Literature DB >> 34550593

Contrast-Based and Arm-Based Models for Network Meta-Analysis.

Amalia Karahalios1, Joanne E McKenzie2, Ian R White3.   

Abstract

Network meta-analysis is used to synthesize evidence from a network of treatments. The models used in a network meta-analysis are more complex than those used for pairwise meta-analysis. Two types of models are available to undertake a network meta-analysis: contrast-based and arm-based models. Contrast-based models have been used in most published network meta-analyses. Arm-based models offer greater flexibility and handle treatments symmetrically, but risk compromising randomization. In this chapter, we (1) present the contrast-based and arm-based statistical models; (2) describe the theoretical differences between the models (noting when the estimates from the models are expected to diverge); (3) summarize the evidence comparing the two models from simulation studies and empirical investigations; and (4) provide a worked example applying the two models to a network using the R software package.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Arm-based; Bayesian; Contrast-based; Mixed treatment comparisons; Models; Multiple treatments meta-analysis; Network meta-analysis; Systematic review

Mesh:

Year:  2022        PMID: 34550593     DOI: 10.1007/978-1-0716-1566-9_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  16 in total

Review 1.  GetReal in network meta-analysis: a review of the methodology.

Authors:  Orestis Efthimiou; Thomas P A Debray; Gert van Valkenhoef; Sven Trelle; Klea Panayidou; Karel G M Moons; Johannes B Reitsma; Aijing Shang; Georgia Salanti
Journal:  Res Synth Methods       Date:  2016-01-11       Impact factor: 5.273

2.  How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS.

Authors:  Paul C Lambert; Alex J Sutton; Paul R Burton; Keith R Abrams; David R Jones
Journal:  Stat Med       Date:  2005-08-15       Impact factor: 2.373

3.  Modeling between-trial variance structure in mixed treatment comparisons.

Authors:  Guobing Lu; Ae Ades
Journal:  Biostatistics       Date:  2009-08-17       Impact factor: 5.899

Review 4.  Evaluation of networks of randomized trials.

Authors:  Georgia Salanti; Julian P T Higgins; A E Ades; John P A Ioannidis
Journal:  Stat Methods Med Res       Date:  2007-10-09       Impact factor: 3.021

5.  Network meta-analysis of randomized clinical trials: reporting the proper summaries.

Authors:  Jing Zhang; Bradley P Carlin; James D Neaton; Guoxing G Soon; Lei Nie; Robert Kane; Beth A Virnig; Haitao Chu
Journal:  Clin Trials       Date:  2013-10-03       Impact factor: 2.486

6.  A Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons.

Authors:  Hwanhee Hong; Haitao Chu; Jing Zhang; Bradley P Carlin
Journal:  Res Synth Methods       Date:  2015-11-04       Impact factor: 5.273

7.  Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews.

Authors:  Rebecca M Turner; Jonathan Davey; Mike J Clarke; Simon G Thompson; Julian Pt Higgins
Journal:  Int J Epidemiol       Date:  2012-03-29       Impact factor: 7.196

8.  Absolute or relative effects? Arm-based synthesis of trial data.

Authors:  S Dias; A E Ades
Journal:  Res Synth Methods       Date:  2015-10-13       Impact factor: 5.273

9.  Combination of direct and indirect evidence in mixed treatment comparisons.

Authors:  G Lu; A E Ades
Journal:  Stat Med       Date:  2004-10-30       Impact factor: 2.373

10.  A comparison of arm-based and contrast-based models for network meta-analysis.

Authors:  Ian R White; Rebecca M Turner; Amalia Karahalios; Georgia Salanti
Journal:  Stat Med       Date:  2019-10-03       Impact factor: 2.373

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  1 in total

Review 1.  Analgesic Efficacy of Adjuvant Medications in the Pediatric Caudal Block for Infraumbilical Surgery: A Network Meta-Analysis of Randomized Controlled Trials.

Authors:  Ushma J Shah; Niveditha Karuppiah; Hovhannes Karapetyan; Janet Martin; Herman Sehmbi
Journal:  Cureus       Date:  2022-08-30
  1 in total

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