Literature DB >> 28603010

Deficiencies in addressing effect modification in network meta-analyses: a meta-epidemiological survey.

Bruno Kovic1, Michael J Zoratti2, Steven Michalopoulos2, Camila Silvestre3, Kristian Thorlund4, Lehana Thabane5.   

Abstract

OBJECTIVE: The objectives of this study were to evaluate the current state of reporting and handling of effect modification in network meta-analyses (NMAs) and perform exploratory analyses to identify variables that are potentially associated with incomplete reporting of effect modifiers in NMAs. STUDY DESIGN AND
SETTING: We conducted a meta-epidemiological survey using a systematic review of NMAs published in 2013 and identified through MEDLINE and Embase databases.
RESULTS: The review identified 77 NMAs. The most common type of effect modifiers identified and explored were patient characteristics (50.7% or 39/77), and the most common adjustment method used was sensitivity analysis (51.7% or 30/58). Over 45% (35/77) of studies did not describe a plan, nearly 40% (30/77) did not report the results of analyses, and approximately 47% (36/77) of studies had incomplete reporting. Exploratory univariate regression analyses yielded a statistically significant association for the variables of journal impact factor, ratio of randomized controlled trials to number of comparisons, and total number of randomized controlled trials.
CONCLUSION: Current reporting practices are largely deficient, given that almost half of identified published NMAs do not explore or report effect modification. Journal impact factor and amount of available information in a network were associated with completeness of reporting.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Effect modifier; Heterogeneity; Indirect treatment comparisons; Meta-epidemiological survey; Methodology; Network meta-analysis; Systematic literature review

Mesh:

Year:  2017        PMID: 28603010     DOI: 10.1016/j.jclinepi.2017.06.004

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  4 in total

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Authors:  Daeria O Lawson; Alvin Leenus; Lawrence Mbuagbaw
Journal:  Pilot Feasibility Stud       Date:  2020-01-30

2.  Patient characteristics as effect modifiers for psoriasis biologic treatment response: an assessment using network meta-analysis subgroups.

Authors:  Ros Wade; Sahar Sharif-Hurst; Sofia Dias
Journal:  Syst Rev       Date:  2020-06-05

3.  BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses.

Authors:  Audrey Béliveau; Devon J Boyne; Justin Slater; Darren Brenner; Paul Arora
Journal:  BMC Med Res Methodol       Date:  2019-10-22       Impact factor: 4.615

4.  When does the use of individual patient data in network meta-analysis make a difference? A simulation study.

Authors:  Steve Kanters; Mohammad Ehsanul Karim; Kristian Thorlund; Aslam Anis; Nick Bansback
Journal:  BMC Med Res Methodol       Date:  2021-01-13       Impact factor: 4.615

  4 in total

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