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Sample size reassessment in non-inferiority trials. Internal pilot study designs with ANCOVA.

机译:非劣效性试验中的样本量重新评估。使用ANCOVA进行内部试验研究设计。

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OBJECTIVES: Analysis of covariance (ANCOVA) is widely applied in practice and its use is recommended by regulatory guidelines. However, the required sample size for ANCOVA depends on parameters that are usually uncertain in the planning phase of a study. Sample size recalculation within the internal pilot study design allows to cope with this problem. From a regulatory viewpoint it is preferable that the treatment group allocation remains masked and that the type I error is controlled at the specified significance level. The characteristics of blinded sample size reassessment for ANCOVA in non-inferiority studies have not been investigated yet. We propose an appropriate method and evaluate its performance. METHODS: In a simulation study, the characteristics of the proposed method with respect to type I error rate, power and sample size are investigated. It is illustrated by a clinical trial example how strict control of the significance level can be achieved. RESULTS: A slight excess of the type I error rate beyond the nominal significance level was observed. The extent of exceedance increases with increasing non-inferiority margin and increasing correlation between outcome and covariate. The procedure assures the desired power over a wide range of scenarios even if nuisance parameters affecting the sample size are initially mis-specified. CONCLUSIONS: The proposed blinded sample size recalculation procedure protects from insufficient sample sizes due to incorrect assumptions about nuisance parameters in the planning phase. The original procedure may lead to an elevated type I error rate, but methods are available to control the nominal significance level.
机译:目的:协方差分析(ANCOVA)在实践中得到广泛应用,监管指南建议使用此方法。但是,ANCOVA所需的样本量取决于在研究计划阶段通常不确定的参数。内部试点研究设计中的样本量重新计算可以解决此问题。从管理的观点来看,优选的是,治疗组的分配保持掩盖,并且将I型错误控制在指定的显着性水平。在非劣效性研究中,ANCOVA的盲样本量重新评估的特征尚未得到研究。我们提出一种合适的方法并评估其性能。方法:在仿真研究中,研究了该方法在I型错误率,功效和样本量方面的特点。通过临床试验示例说明了如何严格控制显着性水平。结果:观察到I型错误率略有超出名义显着水平。超出的程度随非劣性余量的增加以及结果与协变量之间的相关性增加而增加。即使最初错误指定了影响样本大小的令人讨厌的参数,该过程仍可确保在各种情况下均具有所需的功率。结论:由于在计划阶段对扰动参数的错误假设,建议的盲目样本量重新计算程序可防止样本量不足。原始过程可能会导致I型错误率升高,但是可以使用一些方法来控制名义上的显着性水平。

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