Friede Tim, Kieser Meinhard
Warwick Medical School, The University of Warwick, Coventry, UK.
Pharm Stat. 2011 Jan-Feb;10(1):8-13. doi: 10.1002/pst.398.
Baseline adjusted analyses are commonly encountered in practice, and regulatory guidelines endorse this practice. Sample size calculations for this kind of analyses require knowledge of the magnitude of nuisance parameters that are usually not given when the results of clinical trials are reported in the literature. It is therefore quite natural to start with a preliminary calculated sample size based on the sparse information available in the planning phase and to re-estimate the value of the nuisance parameters (and with it the sample size) when a portion of the planned number of patients have completed the study. We investigate the characteristics of this internal pilot study design when an analysis of covariance with normally distributed outcome and one random covariate is applied. For this purpose we first assess the accuracy of four approximate sample size formulae within the fixed sample size design. Then the performance of the recalculation procedure with respect to its actual Type I error rate and power characteristics is examined. The results of simulation studies show that this approach has favorable properties with respect to the Type I error rate and power. Together with its simplicity, these features should make it attractive for practical application.
在实际应用中,基线调整分析很常见,并且监管指南也认可这种做法。此类分析的样本量计算需要了解干扰参数的大小,而在文献中报告临床试验结果时通常不会给出这些参数。因此,很自然的做法是在规划阶段基于可用的稀疏信息初步计算样本量,并在一部分计划患者完成研究时重新估计干扰参数的值(以及样本量)。当应用具有正态分布结果和一个随机协变量的协方差分析时,我们研究这种内部预试验设计的特征。为此,我们首先在固定样本量设计中评估四个近似样本量公式的准确性。然后检查重新计算程序在实际I型错误率和检验效能特征方面的表现。模拟研究结果表明,这种方法在I型错误率和检验效能方面具有良好的特性。连同其简单性,这些特征应该使其在实际应用中具有吸引力。