Standardizing Benchmark Dose Calculations to Improve Science-Based Decisions in Human Health Assessments.
Background: Benchmark dose (BMD) modeling computes the dose associated with a prespecified response level. While offering advantages over traditional points of departure (PODs), such as no-observed-adverse-effect-levels (NOAELs), BMD methods have lacked consistency and transparency in application, i...
| Publicado en: | Environmental Health Perspectives Vol. 122; no. 5; pp. 499 - 506 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
National Institute of Environmental Health Sciences
May2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103941166&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103941166 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00916765 3B5 jtl: Environmental Health Perspectives issn: 00916765 maglogo: N pubinfo: dt: May2014 vid: 122 iid: 5 pid: 56539 pub: National Institute of Environmental Health Sciences place: Research Triangle Park, North Carolina artinfo: ui: 103941166 95891839 10.1289/ehp.1307539 NLM24569956 103941166 ppf: 499 ppct: 7 formats: fmt: @attributes: type: P tig: atl: Standardizing Benchmark Dose Calculations to Improve Science-Based Decisions in Human Health Assessments. aug: au: Wignall, Jessica A. Shapiro, Andrew J. Wright, Fred A. Woodruff, Tracey J. Chiu, Weihsueh A. Guyton, Kathryn Z. Rusyn, Ivan affil: Department of Environmental Sciences and Engineering, and Gillings School of Global Public Health, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, USA sug: subj: Benchmarking Methods Dose-Response Relationship Standards Data Analysis, Statistical Pearson's Correlation Coefficient Spearman's Rank Correlation Coefficient Two-Tailed Test Unpaired T-Tests ab: Background: Benchmark dose (BMD) modeling computes the dose associated with a prespecified response level. While offering advantages over traditional points of departure (PODs), such as no-observed-adverse-effect-levels (NOAELs), BMD methods have lacked consistency and transparency in application, interpretation, and reporting in human health assessments of chemicals. Objectives: We aimed to apply a standardized process for conducting BMD modeling to reduce inconsistencies in model fitting and selection. Methods: We evaluated 880 dose-response data sets for 352 environmental chemicals with existing human health assessments. We calculated benchmark doses and their lower limits [10% extra risk, or change in the mean equal to 1 SD (BMD/L10/1SD)] for each chemical in a standardized way with prespecified criteria for model fit acceptance. We identified study design features associated with acceptable model fits. Results: We derived values for 255 (72%) of the chemicals. Batch-calculated BMD/L10/1SD values were significantly and highly correlated (R2 of 0.95 and 0.83, respectively, n = 42) with PODs previously used in human health assessments, with values similar to reported NOAELs. Specifically, the median ratio of BMDs10/1SD:NOAELs was 1.96, and the median ratio of BMDLs10/1SD:NOAELs was 0.89. We also observed a significant trend of increasing model viability with increasing number of dose groups. Conclusions: BMD/L10/1SD values can be calculated in a standardized way for use in health assessments on a large number of chemicals and critical effects. This facilitates the exploration of health effects across multiple studies of a given chemical or, when chemicals need to be compared, providing greater transparency and efficiency than current approaches. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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