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Methodological quality of meta-analyses: matched-pairs comparison over time and between industry sponsored and academic-sponsored reports

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Peter W. Lane
  • Julian P. T. Higgins
  • Betsy Anagnostelis
  • Judith Anzures-Cabrera
  • Nigel F. Baker
  • Joseph C. Cappelleri
  • Scott Haughie
  • Sally Hollis
  • Steff C. Lewis
  • Patrick Moneuse
  • Anne Whitehead
<mark>Journal publication date</mark>12/2013
<mark>Journal</mark>Research Synthesis Methods
Issue number4
Number of pages9
Pages (from-to)342-350
Publication StatusPublished
<mark>Original language</mark>English


Context: Meta-analyses are regularly used to inform healthcare decisions. Concerns have been expressed about the quality of meta-analyses and, in particular, about those supported by the pharmaceutical industry.
Objective: The objective of this study is to compare the quality of pharmaceutical-industry-supported meta-analyses with academic meta-analyses and of meta-analyses published before and after companies started to disclose their data.
Data Sources: We identified industry-supported meta-analyses by searching the Scopus bibliographic database, using author affiliations. We matched each industry-supported meta-analysis with an academic meta-analysis using high-level MeSH terms in PubMed.
Study Selection: We included meta-analyses of randomized trials assessing the efficacy or safety of any pharmaceutical intervention in humans, published in 2002–2004 or 2008–2009. Cochrane reviews were excluded. Two individuals independently selected papers, with discrepancies resolved by two further
Assessment: We developed and piloted a quality-assessment tool, consisting of 43 questions in four domains, with a key summary question covering each domain. Two individuals independently assessed each meta-analysis.
Results: We examined 126 meta-analysis publications in 63 matched pairs. The average quality was low, with fewer than 50% adequate in three of the four domains. Industry-supported meta-analyses less often