A Cost-Benefit Analysis of Genetic Screening for Susceptibility to Occupational Toxicants

Genetic screening can identify individuals with increased susceptibility to certain workplace toxicants. One conceivable benefit is a reduction in occupational disease costs. We examine this rationale by considering the associations among genetic traits, exposure, disease risk, and disease incidence...

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Bibliographic Details
Published in:Journal of occupational and environmental medicine 1999-07, Vol.41 (7), p.535-544
Main Authors: Nicas, Mark, Lomax, Geoffrey P.
Format: Article
Language:English
Subjects:
Benefit cost analysis
Benzene - adverse effects
Berylliosis - genetics
Biological and medical sciences
Chemical and industrial products toxicology. Toxic occupational diseases
Cost-Benefit Analysis
General aspects
Genetic Predisposition to Disease
Genetic Testing - economics
Genetics
Humans
Medical sciences
Medical screening
Monte Carlo Method
Neoplasms - chemically induced
Neoplasms - genetics
Occupational diseases
Occupational Diseases - genetics
Occupational Exposure
ORIGINAL ARTICLES
Toxicology
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Summary:Genetic screening can identify individuals with increased susceptibility to certain workplace toxicants. One conceivable benefit is a reduction in occupational disease costs. We examine this rationale by considering the associations among genetic traits, exposure, disease risk, and disease incidence. Given appropriate information, we describe methods for computing the expectation and variance of the future number of disease cases and of the differential screening cost per worker hired (a cost-benefit measure). We present two hypothetical scenarios: (1) benzene-induced cancer with few expected cases, and (2) chronic beryllium disease with many expected cases. We show that variability in disease incidence and cost outcomes must be considered because in specific instances, screening can be cost-beneficial on average but yield an unfavorable outcome with high probability. This circumstance pertains to scenarios involving small differences between the expected number of cases in screened versus unscreened cohorts.
ISSN:1076-2752
1536-5948
DOI:10.1097/00043764-199907000-00002