Literature DB >> 26754852

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

Orestis Efthimiou1, Thomas P A Debray2,3, Gert van Valkenhoef4, Sven Trelle5,6, Klea Panayidou5, Karel G M Moons2,3, Johannes B Reitsma2,3, Aijing Shang7, Georgia Salanti8.   

Abstract

Pairwise meta-analysis is an established statistical tool for synthesizing evidence from multiple trials, but it is informative only about the relative efficacy of two specific interventions. The usefulness of pairwise meta-analysis is thus limited in real-life medical practice, where many competing interventions may be available for a certain condition and studies informing some of the pairwise comparisons may be lacking. This commonly encountered scenario has led to the development of network meta-analysis (NMA). In the last decade, several applications, methodological developments, and empirical studies in NMA have been published, and the area is thriving as its relevance to public health is increasingly recognized. This article presents a review of the relevant literature on NMA methodology aiming to pinpoint the developments that have appeared in the field.
Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Keywords:  comparing multiple interventions; indirect treatment comparison; mixed-treatment comparison; multiple-treatment meta-analysis

Mesh:

Substances:

Year:  2016        PMID: 26754852     DOI: 10.1002/jrsm.1195

Source DB:  PubMed          Journal:  Res Synth Methods        ISSN: 1759-2879            Impact factor:   5.273


  78 in total

1.  Methodological approaches for analysing data from therapeutic efficacy studies.

Authors:  Solange Whegang Youdom; Leonardo K Basco
Journal:  Malar J       Date:  2021-05-21       Impact factor: 2.979

2.  Perspective: Network Meta-analysis Reaches Nutrition Research: Current Status, Scientific Concepts, and Future Directions.

Authors:  Lukas Schwingshackl; Guido Schwarzer; Gerta Rücker; Joerg J Meerpohl
Journal:  Adv Nutr       Date:  2019-09-01       Impact factor: 8.701

Review 3.  Network meta-analysis: an introduction for pharmacists.

Authors:  Yina Xu; Mohamed Amine Amiche; Mina Tadrous
Journal:  Int J Clin Pharm       Date:  2018-10

4.  Borrowing of strength from indirect evidence in 40 network meta-analyses.

Authors:  Lifeng Lin; Aiwen Xing; Michael J Kofler; Mohammad Hassan Murad
Journal:  J Clin Epidemiol       Date:  2018-10-17       Impact factor: 6.437

5.  Quantifying and presenting overall evidence in network meta-analysis.

Authors:  Lifeng Lin
Journal:  Stat Med       Date:  2018-07-18       Impact factor: 2.373

6.  Fragility index of network meta-analysis with application to smoking cessation data.

Authors:  Aiwen Xing; Haitao Chu; Lifeng Lin
Journal:  J Clin Epidemiol       Date:  2020-07-10       Impact factor: 6.437

7.  A meta-analysis of procedures to change implicit measures.

Authors:  Patrick S Forscher; Calvin K Lai; Jordan R Axt; Charles R Ebersole; Michelle Herman; Patricia G Devine; Brian A Nosek
Journal:  J Pers Soc Psychol       Date:  2019-06-13

8.  A Bayesian approach to discrete multiple outcome network meta-analysis.

Authors:  Rebecca Graziani; Sergio Venturini
Journal:  PLoS One       Date:  2020-04-28       Impact factor: 3.240

9.  On evidence cycles in network meta-analysis.

Authors:  Lifeng Lin; Haitao Chu; James S Hodges
Journal:  Stat Interface       Date:  2020       Impact factor: 0.582

10.  Empirical evaluation of SUCRA-based treatment ranks in network meta-analysis: quantifying robustness using Cohen's kappa.

Authors:  Caitlin H Daly; Binod Neupane; Joseph Beyene; Lehana Thabane; Sharon E Straus; Jemila S Hamid
Journal:  BMJ Open       Date:  2019-09-05       Impact factor: 2.692

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