Graphical tools for visualizing the results of network meta-analysis of multicomponent interventions

Georgios Seitidis*, Sofia Tsokani, Christos Christogiannis, Katerina Maria Kontouli, Alexandros Fyraridis, Stavros Nikolakopoulos, Areti Angeliki Veroniki, Dimitris Mavridis

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Network meta-analysis (NMA) is an established method for assessing the comparative efficacy and safety of competing interventions. It is often the case that we deal with interventions that consist of multiple, possibly interacting, components. Examples of interventions' components include characteristics of the intervention, mode (face-to-face, remotely etc.), location (hospital, home etc.), provider (physician, nurse etc.), time of communication (synchronous, asynchronous etc.) and other context related components. Networks of multicomponent interventions are typically sparse and classical NMA inference is not straightforward and prone to confounding. Ideally, we would like to disentangle the effect of each component to find out what works (or does not work). To this aim, we propose novel ways of visualizing the NMA results, describe their use, and illustrate their application in real-life examples. We developed an R package viscomp to produce all the suggested figures.

Original languageEnglish
Article numberdoi.org/10.1002/jrsm.1617
Pages (from-to)382-395
Number of pages14
JournalResearch Synthesis Methods
Volume14
Issue number3
DOIs
Publication statusPublished - May 2023

Keywords

  • multicomponent
  • network meta-analysis
  • sparse network
  • transitivity
  • visualization

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