Blinded sample size re-estimation accounting for uncertainty in mid-trial estimation
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考虑试验中期估计不确定性的盲态样本量重估
- 研究问题
- 两正态总体比较的试验中，如何在不揭示治疗分配的情况下重估样本量，并降低中期方差估计误差造成的功效不足风险？
- 方法与思路
- 作者分析盲态总体方差估计的期望性质，提出使用方差置信上限重估样本量，并选择置信水平以使重估设计达到目标功效。
- 材料陈述的贡献
- 摘要称，既有总体方差方法可作最坏情形评估，但小样本盲态审查仍可能功效不足；新方法在数值研究中表现优于既有方法。
- 阅读关注点
- 应核对总体方差期望上界与单次估计值的区别、置信水平选择方法，以及样本量调整对最终检验功效和错误率的影响。
- 阅读边界
- 这是预印本，同行评审或期刊接收未核实。摘要未给出置信限构造及功效保证的具体条件，不能判断其对非正态设计的适用性。
原文摘要
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.