Kaiser Lee D
Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
Pharm Stat. 2013 Jan-Feb;12(1):43-7. doi: 10.1002/pst.1550. Epub 2012 Dec 21.
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.
已发表的文献和监管机构的指导文件对于预先指定的亚组分析是否也要求研究采用按亚组归属分层的随机化方法以确保其有效性给出了相互矛盾的建议。这是一个重要问题，因为在伴随诊断药物的研发中，通常需要进行亚组分析来证明疗效。在此表明，对于典型的随机化方法，接受实验性治疗的亚组中的患者比例平均而言与整个研究中的目标比例相匹配。此外，亚组中各治疗组之间的协变量均值平均而言是平衡的，并且有人认为，与按亚组分层的随机化方法相比，亚组中各治疗组之间协变量不平衡的方差充其量只是略有增加。最后，在方差分析的设定中，无论随机化是否按亚组归属分层，亚组内的最小二乘治疗效果估计量都被证明是无偏的。因此，要求研究按亚组归属分层会给创新和个性化医疗的目标设置人为障碍。
