Yu Kai, Chatterjee Nilanjan, Wheeler William, Li Qizhai, Wang Sophia, Rothman Nathaniel, Wacholder Sholom
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Am J Hum Genet. 2007 Sep;81(3):540-51. doi: 10.1086/520678. Epub 2007 Aug 3.
As more population-based studies suggest associations between genetic variants and disease risk, there is a need to improve the design of follow-up studies (stage II) in independent samples to confirm evidence of association observed at the initial stage (stage I). We propose to use flexible designs developed for randomized clinical trials in the calculation of sample size for follow-up studies. We apply a bootstrap procedure to correct the effect of regression to the mean, also called "winner's curse," resulting from choosing to follow up the markers with the strongest associations. We show how the results from stage I can improve sample size calculations for stage II adaptively. Despite the adaptive use of stage I data, the proposed method maintains the nominal global type I error for final analyses on the basis of either pure replication with the stage II data only or a joint analysis using information from both stages. Simulation studies show that sample-size calculations accounting for the impact of regression to the mean with the bootstrap procedure are more appropriate than is the conventional method. We also find that, in the context of flexible design, the joint analysis is generally more powerful than the replication analysis.
随着越来越多基于人群的研究表明基因变异与疾病风险之间存在关联，有必要改进独立样本中后续研究（第二阶段）的设计，以确认在初始阶段（第一阶段）观察到的关联证据。我们建议在后续研究的样本量计算中使用为随机临床试验开发的灵活设计。我们应用一种自助程序来校正均值回归的影响，这种影响也被称为“胜者的诅咒”，它是由于选择对关联最强的标记进行后续研究而产生的。我们展示了第一阶段的结果如何自适应地改进第二阶段的样本量计算。尽管自适应地使用了第一阶段的数据，但所提出的方法在仅基于第二阶段数据的纯复制或使用两个阶段信息的联合分析的最终分析中，保持了名义上的全局I型错误。模拟研究表明，使用自助程序考虑均值回归影响的样本量计算比传统方法更合适。我们还发现，在灵活设计的背景下，联合分析通常比复制分析更具功效。
