The Emmes Company, Rockville, MD, 20850, USA.
Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI, 53226, USA.
Lifetime Data Anal. 2020 Jul;26(3):603-623. doi: 10.1007/s10985-019-09491-z. Epub 2019 Nov 15.
Medical research frequently involves comparing an event time of interest between treatment groups. Rather than comparing the entire survival or cumulative incidence curves, it is sometimes preferable to evaluate these probabilities at a fixed point in time. Performing a covariate adjusted analysis can improve efficiency, even in randomized clinical trials, but no currently available group sequential test for fixed point analysis provides this adjustment. This paper introduces covariate adjusted group sequential pointwise comparisons of survival and cumulative incidence probabilities. Their test statistics have an asymptotic distribution with independent increments, permitting use of common stopping boundary specification methods. These tests are demonstrated through a redesign of BMT CTN 0402, a clinical trial that evaluated a prophylactic treatment for adverse outcomes following blood and marrow transplantation. A simulation study demonstrates that these tests maintain the type I error rate and power at nominal levels under a variety of settings involving influential covariates.
医学研究经常涉及比较治疗组之间感兴趣的事件时间。与其比较整个生存或累积发生率曲线,有时更可取的是在固定时间点评估这些概率。进行协变量调整分析可以提高效率,即使在随机临床试验中也是如此,但目前尚无用于固定点分析的可用组序贯测试提供这种调整。本文介绍了生存和累积发生率概率的协变量调整组序贯逐点比较。它们的检验统计量具有具有独立增量的渐近分布,允许使用常见的停止边界指定方法。通过重新设计 BMT CTN 0402 来演示这些检验,这是一项评估血液和骨髓移植后不良结局的预防性治疗的临床试验。一项模拟研究表明,在涉及有影响力的协变量的各种情况下,这些检验在名义水平下保持了 I 型错误率和功效。