Type I error rates of multi-arm multi-stage clinical trials: strong control and impact of intermediate outcomes.
Type I error rates of multi-arm multi-stage clinical trials: strong control and impact of intermediate outcomes.
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DOI：
10.1186/s13063-016-1382-5
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发表时间：
2016-07-02
期刊：
影响因子：
2.5
通讯作者：
Choodari-Oskooei B
中科院分区：
文献类型：
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作者：
Bratton DJ;Parmar MK;Phillips PP;Choodari-Oskooei B
Royston 等人描述的多臂多级 (MAMS) 设计。 [统计医学。 2003；22(14):2239–56 和审判。 2011;12:81] 可以通过在单次试验中将多种治疗方法与对照进行比较，并在研究过程中停止招募没有表现出足够希望的手臂来加速治疗评估。为了进一步提高效率，中期评估可以基于比研究的最终结果 (D) 更早观察到的中间结果 (I)。 MAMS 试验中通常对 I 类错误率的两种测量方法感兴趣。成对 I 型错误率 (PWER) 是在研究结束时推荐无效治疗的概率，无论试验中的其他实验组如何。 Familywise I 型错误率 (FWER) 是推荐至少一种无效治疗的概率，并且通常在具有多个实验组的研究中更受关注。我们演示了当 MAMS 设计中的 I 和 D 结果不同时如何计算 PWER 和 FWER。我们探讨了每种测量方法相对于 I 的潜在治疗效果如何变化，并展示了如何在任何情况下控制 I 类错误率。最后，我们应用这些方法来估计正在进行的 MAMS 研究的最大 I 类错误率，并展示在任何情况下控制 FWER 时设计的外观。随着实验组对 I 的有效性增加，PWER 和 FWER 收敛到最大值。我们表明，通过将研究最后阶段的成对显着性水平设置为目标水平，可以在任何情况下控制这两种措施。在一个例子中，控制 FWER 被证明可以显着增加试验的规模，尽管它仍然比在单独的试验中评估每种新治疗方法更有效。所提出的方法允许在各种 MAMS 设计中控制 PWER 和 FWER，从而有可能增加 MAMS 设计在实践中的采用率。这些方法也适用于 I 和 D 结果相同的情况。
The multi-arm multi-stage (MAMS) design described by Royston et al. [Stat Med. 2003;22(14):2239–56 and Trials. 2011;12:81] can accelerate treatment evaluation by comparing multiple treatments with a control in a single trial and stopping recruitment to arms not showing sufficient promise during the course of the study. To increase efficiency further, interim assessments can be based on an intermediate outcome (I) that is observed earlier than the definitive outcome (D) of the study. Two measures of type I error rate are often of interest in a MAMS trial. Pairwise type I error rate (PWER) is the probability of recommending an ineffective treatment at the end of the study regardless of other experimental arms in the trial. Familywise type I error rate (FWER) is the probability of recommending at least one ineffective treatment and is often of greater interest in a study with more than one experimental arm. We demonstrate how to calculate the PWER and FWER when the I and D outcomes in a MAMS design differ. We explore how each measure varies with respect to the underlying treatment effect on I and show how to control the type I error rate under any scenario. We conclude by applying the methods to estimate the maximum type I error rate of an ongoing MAMS study and show how the design might have looked had it controlled the FWER under any scenario. The PWER and FWER converge to their maximum values as the effectiveness of the experimental arms on I increases. We show that both measures can be controlled under any scenario by setting the pairwise significance level in the final stage of the study to the target level. In an example, controlling the FWER is shown to increase considerably the size of the trial although it remains substantially more efficient than evaluating each new treatment in separate trials. The proposed methods allow the PWER and FWER to be controlled in various MAMS designs, potentially increasing the uptake of the MAMS design in practice. The methods are also applicable in cases where the I and D outcomes are identical.