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Sample size determination for paired right-censored data based on the difference of Kaplan-Meier estimates

机译:基于Kaplan-Meier估计值差异的成对右删失数据的样本量确定

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摘要

Sample size determination is essential to planning clinical trials. established a sample size calculation formula for paired right-censored data based on the logrank test, which has been well-studied for comparing independent survival outcomes. An alternative to rank-based methods for independent right-censored data, advocated by , tests for differences between integrated weighted Kaplan-Meier estimates and is more sensitive to the magnitude of difference in survival times between groups. In this paper, we employ the concept of the Pepe-Fleming method to determine an adequate sample size by calculating differences between Kaplan-Meier estimators considering pair-wise correlation. We specify a positive stable frailty model for the joint distribution of paired survival times. We evaluate the performance of the proposed method by simulation studies and investigate the impacts of the accrual times, follow-up times, loss to follow-up rate, and sensitivity of power under misspecification of the model. The results show that ignoring the pair-wise correlation results in overestimating the required sample size. Furthermore, the proposed method is applied to two real-world studies, and the R code for sample size calculation is made available to users.
机译:样本量的确定对于规划临床试验至关重要。建立了基于对数秩检验的成对右删失数据的样本量计算公式,该公式已被很好地研究用于比较独立生存结果。提倡一种基于等级的方法来对独立的右删失数据进行检验,以测试综合加权Kaplan-Meier估计之间的差异,并且对组之间生存时间差异的大小更为敏感。在本文中,我们采用Pepe-Fleming方法的概念,通过计算考虑成对相关性的Kaplan-Meier估计量之间的差异来确定适当的样本量。我们为配对生存时间的联合分布指定了一个正稳定的脆弱模型。我们通过仿真研究评估了所提出方法的性能,并研究了应计时间,随访时间,对随访率的损失以及模型错误指定下的功率敏感性的影响。结果表明,忽略成对相关会导致高估所需的样本量。此外,所提出的方法被应用于两个现实世界的研究,并且用于样本大小计算的R代码可供用户使用。

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