A Distributional Approach to Characterizing Low‐Dose Cancer Risk

Evans, John S.; Graham, John D.; Gray, George M.; Sielken, Robert L.

doi:10.1111/j.1539-6924.1994.tb00025.x

Cited by 58 publications

(25 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Evans et al (53,54) developed and demonstrated such methods in the context of health experts' judgments about low-dose cancer risk from exposure to formaldehyde in environmental and occupational settings. The method used the construction of probability trees that allowed experts to make judgments about the relative likelihood that alternative models of possible pharmacokinetic and pharmacodynamic processes correctly describe the biological process that are involved.…”

Section: Uncertainty About Model Functional Formmentioning

confidence: 99%

“…The process they developed is very labor intensive and uses experts as evaluators of alternative causal models and their implications rather than as proponents of one or another model. It would be highly desirable to apply procedures such as those developed and demonstrated by Evans et al (53,54) and Budnitz et al (55,56) in assessment processes such as that used by the Intergovernmental Panel on Climate Change (IPCC). However, resource constraints and the limited familiarity that most experts have with decision science, probably makes such an effort infeasible.…”

Section: Uncertainty About Model Functional Formmentioning

confidence: 99%

See 1 more Smart Citation

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

Morgan

2014

Proc. Natl. Acad. Sci. U.S.A.

523

467

View full text Add to dashboard Cite

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making.

show abstract

Section: Uncertainty About Model Functional Formmentioning

confidence: 99%

Section: Uncertainty About Model Functional Formmentioning

confidence: 99%

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

Morgan

2014

Proc. Natl. Acad. Sci. U.S.A.

523

467

View full text Add to dashboard Cite

show abstract

“…Most analysts in the field of environmental risk analysis would agree, however, that uncertainty in doseresponse relationships often overwhelms any uncertainty from other sources including exposure ( Taylor et al, 1993, Thompson andEvans, 1997 ). Other studies have suggested that uncertainty in dose response may span orders of magnitude ( Evans et al, 1994 ).…”

Section: Introductionmentioning

confidence: 99%

Use of expert judgment in exposure assessment: Part 2. Calibration of expert judgments about personal exposures to benzene

Walker

Catalano

Hammitt

et al. 2003

J Expo Sci Environ Epidemiol

View full text Add to dashboard Cite

The recent movement of regulatory agencies toward probabilistic analyses of human health and environmental risks has focused greater attention on the quality of the estimates of variability and uncertainty that underlie them. Of particular concern is how uncertainty -a measure of what is not known -is characterized, as uncertainty can play an influential role in analyses of the need for regulatory controls or in estimates of the economic value of additional research. This paper reports the second phase of a study, conducted as an element of the National Human Exposure Assessment Survey ( NHEXAS ), to obtain and calibrate exposure assessment experts' judgments about uncertainty in residential ambient, residential indoor, and personal air benzene concentrations experienced by the nonsmoking, nonoccupationally exposed population in U.S. EPA's Region V. Subjective judgments ( i.e., the median, interquartile range, and 90% confidence interval ) about the means and 90th percentiles of each of the benzene distributions were elicited from the seven experts participating in the study. The calibration or quality of the experts' judgments was assessed by comparing them to the actual measurements from the NHEXAS Region V study using graphical techniques, a quadratic scoring rule, and surprise and interquartile indices. The results from both quantitative scoring methods suggested that, considered collectively, the experts' judgments were relatively well calibrated although on balance, underconfident. The calibration of individual expert judgments appeared variable, highlighting potential pitfalls in reliance on individual experts. In a surprising finding, the experts' judgments about the 90th percentiles of the benzene distributions were better calibrated than their predictions about the means; the experts tended to be overconfident in their ability to predict the means. This paper is also one of the first calibration studies to demonstrate the importance of taking into account intraexpert correlation on the statistical significance of the findings. When the judgments were assumed to be independent, analysis of the surprise and interquartile indices found evidence of poor calibration ( P < 0.05 ). However, when the intraexpert correlation in the study was taken into account, these findings were no longer statistically significant. The analysis further found that the experts' judgments scored better than estimates of Region V benzene concentrations simply drawn from earlier studies of ambient, indoor and personal benzene levels in other U.S. cities. These results suggest the value of careful elicitation of expert judgments in characterizing exposures in probabilistic form. Additional calibration studies need to be undertaken to corroborate and extend these findings.

show abstract

“…These are not simple questions and the choice made can be significant. As a simple demonstration, using analysis from Evans et al (1994) and assuming 10,000.0000 people exposed to a background level of 3.45 ppb of formaldehyde in air, 20 m3 air breathed per day and 70 years of exposure the choice of dose-response model leads to prediction of excess cancers of 0 for a probit model, <1 for a multistage model, and about 21,000 for a one-hit model. In the absence of compelling information about the scientific appropriateness of one model or another, the choice becomes a matter of science policy.…”

Section: Science Policymentioning

confidence: 99%

Hormesis in Regulatory Risk Assessment - Science and Science Policy

Gray¹

2010

Dose-Response

View full text Add to dashboard Cite

ᮀ This brief commentary will argue that whether hormesis is considered in regulatory risk assessment is a matter less of science than of science policy. I will first discuss the distinction between science and science policy and their roles in regulatory risk assessment. Then I will focus on factors that influence science policy, especially as it relates to the conduct of risk assessments to inform regulatory decisions, with a focus on the U.S. Environmental Protection Agency (EPA). The key questions will then be how does hormesis interact with current concepts of science and science policy for risk assessment? Finally, I look ahead to factors that may increase, or decrease, the likelihood of hormesis being incorporated into regulatory risk assessment.

show abstract

A Distributional Approach to Characterizing Low‐Dose Cancer Risk

Cited by 58 publications

References 17 publications

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

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

Use of expert judgment in exposure assessment: Part 2. Calibration of expert judgments about personal exposures to benzene

Hormesis in Regulatory Risk Assessment - Science and Science Policy

Contact Info

Product

Resources

About