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GRADE approach to drawing conclusions from a network meta-analysis using a minimally contextualised framework

  • Romina Brignardello-Petersen
  • , Ivan D. Florez
  • , Ariel Izcovich
  • , Nancy Santesso
  • , Glen Hazlewood
  • , Waleed Alhazanni
  • , Juan José Yepes-Nuñez
  • , George Tomlinson
  • , Holger J. Schünemann
  • , Gordon H. Guyatt
  • McMaster University
  • Universidad de Antioquia
  • Hospital Alemán
  • University of Calgary
  • Universidad de los Andes Colombia
  • University of Toronto
  • Toronto Hospital

Research output: Contribution to journalArticlepeer-review

246 Scopus citations

Abstract

This article describes GRADE (grading of recommendations assessment, development and evaluation) guidance on how to draw conclusions from a network meta-analysis of interventions that includes individual randomised controlled trials addressing a single outcome. The guidance uses a minimally contextualised approach that avoids value judgments regarding the magnitude of intervention effects. The framework is based on two principles: interventions should be grouped in categories, from the most to the least effective or harmful; and the judgments that place interventions in such categories should simultaneously consider the estimates of effect, the certainty of the evidence, and the rankings. The framework includes five steps, which we describe and illustrate using an example. The framework is simple, methodologically sound, and flexible, allowing for modifications to resolve situations in which additional complexity or value judgments might be appropriate.

Original languageEnglish
Article numberm3900
JournalBMJ
Volume371
DOIs
StatePublished - Nov 11 2020

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