Issues in using human variability distributions to estimate low-dose risk.
Background: The National Research Council (NRC) Committee on Improving Risk Analysis Approaches Used by the U.S. EPA (Environmental Protection Agency) recommended that low-dose risks be estimated in some situations using human variability distributions (HVDs). HVD modeling estimates log-normal distr...
| Publicado en: | Environmental Health Perspectives Vol. 118; no. 3; pp. 387 - 394 |
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| Autores principales: | , , |
| Formato: | equations & formulas tables/charts Journal Article |
| Publicado: |
National Institute of Environmental Health Sciences
Mar2010
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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=105169227&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105169227 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00916765 3B5 jtl: Environmental Health Perspectives issn: 00916765 maglogo: N pubinfo: dt: Mar2010 vid: 118 iid: 3 pid: 56539 pub: National Institute of Environmental Health Sciences place: Research Triangle Park, North Carolina artinfo: ui: 105169227 2010620760 10.1289/ehp.0901250 NLM20064772 PMC2854768 105169227 ppf: 387 ppct: 7 formats: fmt: @attributes: type: P tig: atl: Issues in using human variability distributions to estimate low-dose risk. aug: au: Crump KS Chiu WA Subramaniam RP affil: Louisiana Tech University, P.O. Box 10348, Ruston, LA 71272-0046, USA; kennycrump@email.com sug: subj: Carcinogens Dose-Response Relationship Models, Statistical Risk Assessment United States Environmental Protection Agency Pharmacokinetics Toxicology United States ab: Background: The National Research Council (NRC) Committee on Improving Risk Analysis Approaches Used by the U.S. EPA (Environmental Protection Agency) recommended that low-dose risks be estimated in some situations using human variability distributions (HVDs). HVD modeling estimates log-normal distributions from data on pharmacokinetic and pharmacodynamic variables that affect individual sensitivities to the toxic response. These distributions are combined into an overall log-normal distribution for the threshold dose (dose below which there is no contribution to a toxic response) by assuming the variables act independently and multiplicatively. This distribution is centered at a point-of-departure dose that is usually estimated from animal data. The resulting log-normal distribution is used to quantify low-dose risk. Objective: We examined the implications of various assumptions in HVD modeling for estimating low-dose risk. Methods: The assumptions and data used in HVD modeling were subjected to rigorous scrutiny. Results: We found that the assumption that the variables affecting human sensitivity vary log normally is not scientifically defensible. Other distributions that are equally consistent with the data provide very different estimates of low-dose risk. HVD modeling can also involve an assumption that a threshold dose defined by dichotomizing a continuous apical response has a log-normal distribution. This assumption is shown to be incompatible (except under highly specialized conditions) with assuming that the continuous apical response itself is log normal. However, the two assumptions can lead to very different estimates of low-dose risk. The assumption in HVD modeling that the threshold dose can be expressed as a function of a product of independent variables lacks phenomenological support. We provide an example that shows that this assumption is generally invalid. Conclusion: In view of these problems, we recommend caution in the use of HVD modeling as a general approach to estimating low-dose risks from human exposures to toxic chemicals. Key words: dose-response model, human variability distribution, log-normal distribution, low-dose risk, risk assessment, threshold distribution. pubtype: Academic Journal doctype: equations & formulas tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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