• Holger J Schünemann, Carlos Cuello, Elie A Akl, Reem A Mustafa, Jörg J Meerpohl, Kris Thayer, Rebecca L Morgan, Gerald Gartlehner, Regina Kunz, S Vittal Katikireddi, Jonathan Sterne, Julian Pt Higgins, Gordon Guyatt, and GRADE Working Group.
• Department of Health Research Methods, Evidence, and Impact and McGRADE Center, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S4K1, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S4K1, Canada. Electronic address: schuneh@mcmaster.ca.
• J Clin Epidemiol. 2019 Jul 1; 111: 105-114.

ObjectiveTo 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 SettingThe 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.ResultsWe 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.ConclusionsThe 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.Copyright © 2018 Elsevier Inc. All rights reserved.

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