Leclercq Victoria, Beaudart Charlotte, Ajamieh Sara, Tirelli Ezio, Bruyère Olivier
Division of Public Health, Epidemiology and Health Economics, University of Liege, Liege, Belgium
Division of Public Health, Epidemiology and Health Economics, University of Liege, Liege, Belgium.
BMJ Open. 2020 Aug 3;10(8):e036349. doi: 10.1136/bmjopen-2019-036349.
Meta-analyses (MAs) are often used because they are lauded to provide robust evidence that synthesises information from multiple studies. However, the validity of MA conclusions relies on the procedural rigour applied by the authors. Therefore, this meta-research study aims to characterise the methodological quality and meta-analytic practices of MAs indexed in PsycINFO.
A meta-epidemiological study.
We evaluated a random sample of 206 MAs indexed in the PsycINFO database in 2016.
Two authors independently extracted the methodological characteristics of all MAs and checked their quality according to the 16 items of the A MeaSurement Tool to Assess systematic Reviews (AMSTAR2) tool for MA critical appraisal. Moreover, we investigated the effect of mentioning Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) on the methodological quality of MAs.
According to AMSTAR2 criteria, 95% of the 206 MAs were rated as critically low quality. Statistical methods were appropriate and publication bias was well evaluated in 87% and 70% of the MAs, respectively. However, much improvement is needed in data collection and analysis: only 11% of MAs published a research protocol, 44% had a comprehensive literature search strategy, 37% assessed and 29% interpreted the risk of bias in the individual included studies, and 11% presented a list of excluded studies. Interestingly, the explicit mentioning of PRISMA suggested a positive influence on the methodological quality of MAs.
The methodological quality of MAs in our sample was critically low according to the AMSTAR2 criteria. Some efforts to tremendously improve the methodological quality of MAs could increase their robustness and reliability.
元分析（MAs）经常被使用，因为它们被誉为能提供强有力的证据，综合多项研究的信息。然而，元分析结论的有效性依赖于作者所采用程序的严谨性。因此，这项元研究旨在描述PsycINFO中索引的元分析的方法学质量和元分析实践。
一项元流行病学研究。
我们评估了2016年PsycINFO数据库中索引的206项元分析的随机样本。
两位作者独立提取了所有元分析的方法学特征，并根据评估系统评价的测量工具（AMSTAR2）工具的16项内容对其质量进行检查，以进行元分析的批判性评价。此外，我们调查了提及系统评价和元分析的首选报告项目（PRISMA）对元分析方法学质量的影响。
根据AMSTAR2标准，206项元分析中有95%被评为极低质量。分别有87%和70%的元分析统计方法恰当且对发表偏倚进行了良好评估。然而，在数据收集和分析方面仍需大幅改进：只有11%的元分析发表了研究方案，44%有全面的文献检索策略，37%评估且29%解释了纳入的个体研究中的偏倚风险，11%列出了排除研究清单。有趣的是，明确提及PRISMA对元分析的方法学质量有积极影响。
根据AMSTAR2标准，我们样本中元分析的方法学质量极低。为大幅提高元分析的方法学质量所做的一些努力可以增加其稳健性和可靠性。
