Much ado about nothing: a comparison of the performance of meta-analytical methods with rare events
Much ado about nothing: a comparison of the performance of meta-analytical methods with rare events
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DOI：
10.1002/sim.2528
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发表时间：
2007-01-15
影响因子：
2
通讯作者：
Localio, A. Russell
中科院分区：
文献类型：
--
作者：
Bradburn, Michael J.;Deeks, Jonathan J.;Localio, A. Russell
对于罕见的结果，随机试验的荟萃分析可能是获得医疗干预效果可靠证据的唯一途径。然而，许多荟萃分析方法都是基于大样本近似，当事件很少时可能不适合。通过模拟，我们评估了12种方法用于汇集罕见事件的性能，考虑了可估计性，偏倚，覆盖率和统计功效。模拟基于三个案例研究的数据集，这些案例研究包括5至19项试验，基线事件发生率为0.1%至10%，风险比为1，0.75，0.5和0.2。我们发现，大多数常用的元分析方法是有偏见的数据稀疏时。在逆方差、DerSimonian和Laird比值比和风险差方法以及使用0.5零单元校正的Mantel-Haenszel（MH）比值比方法中，偏倚最大。风险差异荟萃分析方法倾向于显示保守的置信区间覆盖率和低事件率下的低统计功效。在事件发生率低于1%时，Peto一步比值比方法是偏倚最小和最有效的方法，并且提供了最佳置信区间覆盖范围，前提是试验中治疗组和对照组规模之间没有实质性失衡，并且治疗效应不是特别大。在其他情况下，没有零单元校正的MH OR，逻辑回归和精确方法彼此相似，并且比Peto方法偏倚更小。版权所有（c）2006约翰威利父子有限公司。
For rare outcomes, meta-analysis of randomized trials may be the only way to obtain reliable evidence of the effects of healthcare interventions. However, many methods of meta-analysis are based on large sample approximations, and may be unsuitable when events are rare. Through simulation, we evaluated the performance of 12 methods for pooling rare events, considering estimability, bias, coverage and statistical power. Simulations were based on data sets from three case studies with between five and 19 trials, using baseline event rates between 0.1 and 10 per cent and risk ratios of 1, 0.75, 0.5 and 0.2. We found that most of the commonly used meta-analytical methods were biased when data were sparse. The bias was greatest in inverse variance and DerSimonian and Laird odds ratio and risk difference methods, and the Mantel-Haenszel (MH) odds ratio method using a 0.5 zero-cell correction. Risk difference meta-analytical methods tended to show conservative confidence interval coverage and low statistical power at low event rates. At event rates below 1 per cent the Peto one-step odds ratio method was the least biased and most powerful method, and provided the best confidence interval coverage, provided there was no substantial imbalance between treatment and control group sizes within trials, and treatment effects were not exceptionally large. In other circumstances the MH OR without zero-cell corrections, logistic regression and the exact method performed similarly to each other, and were less biased than the Peto method. Copyright (c) 2006 John Wiley & Sons, Ltd.