GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence

GRADE Working Group

Research output: Contribution to journalArticle (Academic Journal)

51 Citations (Scopus)
274 Downloads (Pure)

Abstract

Objective: To provide guidance on how systematic review authors, guideline developers, and health technology assessment practitioners should approach the use of the risk of bias in nonrandomized studies of interventions (ROBINS-I) tool as a part of GRADE's certainty rating process. Study Design and Setting: The study design and setting comprised iterative discussions, testing in systematic reviews, and presentation at GRADE working group meetings with feedback from the GRADE working group. Results: We describe where to start the initial assessment of a body of evidence with the use of ROBINS-I and where one would anticipate the final rating would end up. The GRADE accounted for issues that mitigate concerns about confounding and selection bias by introducing the upgrading domains: large effects, dose-effect relations, and when plausible residual confounders or other biases increase certainty. They will need to be considered in an assessment of a body of evidence when using ROBINS-I. Conclusions: The use of ROBINS-I in GRADE assessments may allow for a better comparison of evidence from randomized controlled trials (RCTs) and nonrandomized studies (NRSs) because they are placed on a common metric for risk of bias. Challenges remain, including appropriate presentation of evidence from RCTs and NRSs for decision-making and how to optimally integrate RCTs and NRSs in an evidence assessment.

Original languageEnglish
Pages (from-to)105-114
Number of pages10
JournalJournal of Clinical Epidemiology
Volume111
Early online date9 Feb 2018
DOIs
Publication statusPublished - 1 Jul 2019

Bibliographical note

Copyright © 2018 Elsevier Inc. All rights reserved.

Keywords

  • Certainty of the evidence
  • GRADE
  • Nonrandomized studies
  • Quality of evidence
  • Risk of bias
  • ROBINS

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