4.4 Article

Indirect comparisons of treatments based on systematic reviews of randomised controlled trials

期刊

INTERNATIONAL JOURNAL OF CLINICAL PRACTICE
卷 63, 期 6, 页码 841-854

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WILEY
DOI: 10.1111/j.1742-1241.2009.02072.x

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  1. UK Department of Health
  2. AstraZeneca UK Ltd.

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Randomised controlled trials are the most effective way to differentiate between the effects of competing interventions. However, head-to-head studies are unlikely to have been conducted for all competing interventions. Evaluation of different methodologies used to indirectly compare interventions based on meta analyses of randomised controlled trials. Systematic review of Cochrane Database of Systematic Reviews, Cochrane Methodology Register, EMBASE and MEDLINE for reports including meta analyses that contained an indirect comparison. Searching was completed in July 2007. No restriction was placed on language or year of publication. Sixty-two papers identified contained indirect comparisons of treatments. Five different methodologies were employed: comparing point estimates (1/62); comparing 95% confidence intervals (26/62); performing statistical tests on summary estimates (8/62); indirect comparison using a single common comparator (20/62); and mixed treatment comparison (MTC) (7/62). The only methodologies that provide an estimate of the difference between the interventions under consideration and a measure of the uncertainty around that estimate are indirect comparison using a single common comparator and MTC. The MTC might have advantages over other approaches because it is not reliant on a single common comparator and can incorporate the results of direct and indirect comparisons into the analysis. Indirect comparisons require an underlying assumption of consistency of evidence. Utilising any of the methodologies when this assumption is not true can produce misleading results. Use of either indirect comparison using a common comparator or MTC provides estimates for use in decision making, with the preferred methodology being dependent on the available data.

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