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首页> 外文期刊>Controlled clinical trials >A flexible stochastic curtailing procedure for the log-rank test.
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A flexible stochastic curtailing procedure for the log-rank test.

机译：对数秩测试的灵活随机缩减程序。

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摘要

For safety and ethical reasons, a data monitoring committee of a clinical trial may wish to assess the futility of continuing a trial if the currently available data at an interim look show no beneficial effect due to treatment, especially when accompanied by mounting evidence of treatment emergent adverse effects. Stochastic curtailing whereby conditional power is evaluated given currently observed data is one way of evaluating futility. In clinical trials that look at "time-to-event" as the primary outcome, difference between treatment groups with respect to the primary outcome is commonly evaluated using the log-rank test. Although the unconditional power function for the log-rank test has been described previously, its conditional power has not been widely investigated. We describe a method for evaluating conditional power when the log-rank test is used to assess the difference between the survival distributions of two treatment groups with respect to some failure-time outcome. The method is useful under a wide range of assumptions regarding the underlying survival distribution, patient entry distribution, losses to follow-up, and (if applicable) noncompliance, drop-ins, lag in treatment effect, and stratification. This level of applicability is attained by generalizing a flexible Markov chain approach to unconditional power computation, described previously, to compute conditional power.
机译：出于安全和道德方面的考虑，如果临时检查中的当前可用数据未显示出由于治疗而没有任何有益效果，则临床试验的数据监视委员会可能希望评估继续进行试验的有效性，尤其是在出现越来越多的治疗证据的情况下不利影响。给定当前观察到的数据来随机评估条件功率是评估无效性的一种方法。在将“事件发生时间”作为主要结果的临床试验中，通常使用对数秩检验评估治疗组之间相对于主要结果的差异。尽管先前已描述了对数秩检验的无条件幂函数，但其​​条件幂尚未得到广泛研究。当对数秩检验用于评估两个治疗组相对于某些失败时间结局的生存分布之间的差异时，我们描述了一种评估条件能力的方法。该方法在有关基本生存分布，患者进入分布，随访损失以及（如果适用）不依从，介入，治疗效果滞后和分层等多种假设下很有用。通过将灵活的马尔可夫链方法推广到无条件功率计算（如前所述）以计算有条件功率，可以达到这种适用级别。

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