期刊
PHARMACEUTICAL STATISTICS
卷 12, 期 1, 页码 43-47出版社
WILEY-BLACKWELL
DOI: 10.1002/pst.1550
关键词
personalized healthcare; companion diagnostic; randomization model; analysis of variance
Published literature and regulatory agency guidance documents provide conflicting recommendations as to whether a pre-specified subgroup analysis also requires for its validity that the study employ randomization that is stratified on subgroup membership. This is an important issue, as subgroup analyses are often required to demonstrate efficacy in the development of drugs with a companion diagnostic. Here, it is shown, for typical randomization methods, that the fraction of patients in the subgroup given experimental treatment matches, on average, the target fraction in the entire study. Also, mean covariate values are balanced, on average, between treatment arms in the subgroup, and it is argued that the variance in covariate imbalance between treatment arms in the subgroup is at worst only slightly increased versus a subgroup-stratified randomization method. Finally, in an analysis of variance setting, a least-squares treatment effect estimator within the subgroup is shown to be unbiased whether or not the randomization is stratified on subgroup membership. Thus, a requirement that a study be stratified on subgroup membership would place an artificial roadblock to innovation and the goals of personalized healthcare. Copyright (c) 2012 John Wiley & Sons, Ltd.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据