Investigation of bias due to selective inclusion of study effect estimates in meta-analyses of nutrition research

IF 5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Research Synthesis Methods Pub Date : 2024-02-05 DOI:10.1002/jrsm.1706
Raju Kanukula, Joanne E. McKenzie, Lisa Bero, Zhaoli Dai, Sally McDonald, Cynthia M. Kroeger, Elizabeth Korevaar, Andrew Forbes, Matthew J. Page
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Abstract

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.

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调查营养研究元分析中选择性纳入研究效果估计值导致的偏差。
我们的目的是在对食物/饮食与健康相关结果的关联性进行荟萃分析的系统综述(SR)样本中,探讨当存在多个效应估计值时,系统综述者是否有选择性地将研究效应估计值纳入荟萃分析。我们随机选取了 2018 年 1 月至 2019 年 6 月间发表的有关食物/饮食与健康相关结果的 SR。我们选择了每篇综述中首次提出的荟萃分析(索引荟萃分析),并从研究报告中提取了所有符合纳入荟萃分析条件的研究效应估计值。我们计算了潜在偏倚指数(PBI),以量化和检验选择性纳入的证据。PBI 的范围在 0 到 1 之间;高于或低于 0.5 的数值分别表明有选择性地纳入了对干预更有利或更不利的效果估计值。我们还将指数荟萃分析估计值与随机构建的荟萃分析估计值分布(即不存在选择性纳入时的预期估计值)的中位数进行了比较。有 312 项研究的 39 篇研究报告被纳入其中。估计的 PBI 为 0.49(95% CI 0.42-0.55),表明从所报告的研究效果估计值中进行的选择符合随机选择的过程。此外,指数荟萃分析效应估计值的平均值与我们在没有选择性纳入的情况下进行荟萃分析时预计的结果相似。尽管如此,我们还是建议系统综述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。
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来源期刊
Research Synthesis Methods
Research Synthesis Methods MATHEMATICAL & COMPUTATIONAL BIOLOGYMULTID-MULTIDISCIPLINARY SCIENCES
CiteScore
16.90
自引率
3.10%
发文量
75
期刊介绍: Research Synthesis Methods is a reputable, peer-reviewed journal that focuses on the development and dissemination of methods for conducting systematic research synthesis. Our aim is to advance the knowledge and application of research synthesis methods across various disciplines. Our journal provides a platform for the exchange of ideas and knowledge related to designing, conducting, analyzing, interpreting, reporting, and applying research synthesis. While research synthesis is commonly practiced in the health and social sciences, our journal also welcomes contributions from other fields to enrich the methodologies employed in research synthesis across scientific disciplines. By bridging different disciplines, we aim to foster collaboration and cross-fertilization of ideas, ultimately enhancing the quality and effectiveness of research synthesis methods. Whether you are a researcher, practitioner, or stakeholder involved in research synthesis, our journal strives to offer valuable insights and practical guidance for your work.
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