Abstract #301203

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JSM 2002 Abstract #301203
Activity Number: 318
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section*
Abstract - #301203
Title: Two-stage Designs for Gene-disease Association Studies
Author(s): Jaya Satagopan*+ and David Verbel and E. Venkatraman and Kenneth Offit and Colin Begg
Affiliation(s): Memorial Sloan-Kettering Cancer Center and Memorial Sloan-Kettering Cancer Center and Memorial Sloan-Kettering Cancer Center and Memorial Sloan-Kettering Cancer Center and Memorial Sloan-Kettering Cancer Center
Address: 1275 York Avenue, New York, New York, 10021, USA
Keywords:
Abstract:

We describe a two-stage design to maximize the power for detecting gene-disease associations. The optimal two-stage design is derived when the principal design constraint is the total cost, represented by the total number of gene evaluations, rather than the total number of individuals. In the first stage, all genes of interest are evaluated on a subset of individuals. The most promising genes are then evaluated on additional subjects in the second stage. This will eliminate wastage of resources on genes unlikely to be associated with disease, based upon the results of the first stage. We consider the case where the genes are independent and the case where the genes are correlated. Using simulation results, we show that, as a general guideline when the genes are independent or when the correlation is small, utilizing 75% of the resources in Stage 1 to screen all the markers, and evaluating the most promising 10% of the markers with the remaining resources, provides near-optimal power for a broad range of parametric configurations. This translates to screening all the markers on approximately one-quarter of the required sample size in Stage 1.

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Revised March 2002