The University of Texas Health Science Center at Houston, TX, USA.
Merck & Co., Inc., Kenilworth, NJ, USA.
Contemp Clin Trials. 2021 Feb;101:106249. doi: 10.1016/j.cct.2020.106249. Epub 2020 Dec 15.
Biomarker subpopulations have become increasingly important for drug development in targeted therapies. The use of biomarkers has the potential to facilitate more effective outcomes by guiding patient selection appropriately, thus enhancing the benefit-risk profile and improving trial power. Studying a broad population simultaneously with a more targeted one allows the trial to determine the population for which a treatment is effective and allows a goal of making approved regulatory labeling as inclusive as is appropriate. We examine new methods accounting for the complete correlation structure in group sequential designs with hypotheses in nested subgroups. The designs provide full control of family-wise Type I error rate. This extension of previous methods accounting for either group sequential design or correlation between subgroups improves efficiency (power or sample size) over a typical Bonferroni approach for testing nested populations.
生物标志物亚群在靶向治疗的药物开发中变得越来越重要。通过适当指导患者选择，使用生物标志物有可能实现更有效的结果，从而改善获益风险比并提高试验效能。同时对广泛的人群和更具针对性的人群进行研究，可以使试验确定治疗有效的人群，并使批准的监管标签尽可能具有包容性。我们研究了新的方法，这些方法考虑了具有嵌套子组假设的分组序贯设计中的完整相关结构。这些设计可以完全控制总体错误率。与用于检验嵌套人群的典型 Bonferroni 方法相比，这种对分组序贯设计或子组之间相关性的扩展之前的方法可以提高效率（功效或样本量）。
