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Ascertainment bias in family-based case-control studies
Kimberly D Siegmund1, Bryan Langholz
1Department of Preventive Medicine, University of Southern California, 1540 Alcazar Street, Suite 220, Los Angeles, CA 90089-9011, USA. kims@usc.edu
American Journal of Epidemiology
|April 30, 2002
Summary
Family-based case-control studies may yield biased environmental risk estimates if controls are not from the same geographic region as cases. Gene-environment interaction effects remain consistent, but caution is advised for environmental main effects.
Area of Science:
- Epidemiology
- Genetic Epidemiology
- Biostatistics
Background:
- Family-based case-control studies are common for investigating diseases with adult onset.
- These studies often match controls (siblings/cousins) on age and sex, irrespective of geographic residence.
- Geographic variation in environmental risk factors can complicate interpretation of study results.
Purpose of the Study:
- To evaluate the impact of control selection location on bias in family-based case-control studies.
- To assess the consistency of estimators for gene-environment interaction effects under geographic mismatch.
- To provide guidance on interpreting environmental main effects in such designs.
Main Methods:
- Utilized a family-matched case-control study design.
- Analyzed a population-based sample of cases from a defined geographic region.
- Compared controls selected within and outside the case ascertainment region.
Main Results:
- Estimates of environmental relative risk can be biased if controls are drawn from outside the case region.
- Estimators for gene and gene-environment interaction effects remain consistent, assuming independence of genotype and environment.
- Caution is recommended when interpreting environmental main effects from family-based studies with geographically mismatched controls.
Conclusions:
- Geographic selection of controls is critical for accurate estimation of environmental main effects in family-based case-control studies.
- Gene-environment interaction analyses may be less susceptible to geographic bias under certain assumptions.
- Researchers must carefully consider control selection strategies to avoid biased environmental risk factor assessment.