Literature DB >> 23856683

Conceptual and technical challenges in network meta-analysis.

Andrea Cipriani1, Julian P T Higgins, John R Geddes, Georgia Salanti.   

Abstract

The increase in treatment options creates an urgent need for comparative effectiveness research. Randomized, controlled trials comparing several treatments are usually not feasible, so other methodological approaches are needed. Meta-analyses provide summary estimates of treatment effects by combining data from many studies. However, an important drawback is that standard meta-analyses can compare only 2 interventions at a time. A new meta-analytic technique, called network meta-analysis (or multiple treatments meta-analysis or mixed-treatment comparison), allows assessment of the relative effectiveness of several interventions, synthesizing evidence across a network of randomized trials. Despite the growing prevalence and influence of network meta-analysis in many fields of medicine, several issues need to be addressed when constructing one to avoid conclusions that are inaccurate, invalid, or not clearly justified. This article explores the scope and limitations of network meta-analysis and offers advice on dealing with heterogeneity, inconsistency, and potential sources of bias in the available evidence to increase awareness among physicians about some of the challenges in interpretation.

Mesh:

Year:  2013        PMID: 23856683     DOI: 10.7326/0003-4819-159-2-201307160-00008

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  278 in total

1.  A tool for empirical equipoise assessment in multigroup comparative effectiveness research.

Authors:  Kazuki Yoshida; Daniel H Solomon; Sebastien Haneuse; Seoyoung C Kim; Elisabetta Patorno; Sara K Tedeschi; Houchen Lyu; Sonia Hernández-Díaz; Robert J Glynn
Journal:  Pharmacoepidemiol Drug Saf       Date:  2019-05-27       Impact factor: 2.890

Review 2.  Maximizing response to first-line antipsychotics in schizophrenia: a review focused on finding from meta-analysis.

Authors:  Robert C Smith; Stefan Leucht; John M Davis
Journal:  Psychopharmacology (Berl)       Date:  2018-11-30       Impact factor: 4.530

Review 3.  Dressings and topical agents for treating pressure ulcers.

Authors:  Maggie J Westby; Jo C Dumville; Marta O Soares; Nikki Stubbs; Gill Norman
Journal:  Cochrane Database Syst Rev       Date:  2017-06-22

Review 4.  Modified triple Kessler with least risk of elongation among Achilles tendon repair techniques: a systematic review and network meta-analysis of human cadaveric studies.

Authors:  Pedro Diniz; Jácome Pacheco; Ricardo M Fernandes; Hélder Pereira; Frederico Castelo Ferreira; Gino M M J Kerkhoffs
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2021-06-05       Impact factor: 4.342

5.  Lack of evidence to favor specific preventive interventions in psychosis: a network meta-analysis.

Authors:  Cathy Davies; Andrea Cipriani; John P A Ioannidis; Joaquim Radua; Daniel Stahl; Umberto Provenzani; Philip McGuire; Paolo Fusar-Poli
Journal:  World Psychiatry       Date:  2018-06       Impact factor: 49.548

6.  Comparative efficacy of drugs for treating giardiasis: a systematic update of the literature and network meta-analysis of randomized clinical trials.

Authors:  José M Ordóñez-Mena; Noel D McCarthy; Thomas R Fanshawe
Journal:  J Antimicrob Chemother       Date:  2018-03-01       Impact factor: 5.790

7.  Network Meta-analysis: Users' Guide for Surgeons: Part II - Certainty.

Authors:  Harman Chaudhry; Clary J Foote; Gordon Guyatt; Lehana Thabane; Toshi A Furukawa; Brad Petrisor; Mohit Bhandari
Journal:  Clin Orthop Relat Res       Date:  2015-04-14       Impact factor: 4.176

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

9.  Is It Necessary to Perform the Pharmacological Interventions for Intrahepatic Cholestasis of Pregnancy? A Bayesian Network Meta-Analysis.

Authors:  Yi Shen; Jie Zhou; Sheng Zhang; Xu-Lin Wang; Yu-Long Jia; Shu He; Yuan-Yuan Wang; Wen-Chao Li; Jian-Guo Shao; Xun Zhuang; Yuan-Lin Liu; Gang Qin
Journal:  Clin Drug Investig       Date:  2019-01       Impact factor: 2.859

10.  A CD-based mapping method for combining multiple related parameters from heterogeneous intervention trials.

Authors:  Yang Jiao; Eun-Young Mun; Thomas A Trikalinos; Minge Xie
Journal:  Stat Interface       Date:  2020       Impact factor: 0.582

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