Group Sequential Testing of a Treatment Effect Using a Surrogate Marker
利用替代指标对处理效应进行群序贯检验AI 解读 ↓
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利用替代指标对处理效应进行群序贯检验
- 研究问题
- 未来研究只反复测量替代指标时，如何借助既往研究的主要结局信息检验处理效应，并允许因显著效果或无效性提前停止？
- 方法与思路
- 作者扩展借用既往研究信息的非参数检验，推导多个时间点替代指标检验统计量的相关性质，并计算显著性及无效性停止边界。
- 材料陈述的贡献
- 摘要称，提出适用于重复替代指标测量的群序贯程序，允许提前停止，并通过模拟及两个不同的艾滋病临床试验展示方法。
- 阅读关注点
- 应核对替代指标所需条件、既往与未来试验的信息可迁移性、统计量相关性的估计，以及停止边界如何控制总体检验错误。
- 阅读边界
- 所据为 arXiv 预印本，同行评审与期刊接收未核实；摘要未说明跨研究借用条件，不能认为任意替代指标都能检验主要结局效应。
原文摘要
The identification of surrogate markers is motivated by their potential to make decisions sooner about a treatment effect. However, few methods have been developed to actually use a surrogate marker to test for a treatment effect in a future study. Most existing methods consider combining surrogate marker and primary outcome information to test for a treatment effect, rely on fully parametric methods where strict parametric assumptions are made about the relationship between the surrogate and the outcome, and/or assume the surrogate marker is measured at only a single time point. Recent work has proposed a nonparametric test for a treatment effect using only surrogate marker information measured at a single time point by borrowing information learned from a prior study where both the surrogate and primary outcome were measured. In this paper, we utilize this nonparametric test and propose group sequential procedures that allow for early stopping of treatment effect testing in a setting where the surrogate marker is measured repeatedly over time. We derive the properties of the correlated surrogate-based nonparametric test statistics at multiple time points and compute stopping boundaries that allow for early stopping for a significant treatment effect, or for futility. We examine the performance of our testing procedure using a simulation study and illustrate the method using data from two distinct AIDS clinical trials.