Adaptive increase in sample size when interim results are promising: A practical guide with examples
Adaptive increase in sample size when interim results are promising: A practical guide with examples
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DOI：
10.1002/sim.4102
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发表时间：
2011-12-10
影响因子：
2
通讯作者：
Pocock, Stuart J.
中科院分区：
文献类型：
--
作者：
Mehta, Cyrus R.;Pocock, Stuart J.
本文讨论了第三阶段验证性临床试验中自适应样本量重新估计的好处和局限性。并与传统的固定样本和成组序贯设计进行了比较。可以看出，自适应方法的真正好处是能够将样本量的资源分阶段投入试验。试验一开始就承诺了一个小的预先样本量。只有在中期分析中获得有希望的结果时，才会向试验投入更多的样本量资源。通过实际试验的例子，一个是神经学的，一个是心脏病学的，这一策略在某些情况下比固定样本或分组序贯方法更有利。引起争议并阻碍这些方法更广泛使用的一个主要因素是它们对非标准测试和p值的依赖，以保存类型1错误。然而，如果只有在中期结果有希望的时候才增加样本量，人们就可以省去这些非标准的推断方法。因此，本着使试验规模的自适应增加更具吸引力和更容易实现的精神，我们在此定义了那些有希望的情况，在这些情况下，可以在保留总体类型1错误的同时执行常规的最终推理。审查了方法、监管和操作方面的问题。版权所有(C)2010 John Wiley&Sons，Ltd.
This paper discusses the benefits and limitations of adaptive sample size re-estimation for phase 3 confirmatory clinical trials. Comparisons are made with more traditional fixed sample and group sequential designs. It is seen that the real benefit of the adaptive approach arises through the ability to invest sample size resources into the trial in stages. The trial starts with a small up-front sample size commitment. Additional sample size resources are committed to the trial only if promising results are obtained at an interim analysis. This strategy is shown through examples of actual trials, one in neurology and one in cardiology, to be more advantageous than the fixed sample or group sequential approaches in certain settings. A major factor that has generated controversy and inhibited more widespread use of these methods has been their reliance on non-standard tests and p-values for preserving the type-1 error. If, however, the sample size is only increased when interim results are promising, one can dispense with these non-standard methods of inference. Therefore, in the spirit of making adaptive increases in trial size more widely appealing and readily implementable we here define those promising circumstances in which a conventional final inference can be performed while preserving the overall type-1 error. Methodological, regulatory and operational issues are examined. Copyright (C) 2010 John Wiley & Sons, Ltd.