Meta-analyses in orthopaedic surgery - A systematic review of their methodologies

Background: The number and quality of well-designed scientific studies in t he orthopaedic literature are limited. The purpose of this review was to de termine the methodological qualities of published meta-analyses on orthopae dic-surgery-related topics. Methods: A systematic review of meta-analyses was conducted. A search of th e Medline database provided lists of meta-analyses in orthopaedics publishe d from 1969 to 1999. Extensive manual searches of major orthopaedic journal s, bibliographies of major orthopaedic texts, and personal files identified additional studies. Of 601 studies identified, forty met the criteria for eligibility. Two investigators each assessed the quality of the studies und er blinded conditions, and they abstracted relevant data. Results: More than 50% of the meta-analyses included in this review were pu blished after 1994. We found that 88% had methodological flaws that could l imit their validity. The main deficiency was a lack of information on the m ethods used to retrieve and assess the validity of the primary studies. Reg ression analysis revealed that meta-analyses authored in affiliation with a n epidemiology department and those published in nonsurgical journals were associated with higher scores for quality. Meta-analyses with lower scores for quality tended to report positive findings. The meta-analyses that focu sed upon fracture treatment and degenerative disease (hip, knee, or spine) had significantly lower mean quality scores than did meta-analyses that exa mined thrombosis prevention and diagnostic tests (p < 0.05). Conclusions: The majority of meta-analyses on orthopaedic-surgery-related t opics have methodological limitations. Limitation of bias and improvement i n the validity of the meta-analyses can be achieved by adherence to strict scientific methodology. However, the ultimate quality of a meta-analysis de pends on the quality of the primary studies on which it is based. A meta-an alysis is most persuasive when data from high-quality randomized trials are pooled.