Tudur Smith Catrin, Williamson Paula Ruth
Centre for Medical Statistics and Health Evaluation, University of Liverpool, Liverpool, L69 3GS, UK.
Clin Trials. 2007;4(6):621-30. doi: 10.1177/1740774507085276.
Alternative methods for individual patient data (IPD) meta-analysis of time-to-event outcomes have been established and utilized in practice. The most common approach is a stratified log-rank analysis. The IPD approach is considered to be the gold standard approach for meta-analysis and is becoming increasingly more popular but the performance of different methods has not been studied previously.
To compare commonly used methods for fixed effects meta-analysis of individual patient time-to-event data.
The stratified log-rank analysis, an inverse variance weighted average of Cox model estimates, and the stratified Cox regression model are compared. First, a theoretical comparison of approaches is undertaken. Second, the bias and coverage are assessed for the pooled hazard ratio using simulated data under commonly encountered meta-analysis conditions. Finally, a comparison is presented using empirical data from four separate systematic reviews of anti-epileptic drug trials where IPD are available for two time-to-event outcomes.
For hazard ratio close to 1 with minimal heterogeneity between trials, theoretical results suggest similar results should be expected from all the three methods. Results for empirical and simulated data are in keeping with the theoretical results and show all the three methods perform well under these conditions. When there is no heterogeneity and the proportional hazards assumption holds, the stratified Cox model and inverse variance weighted average produce similar estimates of the pooled treatment effect and are to be preferred to the stratified log-rank analysis when the underlying treatment effect is large. Coverage values diminish for all the three methods and are below 95% for low or moderate heterogeneity. The low coverage values highlight the need for models that appropriately account for or explore the between trial variation.
Until larger simulations can be undertaken, conclusions based on the simulated and empirical data should only be applied to small meta-analyses of four or five trials.
These investigations suggest that under normal conditions all three methods provide similar results. For moderate heterogeneity coverage for all the three fixed effects models depreciates.
针对事件发生时间结局的个体患者数据(IPD)荟萃分析的替代方法已被确立并在实践中得到应用。最常见的方法是分层对数秩检验分析。IPD方法被认为是荟萃分析的金标准方法,并且越来越受欢迎,但之前尚未研究过不同方法的性能。
比较个体患者事件发生时间数据固定效应荟萃分析的常用方法。
比较分层对数秩检验分析、Cox模型估计值的逆方差加权平均值以及分层Cox回归模型。首先,对这些方法进行理论比较。其次,在常见的荟萃分析条件下,使用模拟数据评估合并风险比的偏差和覆盖率。最后,使用来自四项单独的抗癫痫药物试验系统评价的经验数据进行比较,这些试验中有两项事件发生时间结局的IPD数据可用。
对于试验间异质性最小且风险比接近1的情况,理论结果表明这三种方法应能得到相似的结果。经验数据和模拟数据的结果与理论结果一致,表明这三种方法在这些条件下表现良好。当不存在异质性且比例风险假设成立时,分层Cox模型和逆方差加权平均值对合并治疗效果的估计相似,并且当潜在治疗效果较大时,比分层对数秩检验分析更可取。对于所有三种方法,覆盖率值都会降低,对于低或中度异质性,覆盖率值低于95%。低覆盖率值凸显了需要能够适当考虑或探究试验间变异的模型。
在能够进行更大规模的模拟之前,基于模拟和经验数据得出的结论仅应适用于四五项试验的小型荟萃分析。
这些研究表明,在正常条件下,所有三种方法都能提供相似的结果。对于中度异质性,所有三种固定效应模型的覆盖率都会降低。