Statistical Monitoring of Clinical Trials With Multiple Co-Primary Endpoints Using Multivariate B-value
Statistical Monitoring of Clinical Trials With Multiple Co-Primary Endpoints Using Multivariate B-value
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DOI：
10.1080/19466315.2014.923324
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发表时间：
2014-01-01
影响因子：
1.8
通讯作者：
Menon, Sandeep
中科院分区：
文献类型：
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作者：
Cheng, Yansong;Ray, Surajit;Menon, Sandeep
本文开发了具有多个共同主要终点的临床试验的统计监测方法，其中成功定义为同时满足两个终点。在实践中，组序贯设计（GSD）方法用于提前停止试验以获得有希望的疗效，条件把握度（CP）用于无效停止规则。在这篇文章中，我们表明，停止边界的GSD与多个共同的主要终点应该是相同的研究与单一终点。Lan和Wittes提出了B值工具来计算单终点试验的CP，我们将该工具扩展到计算具有多个协同主要终点的研究的CP。我们考虑了两组研究的情况下，共同主要正常，并提供了一个例子，模拟试验的实施。提出了一种基于CP的固定权重样本容量重估计方法。
This article develops methods of statistical monitoring of clinical trials with multiple co-primary endpoints, where success is defined as meeting both endpoints simultaneously. In practice, a group sequential design (GSD) method is used to stop trials early for promising efficacy, and conditional power (CP) is used for futility stopping rules. In this article, we show that stopping boundaries for the GSD with multiple co-primary endpoints should be the same as those for studies with single endpoints. Lan and Wittes proposed the B-value tool to calculate the CP of single endpoint trials and we extend this tool to calculate the CP for studies with multiple co-primary endpoints. We consider the cases of two-arm studies with co-primary normal and provide an example of implementation with simulated trial. A fixed-weight sample size reestimation approach based on CP is introduced.