Background: The objectives of a family-based disease registry range from characterizing measured genetic factors and gene-environment interaction effects to detecting novel susceptibility genes. Gathering complete information on exposure and disease status in all family members for a sample of affected subjects (probands) to address these diverse objectives would be prohibitively expensive.
Methods: Multistage sampling can be used to design an efficient family-based disease registry. At each stage, the probands are classified on the basis of previously collected data, and a subsample is selected for more detailed observation. The design can be optimized to minimize the variance of any of the model parameter estimates, subject to a constraint on the total sample size.
Results: We describe the basic statistical theory and its application to a four-stage sampling scheme proposed for the Cooperative Family Registry for Epidemiologic Studies of Colorectal Cancer at the University of Southern California.