:  2017-02-16       Impact factor: 3.271

2.  Conditional Toxicity Value (CTV) Predictor: An In Silico Approach for Generating Quantitative Risk Estimates for Chemicals.

Authors:  Jessica A Wignall; Eugene Muratov; Alexander Sedykh; Kathryn Z Guyton; Alexander Tropsha; Ivan Rusyn; Weihsueh A Chiu
Journal:  Environ Health Perspect       Date:  2018-05-29       Impact factor: 9.031

  2 in total

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