How valuable are multiple treatment comparison methods in evidence-based health-care evaluation?

Nicola J. Cooper, Jaime Peters, Monica C. W. Lai, Peter Juni, Simon Wandel, Steve Palmer, Mike Paulden, Stefano Conti, Nicky J. Welton, Keith R. Abrams, Sylwia Bujkiewicz, David Spiegelhalter, Alex J. Sutton

Research output: Contribution to journalArticle (Academic Journal)peer-review

38 Citations (Scopus)


Objectives: To compare the use of pair-wise meta-analysis methods to multiple treatment comparison (MTC) methods for evidence-based health-care evaluation to estimate the effectiveness and cost-effectiveness of alternative health-care interventions based on the available evidence.

Methods: Pair-wise meta-analysis and more complex evidence syntheses, incorporating an MTC component, are applied to three examples: 1) clinical effectiveness of interventions for preventing strokes in people with atrial fibrillation; 2) clinical and cost-effectiveness of using drug-eluting stents in percutaneous coronary intervention in patients with coronary artery disease; and 3) clinical and cost-effectiveness of using neuraminidase inhibitors in the treatment of influenza. We compare the two synthesis approaches with respect to the assumptions made, empirical estimates produced, and conclusions drawn.

Results: The difference between point estimates of effectiveness produced by the pair-wise and MTC approaches was generally unpredictable-sometimes agreeing closely whereas in other instances differing considerably. In all three examples, the MTC approach allowed the inclusion of randomized controlled trial evidence ignored in the pair-wise meta-analysis approach. This generally increased the precision of the effectiveness estimates from the MTC model.

Conclusions: The MTC approach to synthesis allows the evidence base on clinical effectiveness to be treated as a coherent whole, include more data, and sometimes relax the assumptions made in the pair-wise approaches. However, MTC models are necessarily more complex than those developed for pair-wise meta-analysis and thus could be seen as less transparent. Therefore, it is important that model details and the assumptions made are carefully reported alongside the results. Copyright (C) 2011, International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.

Original languageEnglish
Pages (from-to)371-380
Number of pages10
JournalValue in Health
Issue number2
Publication statusPublished - 2011

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