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American Journal of Epidemiology Advance Access published online on June 7, 2007

American Journal of Epidemiology, doi:10.1093/aje/kwm097
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American Journal of Epidemiology Copyright © 2007 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

Original Contribution

Using Risk-based Sampling to Enrich Cohorts for Endpoints, Genes, and Exposures

Clarice R. Weinberg1, David L. Shore2, David M. Umbach1 and Dale P. Sandler3

1 Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC
2 Westat, Durham, NC
3 Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC

Correspondence to Dr. Clarice R. Weinberg, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709 (e-mail: weinberg{at}niehs.nih.gov).

Received for publication August 17, 2006. Accepted for publication February 21, 2007.

Targeting the first-degree relatives of people with a particular complex disease can offer a powerful approach to building a risk-based cohort for prospective studies of etiologic factors. Such a cohort provides both a sizable increase in the rate of accrual of newly incident cases, enriching for risk factors that are known or even unknown, and a high level of motivation among participants. A nationwide study of breast cancer in the United States and Puerto Rico, the Sister Study, made up of women who are each the sister of a woman with breast cancer, exemplifies this approach. In this paper, the authors provide power calculations to aid in the design of such studies and quantify their benefits for detecting both genetic variants related to risk and interactive effects of genetic and environmental factors. While the risk-based cohort can have markedly increased prevalences of rare causative alleles, most of the power advantages for this design is due to the increased rate of accrual of newly incident cases rather than the increase in any one individual allele.

cohort studies; disease susceptibility; genes; prospective studies; risk; sampling studies


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