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

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Tonin, FS (Author) Other; Borba, HH (Author) Other; Mendes, AM (Author) Other; Wiens, A (Author) Other; Fernandez Llimos, F (Author) Other; Pontarolo, R (Author) Other

Journal

Title: PLoS ONE

Vol. 14

ISSN: 1932-6203

Publisher: Public Library of Science

Indexing

ISI Web of Knowledge - 39 Citations

Scopus - 35 Citations

Other information

Authenticus ID: P-00Q-8C3

DOI: 10.1371/journal.pone.0212650

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14