Institute for Evidence in Medicine, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Cochrane Germany, Cochrane Germany Foundation, Freiburg, Germany.
Res Synth Methods. 2022 May;13(3):330-341. doi: 10.1002/jrsm.1543. Epub 2022 Jan 6.
Using the Hartung-Knapp method and 95% prediction intervals (PIs) in random-effects meta-analyses is recommended by experts but rarely applied. Therefore, we aimed to reevaluate statistically significant meta-analyses using the Hartung-Knapp method and 95% PIs. In this methodological study, three databases were searched from January 2010 to July 2019. We included systematic reviews reporting a statistically significant meta-analysis of at least four randomized controlled trials in advanced cancer patients using either a fixed-effect or random-effects model. We investigated the impact of switching from fixed-effect to random-effects meta-analysis and of using the recommended Hartung-Knapp method in random-effects meta-analyses. Furthermore, we calculated 95% PIs for all included meta-analyses. We identified 6234 hits, of which 261 statistically significant meta-analyses were included. Our recalculations of these 261 meta-analyses produced statistically significant results in 132 of 138 fixed-effect and 114 of 123 random-effects meta-analyses. When switching to a random-effects model, 19 of 132 fixed-effect meta-analyses (14.4%) were no longer statistically significant. Using the Hartung-Knapp method in random-effects meta-analyses resulted in 34 of 114 nonsignificant meta-analyses (29.8%). In the full sample (N = 261), the null effect was included by the 95% PI in 195 (74.7%) and the opposite effect (e.g., hazard ratio 0.5, opposite effect 2) in 98 meta-analyses (37.5%). Using the Hartung-Knapp method and PIs substantially influenced the interpretation of many published, statistically significant meta-analyses. We strongly encourage researchers to check if using the Hartung-Knapp method and reporting 95% PIs is appropriate in random-effects meta-analyses.
使用 Hartung-Knapp 方法和 95%预测区间 (PI) 进行随机效应荟萃分析是专家推荐的,但很少被应用。因此,我们旨在重新评估使用 Hartung-Knapp 方法和 95%PI 的具有统计学意义的荟萃分析。在这项方法学研究中,我们从 2010 年 1 月至 2019 年 7 月在三个数据库中进行了检索。我们纳入了系统评价,这些系统评价报告了至少四项随机对照试验的荟萃分析,这些试验在晚期癌症患者中使用固定效应或随机效应模型进行。我们调查了从固定效应荟萃分析转换为随机效应荟萃分析以及在随机效应荟萃分析中使用推荐的 Hartung-Knapp 方法的影响。此外,我们计算了所有纳入荟萃分析的 95%PI。我们确定了 6234 个命中结果,其中包括 261 项具有统计学意义的荟萃分析。我们对这 261 项荟萃分析进行了重新计算,结果在 138 项固定效应荟萃分析中的 132 项和 123 项随机效应荟萃分析中的 114 项中产生了统计学意义的结果。当转换为随机效应模型时,132 项固定效应荟萃分析中的 19 项(14.4%)不再具有统计学意义。在随机效应荟萃分析中使用 Hartung-Knapp 方法导致 114 项非显著荟萃分析中的 34 项(29.8%)。在整个样本(N=261)中,95%PI 纳入了 195 项(74.7%)的无效效应和 98 项荟萃分析中的 98 项(37.5%)的相反效应(例如,危险比 0.5,相反效应 2)。使用 Hartung-Knapp 方法和 PI 极大地影响了许多已发表的、具有统计学意义的荟萃分析的解释。我们强烈鼓励研究人员检查在随机效应荟萃分析中使用 Hartung-Knapp 方法和报告 95%PI 是否合适。