Informative noncompliance in endpoint trials.

Steven M Snapinn, Qi Jiang, Boris Iglewicz
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引用次数: 18

Abstract

Noncompliance with study medications is an important issue in the design of endpoint clinical trials. Including noncompliant patient data in an intention-to-treat analysis could seriously decrease study power. Standard methods for calculating sample size account for noncompliance, but all assume that noncompliance is noninformative, i.e., that the risk of discontinuation is independent of the risk of experiencing a study endpoint. Using data from several published clinical trials (OPTIMAAL, LIFE, RENAAL, SOLVD-Prevention and SOLVD-Treatment), we demonstrate that this assumption is often untrue, and we discuss the effect of informative noncompliance on power and sample size.

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终点试验中的信息不依从性。
研究药物的不依从性是终点临床试验设计中的一个重要问题。在意向治疗分析中纳入不合规的患者数据可能会严重降低研究的有效性。计算样本量的标准方法考虑了不依从性,但都假设不依从性是非信息性的,即停药的风险独立于经历研究终点的风险。使用几个已发表的临床试验(OPTIMAAL, LIFE, RENAAL, SOLVD-Prevention和SOLVD-Treatment)的数据,我们证明了这种假设通常是不正确的,我们讨论了信息不依从性对功率和样本量的影响。
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