• Johannes Morche, Simone Freitag, Frauke Hoffmann, Olesja Rissling, Gero Langer, Barbara Nußbaumer-Streit, Ingrid Toews, Gerald Gartlehner, and Jörg J Meerpohl.
• Abteilung Fachberatung Medizin. Gemeinsamer Bundesausschuss, Berlin, Deutschland. Electronic address: johannes.morche@g-ba.de.
• Z Evid Fortbild Qual Gesundhwes. 2020 Apr 1; 150-152: 124-133.

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.ConclusionThe 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 © 2020. Published by Elsevier GmbH.

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