MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK.
BMC Med Res Methodol. 2022 Mar 20;22(1):73. doi: 10.1186/s12874-022-01541-9.
Systematic reviews and meta-analysis of time-to-event outcomes are frequently published within the Cochrane Database of Systematic Reviews (CDSR). However, these outcomes are handled differently across meta-analyses. They can be analysed on the hazard ratio (HR) scale or can be dichotomized and analysed as binary outcomes using effect measures such as odds ratios (OR) or risk ratios (RR). We investigated the impact of reanalysing meta-analyses from the CDSR that used these different effect measures.
We extracted two types of meta-analysis data from the CDSR: either recorded in a binary form only ("binary"), or in binary form together with observed minus expected and variance statistics ("OEV"). We explored how results for time-to-event outcomes originally analysed as "binary" change when analysed using the complementary log-log (clog-log) link on a HR scale. For the data originally analysed as HRs ("OEV"), we compared these results to analysing them as binary on a HR scale using the clog-log link or using a logit link on an OR scale.
The pooled HR estimates were closer to 1 than the OR estimates in the majority of meta-analyses. Important differences in between-study heterogeneity between the HR and OR analyses were also observed. These changes led to discrepant conclusions between the OR and HR scales in some meta-analyses. Situations under which the clog-log link performed better than logit link and vice versa were apparent, indicating that the correct choice of the method does matter. Differences between scales arise mainly when event probability is high and may occur via differences in between-study heterogeneity or via increased within-study standard error in the OR relative to the HR analyses.
We identified that dichotomising time-to-event outcomes may be adequate for low event probabilities but not for high event probabilities. In meta-analyses where only binary data are available, the complementary log-log link may be a useful alternative when analysing time-to-event outcomes as binary, however the exact conditions need further exploration. These findings provide guidance on the appropriate methodology that should be used when conducting such meta-analyses.
系统评价和荟萃分析的时间事件结果经常发表在 Cochrane 系统评价数据库（CDSR）中。然而，这些结果在荟萃分析中处理方式不同。它们可以在危险比（HR）尺度上进行分析，也可以通过使用优势比（OR）或风险比（RR）等效应测量值将其离散化并作为二元结果进行分析。我们研究了重新分析使用这些不同效应测量值的 CDSR 中的荟萃分析的影响。
我们从 CDSR 中提取了两种类型的荟萃分析数据：仅以二进制形式记录的（“二进制”），或同时以二进制形式记录并记录观察到的减去预期值和方差统计数据（“OEV”）。我们探索了当原始分析为“二进制”的时间事件结果在 HR 尺度上使用互补对数（clog-log）链接进行分析时，结果如何变化。对于最初以 HR 分析的数据（“OEV”），我们将这些结果与在 HR 尺度上使用 clog-log 链接或使用 OR 尺度上的对数链接进行二进制分析进行了比较。
在大多数荟萃分析中，汇总 HR 估计值比 OR 估计值更接近 1。还观察到 HR 和 OR 分析之间在研究间异质性方面的重要差异。这些变化导致了一些荟萃分析中 OR 和 HR 尺度之间不一致的结论。在 clog-log 链接表现优于对数链接和反之亦然的情况下明显存在，这表明正确选择方法确实很重要。在事件概率高的情况下，主要会出现尺度之间的差异，并且可能是通过研究间异质性的差异或通过 OR 分析相对于 HR 分析增加了研究内标准误差而发生的。
我们发现，将时间事件结果离散化为二进制可能适用于低事件概率，但不适用于高事件概率。在仅提供二进制数据的荟萃分析中，互补对数链接可能是分析时间事件结果为二进制的有用替代方法，但是需要进一步探索确切的条件。这些发现为进行此类荟萃分析时应使用的适当方法提供了指导。
