11
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Indirect and mixed-treatment comparison, network, or multiple-treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool.

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The ever increasing number of alternative treatment options and the plethora of clinical trials have put systematic reviews and meta-analysis under a new perspective by emphasizing the need to make inferences about competing treatments for the same condition. The statistical component in reviews that compare multiple interventions, network meta-analysis, is the next generation evidence synthesis toolkit which, when properly applied, can serve decision-making better than the established pairwise meta-analysis. The criticism and enthusiasm for network meta-analysis echo those that greeted the advent of simple meta-analysis. The main criticism is associated with the difficulty in evaluating the assumption underlying the statistical synthesis of direct and indirect evidence. In the present article, the assumption of the network meta-analysis are presented using various formulations, the statistical and nonstatistical methodological considerations are elucidated, and the progress achieved in this field is summarized. Throughout, focus is put on highlighting the analogy between the concerns and difficulties that the scientific community had some time ago when advancing from individual trials to their quantitative synthesis via meta-analysis and those currently expressed about the transition from head-to-head meta-analyses to network meta-analysis. Copyright © 2012 John Wiley & Sons, Ltd.

          Related collections

          Author and article information

          Journal
          Res Synth Methods
          Research synthesis methods
          1759-2879
          1759-2879
          Jun 2012
          : 3
          : 2
          Affiliations
          [1 ] Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece. gsalanti@cc.uoi.gr.
          Article
          10.1002/jrsm.1037
          26062083
          6dec54ab-35e5-4ba5-b41b-cfdd4f96a33a
          Copyright © 2012 John Wiley & Sons, Ltd.
          History

          assumptions,consistency,evidence‐based practice,systematic reviews,transitivity

          Comments

          Comment on this article