Indirect comparisons of competing interventions

• Published in: Health technology assessment (Winchester, England) England), 2005-07, Vol.9 (26), p.1-134
• Main Authors: Glenny, A M, Altman, D G, Song, F, Sakarovitch, C, Deeks, J J, D'Amico, R, Bradburn, M, Eastwood, A J
• Format: Article
• Language: English
• Subjects: Bias; Biomedical Research - methods; Humans; Meta-Analysis as Topic; Randomized Controlled Trials as Topic - methods; Research Design; Review Literature as Topic; Treatment Outcome
• ISSN: 1366-5278; 2046-4924; 1366-5278
• DOI: 10.3310/hta9260

To survey the frequency of use of indirect comparisons in systematic reviews and evaluate the methods used in their analysis and interpretation. Also to identify alternative statistical approaches for the analysis of indirect comparisons, to assess the properties of different statistical methods used for performing indirect comparisons and to compare direct and indirect estimates of the same effects within reviews. Electronic databases. The Database of Abstracts of Reviews of Effects (DARE) was searched for systematic reviews involving meta-analysis of randomised controlled trials (RCTs) that reported both direct and indirect comparisons, or indirect comparisons alone. A systematic review of MEDLINE and other databases was carried out to identify published methods for analysing indirect comparisons. Study designs were created using data from the International Stroke Trial. Random samples of patients receiving aspirin, heparin or placebo in 16 centres were used to create meta-analyses, with half of the trials comparing aspirin and placebo and half heparin and placebo. Methods for indirect comparisons were used to estimate the contrast between aspirin and heparin. The whole process was repeated 1000 times and the results were compared with direct comparisons and also theoretical results. Further detailed case studies comparing the results from both direct and indirect comparisons of the same effects were undertaken. Of the reviews identified through DARE, 31/327 (9.5%) included indirect comparisons. A further five reviews including indirect comparisons were identified through electronic searching. Few reviews carried out a formal analysis and some based analysis on the naive addition of data from the treatment arms of interest. Few methodological papers were identified. Some valid approaches for aggregate data that could be applied using standard software were found: the adjusted indirect comparison, meta-regression and, for binary data only, multiple logistic regression (fixed effect models only). Simulation studies showed that the naive method is liable to bias and also produces over-precise answers. Several methods provide correct answers if strong but unverifiable assumptions are fulfilled. Four times as many similarly sized trials are needed for the indirect approach to have the same power as directly randomised comparisons. Detailed case studies comparing direct and indirect comparisons of the same effect show considerable statistical discrepancies, bu