INSERM, SPHERE, U1246, Tours University, Nantes University, Tours, France.
INSERM, SPHERE, U1246, Nantes University, Tours University, Nantes, France.
Stat Methods Med Res. 2023 Oct;32(10):2016-2032. doi: 10.1177/09622802231192960. Epub 2023 Aug 9.
For time-to-event outcomes, the difference in restricted mean survival time is a measure of the intervention effect, an alternative to the hazard ratio, corresponding to the expected survival duration gain due to the intervention up to a predefined time *. We extended two existing approaches of restricted mean survival time estimation for independent data to clustered data in the framework of cluster randomized trials: one based on the direct integration of Kaplan-Meier curves and the other based on pseudo-values regression. Then, we conducted a simulation study to assess and compare the statistical performance of the proposed methods, varying the number and size of clusters, the degree of clustering, and the magnitude of the intervention effect under proportional and non-proportional hazards assumption. We found that the extended methods well estimated the variance and controlled the type I error if there was a sufficient number of clusters (≥ 50) under both proportional and non-proportional hazards assumption. For cluster randomized trials with a limited number of clusters (< 50), a permutation test for pseudo-values regression was implemented and corrected the type I error. We also provided a procedure to estimate permutation-based confidence intervals which produced adequate coverage. All the extended methods performed similarly, but the pseudo-values regression offered the possibility to adjust for covariates. Finally, we illustrated each considered method with a cluster randomized trial evaluating the effectiveness of an asthma-control education program.
对于生存时间结局，受限平均生存时间的差异是干预效果的一种衡量指标，可替代风险比，对应于由于干预导致的预期生存时间延长，最长至预定时间*。我们将两种现有的独立数据受限平均生存时间估计方法扩展到群组随机试验框架中的群组数据中：一种基于直接整合 Kaplan-Meier 曲线，另一种基于伪值回归。然后，我们进行了一项模拟研究，以评估和比较所提出方法的统计性能，方法是在比例和非比例风险假设下，改变群组的数量和大小、群组的聚集程度以及干预效果的大小。我们发现，如果在两种比例和非比例风险假设下有足够数量的群组（≥50），则扩展方法可以很好地估计方差并控制 I 型错误。对于群组数量有限（<50）的群组随机试验，我们实施了伪值回归的置换检验，并校正了 I 型错误。我们还提供了一种程序来估计基于置换的置信区间，该置信区间具有适当的覆盖范围。所有扩展方法的性能相似，但伪值回归提供了调整协变量的可能性。最后，我们通过一项评估哮喘控制教育计划效果的群组随机试验说明了每种考虑的方法。
