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A stochastically curtailed two-arm randomised phaseIItrial design for binary outcomes

机译:一种随机缩减的双臂用于二元成果的两臂随机外部氮气设计

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摘要

Randomised controlled trials are considered the gold standard in trial design. However, phase II oncology trials with a binary outcome are often single-arm. Although a number of reasons exist for choosing a single-arm trial, the primary reason is that single-arm designs require fewer participants than their randomised equivalents. Therefore, the development of novel methodology that makes randomised designs more efficient is of value to the trials community. This article introduces a randomised two-arm binary outcome trial design that includes stochastic curtailment (SC), allowing for the possibility of stopping a trial before the final conclusions are known with certainty. In addition to SC, the proposed design involves the use of a randomised block design, which allows investigators to control the number of interim analyses. This approach is compared with existing designs that also use early stopping, through the use of a loss function comprised of a weighted sum of design characteristics. Comparisons are also made using an example from a real trial. The comparisons show that for many possible loss functions, the proposed design is superior to existing designs. Further, the proposed design may be more practical, by allowing a flexible number of interim analyses. One existing design produces superior design realisations when the anticipated response rate is low. However, when using this design, the probability of rejecting the null hypothesis is sensitive to misspecification of the null response rate. Therefore, when considering randomised designs in phase II, we recommend the proposed approach be preferred over other sequential designs.
机译:随机对照试验被认为是试验设计的黄金标准。然而,具有二元结果的II期肿瘤试验通常是单臂的。尽管选择单臂试验有很多原因,但主要原因是单臂设计需要的参与者比随机等效的参与者少。因此,开发使随机设计更有效的新方法对试验社区有价值。本文介绍了一种随机的两臂二元结果试验设计,其中包括随机限制(SC),允许在最终结论确定之前停止试验。除SC外,拟议的设计还包括使用随机区组设计,这使得研究人员能够控制中期分析的数量。通过使用由设计特征加权和组成的损失函数,将该方法与也使用提前停止的现有设计进行比较。还使用一个真实试验的例子进行了比较。比较表明,对于许多可能的损失函数,该设计优于现有设计。此外,通过允许灵活的中期分析数量,提议的设计可能更实用。当预期响应率较低时,一种现有设计产生了卓越的设计实现。然而,当使用这种设计时,拒绝零假设的概率对零响应率的错误指定很敏感。因此,当在第二阶段考虑随机设计时,我们建议建议建议的方法优先于其他顺序设计。

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