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针对计数数据临床试验的盲法和非盲法内部预试验设计。

Blinded and unblinded internal pilot study designs for clinical trials with count data.

作者信息

Schneider Simon, Schmidli Heinz, Friede Tim

机构信息

Department of Medical Statistics, University Medical Center Göttingen, Germany.

出版信息

Biom J. 2013 Jul;55(4):617-33. doi: 10.1002/bimj.201200189. Epub 2013 May 24.

Abstract

Internal pilot studies are a popular design feature to address uncertainties in the sample size calculations caused by vague information on nuisance parameters. Despite their popularity, only very recently blinded sample size reestimation procedures for trials with count data were proposed and their properties systematically investigated. Although blinded procedures are favored by regulatory authorities, practical application is somewhat limited by fears that blinded procedures are prone to bias if the treatment effect was misspecified in the planning. Here, we compare unblinded and blinded procedures with respect to bias, error rates, and sample size distribution. We find that both procedures maintain the desired power and that the unblinded procedure is slightly liberal whereas the actual significance level of the blinded procedure is close to the nominal level. Furthermore, we show that in situations where uncertainty about the assumed treatment effect exists, the blinded estimator of the control event rate is biased in contrast to the unblinded estimator, which results in differences in mean sample sizes in favor of the unblinded procedure. However, these differences are rather small compared to the deviations of the mean sample sizes from the sample size required to detect the true, but unknown effect. We demonstrate that the variation of the sample size resulting from the blinded procedure is in many practically relevant situations considerably smaller than the one of the unblinded procedures. The methods are extended to overdispersed counts using a quasi-likelihood approach and are illustrated by trials in relapsing multiple sclerosis.

摘要

内部预试验是一种常见的设计特征,用于解决因干扰参数信息模糊而导致样本量计算存在不确定性的问题。尽管其很受欢迎,但直到最近才提出了针对计数数据试验的盲法样本量重新估计程序,并对其性质进行了系统研究。尽管盲法程序受到监管机构的青睐,但实际应用在一定程度上受到限制,因为人们担心如果在规划中错误指定了治疗效果,盲法程序容易产生偏差。在此,我们比较了非盲法和盲法程序在偏差、错误率和样本量分布方面的情况。我们发现这两种程序都能保持所需的检验效能,非盲法程序略显宽松,而盲法程序的实际显著性水平接近名义水平。此外,我们表明,在存在假设治疗效果不确定性的情况下,与非盲法估计量相比,对照事件率的盲法估计量存在偏差,这导致平均样本量存在差异,有利于非盲法程序。然而,与平均样本量偏离检测真实但未知效果所需样本量的偏差相比,这些差异相当小。我们证明,在许多实际相关情况下,盲法程序导致的样本量变化比非盲法程序小得多。使用拟似然方法将这些方法扩展到过度分散的计数情况,并通过复发型多发性硬化症试验进行了说明。

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