Schmucker Christine M, Blümle Anette, Schell Lisa K, Schwarzer Guido, Oeller Patrick, Cabrera Laura, von Elm Erik, Briel Matthias, Meerpohl Joerg J
Cochrane Germany, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.
Institute for Quality and Efficiency in Health Care, Cologne, Germany.
PLoS One. 2017 Apr 25;12(4):e0176210. doi: 10.1371/journal.pone.0176210. eCollection 2017.
A meta-analysis as part of a systematic review aims to provide a thorough, comprehensive and unbiased statistical summary of data from the literature. However, relevant study results could be missing from a meta-analysis because of selective publication and inadequate dissemination. If missing outcome data differ systematically from published ones, a meta-analysis will be biased with an inaccurate assessment of the intervention effect. As part of the EU-funded OPEN project (www.open-project.eu) we conducted a systematic review that assessed whether the inclusion of data that were not published at all and/or published only in the grey literature influences pooled effect estimates in meta-analyses and leads to different interpretation.
Systematic review of published literature (methodological research projects). Four bibliographic databases were searched up to February 2016 without restriction of publication year or language. Methodological research projects were considered eligible for inclusion if they reviewed a cohort of meta-analyses which (i) compared pooled effect estimates of meta-analyses of health care interventions according to publication status of data or (ii) examined whether the inclusion of unpublished or grey literature data impacts the result of a meta-analysis. Seven methodological research projects including 187 meta-analyses comparing pooled treatment effect estimates according to different publication status were identified. Two research projects showed that published data showed larger pooled treatment effects in favour of the intervention than unpublished or grey literature data (Ratio of ORs 1.15, 95% CI 1.04-1.28 and 1.34, 95% CI 1.09-1.66). In the remaining research projects pooled effect estimates and/or overall findings were not significantly changed by the inclusion of unpublished and/or grey literature data. The precision of the pooled estimate was increased with narrower 95% confidence interval.
Although we may anticipate that systematic reviews and meta-analyses not including unpublished or grey literature study results are likely to overestimate the treatment effects, current empirical research shows that this is only the case in a minority of reviews. Therefore, currently, a meta-analyst should particularly consider time, effort and costs when adding such data to their analysis. Future research is needed to identify which reviews may benefit most from including unpublished or grey data.
作为系统评价一部分的荟萃分析旨在对文献数据进行全面、综合且无偏倚的统计总结。然而，由于选择性发表和传播不足，相关研究结果可能会在荟萃分析中缺失。如果缺失的结果数据与已发表的数据存在系统性差异，荟萃分析将会产生偏倚，对干预效果的评估也会不准确。作为欧盟资助的开放项目（www.open-project.eu）的一部分，我们进行了一项系统评价，以评估纳入完全未发表和/或仅发表于灰色文献的数据是否会影响荟萃分析中的合并效应估计，并导致不同的解读。
对已发表文献（方法学研究项目）进行系统评价。检索了四个文献数据库，截至2016年2月，不受出版年份或语言限制。如果方法学研究项目回顾了一组荟萃分析，其中（i）根据数据的出版状态比较医疗保健干预荟萃分析的合并效应估计，或（ii）研究纳入未发表或灰色文献数据是否会影响荟萃分析的结果，则该项目被认为符合纳入条件。确定了七个方法学研究项目，包括187项根据不同出版状态比较合并治疗效应估计的荟萃分析。两项研究项目表明，与未发表或灰色文献数据相比，已发表数据显示出更有利于干预的更大合并治疗效应（比值比分别为1.15，95%置信区间1.04 - 1.28和1.34，95%置信区间1.
