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Interpreting discordant indirect and multiple treatment comparison meta-analyses: an evaluation of direct acting antivirals for chronic hepatitis C infection

Authors Druyts E, Thorlund K, Humphreys S, Lion M, Cooper CL, Mills EJ

Received 20 February 2013

Accepted for publication 22 April 2013

Published 20 June 2013 Volume 2013:5(1) Pages 173—183


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Eric Druyts,1 Kristian Thorlund,2,3 Samantha Humphreys,4 Michaela Lion,4 Curtis L Cooper,5 Edward J Mills1,3

Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada; 2Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada; 3Stanford Prevention Research Centre, Department of Medicine, Stanford University, Palo Alto, CA, USA; 4Merck Sharp and Dohme Ltd, UK; 5Division of Infectious Diseases, Department of Medicine, The Ottawa Hospital, University of Ottawa, Ottawa, Ontario, Canada

Abstract: Indirect treatment comparison (ITC) and multiple treatment comparison (MTC) meta-analyses are increasingly being used to estimate the comparative effectiveness of interventions when head-to-head data do not exist. ITC meta-analyses can be conducted using simple methodology to compare two interventions. MTC meta-analyses can be conducted using more complex methodology, often employing Bayesian approaches, to compare multiple interventions. As the number of ITC and MTC meta-analyses increase, it is common to find multiple analyses evaluating the same interventions in similar therapeutic areas. Depending on the choice of the methodological approach, the conclusions about relative treatment efficacy may differ. Such situations create uncertainty for decision makers. An illustration of this is provided by four ITC and MTC meta-analyses assessing the efficacy of boceprevir and telaprevir for chronic hepatitis C virus infection. This paper examines why these evaluations provide discordant results by examining specific methodological issues that can strengthen or weaken inferences.

Keywords: indirect treatment comparison, multiple treatment comparison, meta-analysis, hepatitis C virus

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