We consider the problem of meta-analyzing outcome measures based on median survival times. Primary studies with time-to-event outcomes often report estimates of median survival times and confidence intervals based on the Kaplan-Meier estimator. However, outcome measures based on median survival are rarely meta-analyzed, as standard inverse-variance weighted methods require within-study standard errors that are typically not reported. In this article, we consider an inverse-variance weighted approach to meta-analyze median survival times that estimates the within-study standard errors from the reported confidence intervals. We show that this method consistently estimates the standard error of median survival when applied to confidence intervals constructed by the Brookmeyer-Crowley method. We conduct a series of simulation studies evaluating the performance of this approach at the study level (i.e., for estimating the standard error of median survival) and the meta-analytic level (i.e., for estimating the pooled median, difference of medians, and ratio of medians) for commonly used confidence intervals for median survival, including the Brookmeyer-Crowley method and nonparametric bootstrap. We find that this approach often performs comparably to a benchmark approach that uses the true within-study standard errors for meta-analyzing median-based outcome measures when within-study sample sizes are moderately large (e.g., above 50). However, when the effective sample sizes are small, the method can yield biased estimates of within-study standard errors. We illustrate an application of this approach in a meta-analysis evaluating survival benefits of being assigned to experimental arms versus comparator arms in randomized trials for non-small cell lung cancer therapies.

翻译：本文探讨基于生存中位数的结局指标的荟萃分析问题。针对时间-事件结局的原始研究常基于Kaplan-Meier估计量报告生存中位数的估计值及其置信区间。然而，由于标准的逆方差加权方法需要各研究内的标准误（而该数据通常未被报告），基于生存中位数的结局指标很少被用于荟萃分析。本文提出一种基于逆方差加权的生存中位数荟萃分析方法，该方法通过已报告的置信区间来估计各研究内的标准误。我们证明，当应用于通过Brookmeyer-Crowley方法构建的置信区间时，该方法能够一致地估计生存中位数的标准误。我们通过一系列模拟研究，在常用生存中位数置信区间（包括Brookmeyer-Crowley方法和非参数自助法）的框架下，从研究层面（即估计生存中位数的标准误）和荟萃分析层面（即估计合并中位数、中位数差及中位数比）评估了该方法的性能。研究发现，当研究内样本量适中（例如大于50）时，该方法在荟萃分析基于中位数的结局指标时，其表现与使用真实研究内标准误的基准方法相当。然而，当有效样本量较小时，该方法可能产生有偏的研究内标准误估计。我们通过一项评估非小细胞肺癌疗法随机试验中实验组与对照组生存获益的荟萃分析，展示了该方法的应用实例。