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American Journal of Epidemiology Vol. 150, No. 8: 878-885
Copyright © 1999 by The Johns Hopkins University School of Hygiene and Public Health


other

Potential Misinterpretation of the Case-Only Study to Assess Gene-Environment Interaction

Silke Schmidt1,3 and Daniel J. Schaid2

1Division of Epidemiology, German Cancer Research Center 69120 Heidelberg, Germany
2Section of Biostatistics, Department of Health Sciences Research and Department of Medical Genetics Mayo Clinic/Mayo Foundation, Rochester, MN

3 Present address: Center for Human Genetics, Duke University Medical Center, Durham, NC.

Novel epidemiologic study designs are often required to assess gene-environment interaction. A design using only cases, without controls, is one of several approaches that have been proposed as more efficient alternatives to the typical random sampling of cases and controls. However, it has not been pointed out that a case-only analysis estimates a different interaction parameter than does a traditional case-control analysis: The latter typically estimates departure from multiplicative population odds or rate ratios, depending on the method of control selection, while the former estimates departure from multiplicative risk ratios if genotype and environmental exposure are not associated in the population. These parameters are approximately equal if the disease risk is small at all levels of the study variables. The authors quantify the impact of allowing for higher disease risk among gene carriers, a relevant situation when the gene under study is highly penetrant. Their findings show that the cross-product ratio computed from case-only data may be substantially smaller than the odds ratio computed from case-control data and may therefore underestimate either the population odds or the rate ratio. Thus, to avoid misinterpretation of interaction parameters estimated from case-only data, the definition of multiplicative interaction should be made explicit. Am J Epidemiol 1999;150:878-85.

case-control studies; epidemiologic methods; gene-environment interaction; interaction; odds ratio


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