For randomized controlled trials to be conclusive, it is important to set the target sample size accurately at the design stage. Comparing two normal populations, the sample size calculation requires specification of the variance other than the treatment effect and misspecification can lead to underpowered studies. Blinded sample size re-estimation is an approach to minimize the risk of inconclusive studies. Existing methods proposed to use the total (one-sample) variance that is estimable from blinded data without knowledge of the treatment allocation. We demonstrate that, since the expectation of this estimator is greater than or equal to the true variance, the one-sample variance approach can be regarded as providing an upper bound of the variance in blind reviews. This worst-case evaluation can likely reduce a risk of underpowered studies. However, blinded reviews of small sample size may still lead to underpowered studies. We propose a refined method accounting for estimation error in blind reviews using an upper confidence limit of the variance. A similar idea had been proposed in the setting of external pilot studies. Furthermore, we developed a method to select an appropriate confidence level so that the re-estimated sample size attains the target power. Numerical studies showed that our method works well and outperforms existing methods. The proposed procedure is motivated and illustrated by recent randomized clinical trials.

翻译：为确保随机对照试验具有结论性，在设计阶段准确设定目标样本量至关重要。在比较两个正态总体时，样本量计算除了需要确定处理效应外，还需明确方差参数。若方差设定存在偏差，可能导致研究检验效能不足。盲法样本量重估计是一种旨在降低研究无结论风险的方法。现有方法建议使用可从盲态数据（无需知晓治疗分配信息）估计的总（单样本）方差。我们证明，由于该估计量的期望值大于或等于真实方差，单样本方差方法可视为在盲态评估中提供了方差的上界估计。这种最坏情况评估可能降低检验效能不足的风险。然而，基于小样本的盲态评估仍可能导致检验效能不足。我们提出一种改进方法，通过使用方差的上置信限来考虑盲态评估中的估计误差。类似思路曾在外部预试验场景中被提出。此外，我们开发了一种选择适当置信水平的方法，使得重估计后的样本量能达到目标检验效能。数值研究表明，本方法表现良好且优于现有方法。所提流程的构建动机与示例均源自近期随机临床试验。