Sample Size Analysis for Pharmacogenetic Studies

被引:2
|
作者
Tseng, Chi-hong [1 ]
Shao, Yongzhao [2 ]
机构
[1] Univ Calif Los Angeles, Sch Med, Dept Med, Los Angeles, CA 90024 USA
[2] NYU, Sch Med, Div Biostat, New York, NY 10016 USA
来源
STATISTICS IN BIOPHARMACEUTICAL RESEARCH | 2010年 / 2卷 / 03期
关键词
Efficient score test; False discovery rate; Gene-drug interaction; Linkage disequilibrium; Multiple comparison; Pharmacogenomics; SINGLE-NUCLEOTIDE POLYMORPHISMS; LINKAGE DISEQUILIBRIUM; STATISTICAL SIGNIFICANCE; GENOMEWIDE; LIKELIHOOD; TRIALS; GENES;
D O I
10.1198/sbr.2009.08076
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Pharmacogenetic studies identify the genetic factors that influence the intersubject variation in drug response. This article proposes a general framework to determine sample size in pharmacogenetic studies. Simple closed form solutions for the sample size are derived for continuous and binary outcomes. To extend the application to pharmacogenomic studies, where a large number of gene-treatment interactions are evaluated simultaneously, we advocate the use of false discovery rate (FDR) in controlling false positive proportion. We adapt the method proposed by Shao and Tseng (2007) to facilitate adjustment for correlation among multiple tests for better control of false positives and power. A real example is given and simulation studies are carried out to demonstrate the performance of the proposed method.
引用
收藏
页码:319 / 328
页数:10
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