A tool to assess the quality of a meta‐analysis. (18th October 2013)

• Record Type: Journal Article
• Authors: Higgins, Julian P.T.; Lane, Peter W.; Anagnostelis, Betsy; Anzures‐Cabrera, Judith; Baker, Nigel F.; Cappelleri, Joseph C.; Haughie, Scott; Hollis, Sally; Lewis, Steff C.; Moneuse, Patrick; Whitehead, Anne
• Is Part Of: Research synthesis methods. Volume 4:Number 4(2013:Oct./Dec.)
• Page Start: 351
• Page End: 366
• Publication Date: 2013-10-18
• Subjects: Research -- Methodology -- Periodicals; Research -- Statistical methods -- Periodicals; 507.2
• DOI: 10.1002/jrsm.1092
• Languages: English
• ISSNs: 1759-2879

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="jrsm1092-sec-0001" sec-type="section"> <title>Background</title> <p>Because meta‐analyses are increasingly prevalent and cited in the medical literature, it is important that tools are available to assess their methodological quality. When performing an empirical study of the quality of published meta‐analyses, we found that existing tools did not place a strong emphasis on statistical and interpretational issues.</p> </sec> <sec id="jrsm1092-sec-0002" sec-type="section"> <title>Methods</title> <p>We developed a quality‐assessment tool using existing materials and expert judgment as a starting point, followed by multiple iterations of input from our working group, piloting, and discussion. After having used the tool for our empirical study, agreement for four key items in the tool was measured using weighted kappa coefficients.</p> </sec> <sec id="jrsm1092-sec-0003" sec-type="section"> <title>Results</title> <p>Our tool contained 43 items divided into four key areas (data sources, analysis of individual studies, meta‐analysis methods, and interpretation), and each area ended with a summary question. We also produced guidance for completing the tool. Agreement between raters was fair to moderate.</p> </sec> <sec id="jrsm1092-sec-0004" sec-type="section"> <title>Conclusions</title> <p>The tool should usefully inform subsequent initiatives to develop quality‐assessment tools for meta‐analysis. We advocate use of consensus between independent raters when assessing statistical appropriateness and adequacy of interpretation in meta‐analyses. Copyright © 2013 John Wiley & Sons, Ltd.</p> </sec> </abstract>