Description of network meta-analysis geometry: A metrics design study

PLoS One. 2019 Feb 20;14(2):e0212650. doi: 10.1371/journal.pone.0212650. eCollection 2019.

Abstract

Background: The conduction and report of network meta-analysis (NMA), including the presentation of the network-plot, should be transparent. We aimed to propose metrics adapted from graph theory and social network-analysis literature to numerically describe NMA geometry.

Methods: A previous systematic review of NMAs of pharmacological interventions was performed. Data on the graph's presentation were collected. Network-plots were reproduced using Gephi 0.9.1. Eleven geometric metrics were tested. The Spearman test for non-parametric correlation analyses and the Bland-Altman and Lin's Concordance tests were performed (IBM SPSS Statistics 24.0).

Results: From the 477 identified NMAs only 167 graphs could be reproduced because they provided enough information on the plot characteristics. The median nodes and edges were 8 (IQR 6-11) and 10 (IQR 6-16), respectively, with 22 included studies (IQR 13-35). Metrics such as density (median 0.39, ranged 0.07-1.00), median thickness (2.0, IQR 1.0-3.0), percentages of common comparators (median 68%), and strong edges (median 53%) were found to contribute to the description of NMA geometry. Mean thickness, average weighted degree and average path length produced similar results than other metrics, but they can lead to misleading conclusions.

Conclusions: We suggest the incorporation of seven simple metrics to report NMA geometry. Editors and peer-reviews should ensure that guidelines for NMA report are strictly followed before publication.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bibliometrics
  • Data Mining
  • Databases, Bibliographic
  • Humans
  • Network Meta-Analysis*
  • Publishing

Grants and funding

FST was supported by the Brazilian National Council of Technological and Scientific Development (CNPq), and the Coordination for the Improvement of Higher Education Personnel (CAPES). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.