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Expert Scientific Judgment and Cancer Risk Assessment: A Pilot Study of Pharmacokinetic Data
Author(s) -
Hawkins Neil C.,
Graham John D.
Publication year - 1988
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1988.tb01205.x
Subject(s) - expert elicitation , expert opinion , risk assessment , protocol (science) , range (aeronautics) , computer science , risk analysis (engineering) , test (biology) , psychology , medicine , data science , actuarial science , management science , engineering , statistics , business , mathematics , alternative medicine , intensive care medicine , computer security , pathology , aerospace engineering , paleontology , biology
When high‐dose tumor data are extrapolated to low doses, it is typically assumed that the dose of a carcinogen delivered to target cells is proportional to the dose administered to test animals, even at exposure levels below the experimental range. Since pharmacokinetic data are becoming available that in some cases question the validity of this assumption, risk assessors must decide whether to maintain the standard assumption. A pilot study of formaldehyde is reported that was undertaken to demonstrate how expert scientific judgment can help guide a controversial risk assessment where pharmacokinetic data are considered inconclusive. Eight experts on pharmacokinetic data were selected by a formal procedure, and each was interviewed personally using a structured interview protocol. The results suggest that expert scientific opinion is polarized in this case, a situation that risk assessors can respond to with a range of risk characterizations considered biologically plausible by the experts. Convergence of expert opinion is likely in this case if several specific research strategies are executed in a competent fashion. Elicitation of expert scientific judgment is a promising vehicle for evaluating the quality of pharmacokinetic data, expressing uncertainty in risk assessment, and fashioning a research agenda that offers possible forging of scientific consensus.