Brittain Erica, Follmann Dean, Yang Song
Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA.
Biometrics. 2008 Mar;64(1):189-97. doi: 10.1111/j.1541-0420.2007.00874.x. Epub 2007 Aug 3.
The approach to early termination for efficacy in a trial where events occur over time but the primary question of interest relates to a long-term binary endpoint is not straightforward. This article considers comparison of treatment groups with Kaplan-Meier (KM) proportions evaluated at increasing times from randomization, at increasing calendar testing times. This strategy is employed to improve the ability to detect important treatment effects and provide critical treatments to patients in a timely manner. This dynamic Kaplan-Meier (DKM) approach is shown to be robust; that is, it produces high power and early termination time across a wide range of circumstances. In contrast, a fixed time KM comparison and the log-rank test are both shown to be more variable in performance. Practical considerations of implementing the DKM method are discussed.
在一个事件随时间发生但主要关注问题与长期二元终点相关的试验中，基于疗效进行早期终止的方法并不简单。本文考虑对治疗组进行比较，比较时采用从随机分组开始在不断增加的时间点（即不断增加的日历测试时间）评估的Kaplan-Meier（KM）比例。采用这种策略是为了提高检测重要治疗效果的能力，并及时为患者提供关键治疗。结果表明，这种动态Kaplan-Meier（DKM）方法具有稳健性；也就是说，在广泛的情况下，它都能产生高检验效能和早期终止时间。相比之下，固定时间的KM比较和对数秩检验在性能上都表现出更大的变异性。文中还讨论了实施DKM方法的实际考虑因素。
