Literature DB >> 26062083

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

Georgia Salanti1.   

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. Copyright © 2012 John Wiley & Sons, Ltd.

Keywords:  assumptions; consistency; evidence‐based practice; systematic reviews; transitivity

Year:  2012        PMID: 26062083     DOI: 10.1002/jrsm.1037

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


  419 in total

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Review 2.  Indirect Comparisons and Network Meta-Analyses.

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Journal:  Oncol Nurs Forum       Date:  2020-07-01       Impact factor: 2.172

4.  Rapid network meta-analysis using data from Food and Drug Administration approval packages is feasible but with limitations.

Authors:  Lin Wang; Benjamin Rouse; Arielle Marks-Anglin; Rui Duan; Qiyuan Shi; Kevin Quach; Yong Chen; Christopher Cameron; Christopher H Schmid; Tianjing Li
Journal:  J Clin Epidemiol       Date:  2019-06-18       Impact factor: 6.437

5.  Relative Efficacy of Spironolactone, Eplerenone, and cAnRenone in patients with Chronic Heart failure (RESEARCH): a systematic review and network meta-analysis of randomized controlled trials.

Authors:  Lutz Frankenstein; Svenja Seide; Tobias Täger; Katrin Jensen; Hanna Fröhlich; Andrew L Clark; Mirjam Seiz; Hugo A Katus; Paul Nee; Lorenz Uhlmann; Huseyin Naci; Dan Atar
Journal:  Heart Fail Rev       Date:  2020-03       Impact factor: 4.214

Review 6.  SGLT2 inhibitors and risk of cancer in type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials.

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Journal:  Diabetologia       Date:  2017-07-19       Impact factor: 10.122

7.  Comparative effectiveness of interventions for managing postoperative catheter-related bladder discomfort: a systematic review and network meta-analysis.

Authors:  Min Hur; Sun-Kyung Park; Hyun-Kyu Yoon; Seokha Yoo; Hyung-Chul Lee; Won Ho Kim; Jin-Tae Kim; Ja Hyeon Ku; Jae-Hyon Bahk
Journal:  J Anesth       Date:  2019-01-02       Impact factor: 2.078

Review 8.  Comparative Effectiveness of Brief Alcohol Interventions for College Students: Results from a Network Meta-Analysis.

Authors:  Emily Alden Hennessy; Emily E Tanner-Smith; Dimitris Mavridis; Sean P Grant
Journal:  Prev Sci       Date:  2019-07

Review 9.  A scoping review and network meta-analysis for efficacy and safety of glaucoma medication in Japanese patients.

Authors:  Kenji Inoue; Kyoko Ishida; Goji Tomita; Hisashi Noma
Journal:  Jpn J Ophthalmol       Date:  2020-02-24       Impact factor: 2.447

10.  Citation of previous meta-analyses on the same topic: a clue to perpetuation of incorrect methods?

Authors:  Tianjing Li; Kay Dickersin
Journal:  Ophthalmology       Date:  2013-03-22       Impact factor: 12.079

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