Methods in Evidence Synthesis Unit, School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia.
Center for Bioethics and Humanities, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.
Res Synth Methods. 2024 Jul;15(4):524-542. doi: 10.1002/jrsm.1706. Epub 2024 Feb 5.
We aimed to explore, in a sample of systematic reviews (SRs) with meta-analyses of the association between food/diet and health-related outcomes, whether systematic reviewers selectively included study effect estimates in meta-analyses when multiple effect estimates were available. We randomly selected SRs of food/diet and health-related outcomes published between January 2018 and June 2019. We selected the first presented meta-analysis in each review (index meta-analysis), and extracted from study reports all study effect estimates that were eligible for inclusion in the meta-analysis. We calculated the Potential Bias Index (PBI) to quantify and test for evidence of selective inclusion. The PBI ranges from 0 to 1; values above or below 0.5 suggest selective inclusion of effect estimates more or less favourable to the intervention, respectively. We also compared the index meta-analytic estimate to the median of a randomly constructed distribution of meta-analytic estimates (i.e., the estimate expected when there is no selective inclusion). Thirty-nine SRs with 312 studies were included. The estimated PBI was 0.49 (95% CI 0.42-0.55), suggesting that the selection of study effect estimates from those reported was consistent with a process of random selection. In addition, the index meta-analytic effect estimates were similar, on average, to what we would expect to see in meta-analyses generated when there was no selective inclusion. Despite this, we recommend that systematic reviewers report the methods used to select effect estimates to include in meta-analyses, which can help readers understand the risk of selective inclusion bias in the SRs.
我们旨在探讨在具有食物/饮食与健康相关结局相关性的荟萃分析的系统评价(SR)样本中,系统评价者在存在多个效应估计值的情况下,是否会选择性地纳入荟萃分析中的研究效应估计值。我们随机选择了 2018 年 1 月至 2019 年 6 月间发表的食物/饮食与健康相关结局的 SR。我们选择了每篇综述中的第一篇呈现的荟萃分析(索引荟萃分析),并从研究报告中提取了所有有资格纳入荟萃分析的研究效应估计值。我们计算了潜在偏倚指数(PBI)来量化和检验选择性纳入的证据。PBI 的范围为 0 到 1;高于或低于 0.5 分别表示对干预措施有利或不利的效应估计值更有可能被选择性纳入。我们还将索引荟萃分析估计值与随机构建的荟萃分析估计值分布的中位数进行了比较(即当没有选择性纳入时预期的估计值)。39 篇综述包含 312 项研究。估计的 PBI 为 0.49(95%CI 0.42-0.55),这表明从报告中选择研究效应估计值的过程与随机选择一致。此外,索引荟萃分析的效应估计值平均与我们预期在没有选择性纳入时生成的荟萃分析中看到的效应估计值相似。尽管如此,我们仍建议系统评价者报告用于选择纳入荟萃分析的效应估计值的方法,这可以帮助读者了解 SR 中选择性纳入偏倚的风险。