Department of Statistics, TU Dortmund University, Dortmund, Germany.
Technion - Israel Institute of Technology, Haifa, Israel.
Contemp Clin Trials. 2023 May;128:107165. doi: 10.1016/j.cct.2023.107165. Epub 2023 Mar 25.
Studies to compare the survival of two or more groups using time-to-event data are of high importance in medical research. The gold standard is the log-rank test, which is optimal under proportional hazards. As the latter is no simple regularity assumption, we are interested in evaluating the power of various statistical tests under different settings including proportional and non-proportional hazards with a special emphasis on crossing hazards. This challenge has been going on for many years now and multiple methods have already been investigated in extensive simulation studies. However, in recent years new omnibus tests and methods based on the restricted mean survival time appeared that have been strongly recommended in biometric literature.
Thus, to give updated recommendations, we perform a vast simulation study to compare tests that showed high power in previous studies with these more recent approaches. We thereby analyze various simulation settings with varying survival and censoring distributions, unequal censoring between groups, small sample sizes and unbalanced group sizes.
Overall, omnibus tests are more robust in terms of power against deviations from the proportional hazards assumption.
We recommend considering the more robust omnibus approaches for group comparison in case of uncertainty about the underlying survival time distributions.
使用时间事件数据比较两个或多个组的生存情况的研究在医学研究中非常重要。金标准是对数秩检验，在比例风险下是最优的。由于后者不是简单的规律假设，我们有兴趣在不同的设置下评估各种统计检验的功效，包括比例和非比例风险，并特别强调交叉风险。这一挑战已经持续了多年，现在已经在广泛的模拟研究中研究了多种方法。然而，近年来，新的基于受限平均生存时间的整体检验和方法出现在生物统计学文献中，被强烈推荐。
因此，为了提供更新的建议，我们进行了一项广泛的模拟研究，比较了在以前的研究中显示出高功效的检验方法与这些更新的方法。我们分析了具有不同生存和删失分布、组间不等删失、小样本量和不平衡组大小的各种模拟设置。
总体而言，整体检验在对抗比例风险假设偏差的功效方面更稳健。
我们建议在对潜在生存时间分布不确定的情况下，考虑更稳健的整体方法进行组间比较。
