Williams P L
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
Stat Med. 1996;15(21-22):2341-57; discussion 2367-70. doi: 10.1002/(SICI)1097-0258(19961115)15:21<2341::AID-SIM453>3.0.CO;2-N.
Many clinical trials follow patients for several different types of survival endpoints, such as mortality, disease progression, and time until dose-limiting toxicity. Conduct of such trials often requires that the accumulating data be reviewed periodically to protect the safety of participating patients and possibly identify early treatment differences. This paper proposes a group sequential method for assessing multiple survival endpoints using repeated confidence intervals. Counting processes for each survival endpoint are used to estimate both the correlation between outcomes and between times of interim analysis. The methods are illustrated using a clinical trial comparing two treatments for PCP prevention in AIDS patients. The operating characteristics of three strategies for constructing confidence intervals are assessed and compared in a simulation study.
许多临床试验会针对几种不同类型的生存终点对患者进行随访，比如死亡率、疾病进展以及直至出现剂量限制性毒性的时间。开展这类试验通常要求定期审查累积的数据，以保护参与试验患者的安全，并有可能识别出早期的治疗差异。本文提出了一种使用重复置信区间评估多个生存终点的组序贯方法。每个生存终点的计数过程用于估计结局之间以及中期分析时间之间的相关性。通过一项比较艾滋病患者预防卡氏肺孢子虫肺炎两种治疗方法的临床试验来说明这些方法。在一项模拟研究中评估并比较了构建置信区间的三种策略的操作特征。
