Literature DB >> 7838990

Use of probabilistic expert judgment in uncertainty analysis of carcinogenic potency.

J S Evans1, G M Gray, R L Sielken, A E Smith, C Valdez-Flores, J D Graham.   

Abstract

A new approach to characterizing the state of knowledge about carcinogenic potency is described. In this approach, the carcinogenic risk posed by a specific dose is characterized by a probability distribution, indicating the relative likelihood of different risk estimates. The approach utilizes expert judgment and a probability tree and is illustrated in a case study of chloroform exposure. Experts in cancer biology/toxicology, pharmacokinetics, and dose-response modeling were identified by a panel of science-policy specialists. In a workshop, experts reviewed the chloroform data, received training in probability elicitation, and constructed a consensual probability tree based on biological theories of cancer causation. Distributions of carcinogenic risk were developed based on the probability tree, chloroform data, judgmental probabilities provided by the experts, and classical statistical techniques. Risk distributions varied considerably between experts, with some predicting essentially no risk from 100 ppb chloroform in drinking water while other have at least some probability on risks generally considered of regulatory significance. Estimated human risk was much lower when extrapolating from liver tumors in animals than from kidney tumors. Issues of scientific disagreement leading to different risk distributions between experts are discussed. The resulting risk distributions are compared to standard EPA risk calculations for the same exposure scenario as well as to the expert judgement of epidemiologists about cancer risks of chlorinated drinking water. Issues in combining expert judgments are discussed, and several alternative methods are presented. Strengths and weaknesses of the distributional approach are discussed.

Entities:  

Mesh:

Substances:

Year:  1994        PMID: 7838990     DOI: 10.1006/rtph.1994.1034

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  7 in total

Review 1.  A methodology for performing global uncertainty and sensitivity analysis in systems biology.

Authors:  Simeone Marino; Ian B Hogue; Christian J Ray; Denise E Kirschner
Journal:  J Theor Biol       Date:  2008-04-20       Impact factor: 2.691

2.  Use (and abuse) of expert elicitation in support of decision making for public policy.

Authors:  M Granger Morgan
Journal:  Proc Natl Acad Sci U S A       Date:  2014-05-12       Impact factor: 11.205

Review 3.  An audit of uncertainty in multi-scale cardiac electrophysiology models.

Authors:  Richard H Clayton; Yasser Aboelkassem; Chris D Cantwell; Cesare Corrado; Tammo Delhaas; Wouter Huberts; Chon Lok Lei; Haibo Ni; Alexander V Panfilov; Caroline Roney; Rodrigo Weber Dos Santos
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2020-05-25       Impact factor: 4.226

4.  The use of expert elicitation in environmental health impact assessment: a seven step procedure.

Authors:  Anne B Knol; Pauline Slottje; Jeroen P van der Sluijs; Erik Lebret
Journal:  Environ Health       Date:  2010-04-26       Impact factor: 5.984

5.  Aggregating predictions from experts: a review of statistical methods, experiments, and applications.

Authors:  Thomas McAndrew; Nutcha Wattanachit; Graham C Gibson; Nicholas G Reich
Journal:  Wiley Interdiscip Rev Comput Stat       Date:  2020-06-16

6.  Data quality in predictive toxicology: reproducibility of rodent carcinogenicity experiments.

Authors:  E Gottmann; S Kramer; B Pfahringer; C Helma
Journal:  Environ Health Perspect       Date:  2001-05       Impact factor: 9.031

7.  Economic analysis of new workplace technology including productivity and injury: The case of needle-less injection in swine.

Authors:  Biaka Imeah; Erika Penz; Masud Rana; Catherine Trask
Journal:  PLoS One       Date:  2020-06-17       Impact factor: 3.240

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.