In drug development, treatments are most often selected at Phase 2 for further development when an initial trial of a new treatment produces a result that is considered positive. This selection due to a positive result means, however, that an estimator of the treatment effect, which does not take account of the selection is likely to over‐estimate the true treatment effect (ie, will be biased). This bias can be large and researchers may face a disappointingly lower estimated treatment effect in further trials. In this paper, we review a number of methods that have been proposed to correct for this bias and introduce three new methods. We present results from applying the various methods to two examples and consider extensions of the examples. We assess the methods with respect to bias of estimation of the treatment effect and compare the probabilities that a bias‐corrected treatment effect estimate will exceed a decision threshold. Following previous work, we also compare average power for the situation where a Phase 3 trial is launched given that the bias‐corrected observed Phase 2 treatment effect exceeds a launch threshold. Finally, we discuss our findings and potential application of the bias correction methods.

中文翻译：

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阶段2阳性结果的治疗方案的选择偏倚

在药物开发中，当新疗法的初步试验产生被认为是阳性的结果时，通常会在第2阶段选择要进一步开发的疗法。然而，由于结果为阳性而进行的这种选择意味着未考虑选择的治疗效果估计值可能会高估真实的治疗效果（即会产生偏差）。这种偏见可能很大，研究人员在进一步的试验中可能会面临令人失望的更低的估计治疗效果。在本文中，我们回顾了为纠正这种偏差而提出的许多方法，并介绍了三种新方法。我们介绍了将各种方法应用于两个示例的结果，并考虑了示例的扩展。我们评估有关偏倚的治疗效果估计方法，并比较偏倚校正的偏倚治疗效果估计超过决策阈值的可能性。在先前的工作之后，我们还比较了在进行了阶段3的临床试验后，观察到的2期治疗效果经过偏差校正后超过启动阈值的情况下的平均功率。最后，我们讨论了偏差校正方法的发现和潜在应用。