GRADE Guidelines 30: the GRADE approach to assessing the certainty of modeled evidence—An overview in the context of health decision-making

dc.contributor.authorBrožek, Jan L.
dc.contributor.authorCanelo-Aybar, Carlos Gilberto
dc.contributor.authorAkl, Elie A.
dc.contributor.authorBowen, James M.
dc.contributor.authorBucher, John R.
dc.contributor.authorChiu, Weihsueh A.
dc.contributor.authorCronin, Mark T.D.
dc.contributor.authorDjulbegović, Benjamin J.
dc.contributor.authorFalavigna, Maicon
dc.contributor.authorGordon, Guyatt H.
dc.contributor.authorGordon, Ami A.
dc.contributor.authorHilton Boon, Michele
dc.contributor.authorHutubessy, Raymond Christiaan W.
dc.contributor.authorJoore, Manuela A.
dc.contributor.authorVittal Katikireddi, S. Vittal
dc.contributor.authorLaKind, Judy S.
dc.contributor.authorLangendam, Miranda W.
dc.contributor.authorManja, Veena
dc.contributor.authorMagnuson, Kristen L.
dc.contributor.authorMathioudakis, Alexander G.
dc.contributor.authorMeerpohl, Joerg J.
dc.contributor.authorMertz, Dominik P.
dc.contributor.authorMezencev, Roman
dc.contributor.authorMorgan, Rebecca L.
dc.contributor.authorMorgano, Gian Paolo
dc.contributor.authorMustafa, Reem A.
dc.contributor.authorO'Flaherty, M. Enrique
dc.contributor.authorPatlewicz, Grace Y.
dc.contributor.authorRiva, John Joseph
dc.contributor.authorPosso, Margarita C.
dc.contributor.authorRooney, Andrew A.
dc.contributor.authorSchlosser, Paul M.
dc.contributor.authorSchwartz, Lisa Jennifer
dc.contributor.authorShemilt, Ian
dc.contributor.authorTarride, Jean Eric
dc.contributor.authorThayer, Kristina A.
dc.contributor.authorTsaioun, Katya I.
dc.contributor.authorVale, Luke David
dc.contributor.authorWambaugh, John
dc.contributor.authorWignall, Jessica A.
dc.contributor.authorWilliams, Ashley R.
dc.contributor.authorXie, Feng
dc.contributor.authorZhang, Yuan
dc.contributor.authorSchunëmann, Holger J.
dc.contributor.departmentInternal Medicine
dc.contributor.facultyFaculty of Medicine (FM)
dc.contributor.institutionAmerican University of Beirut
dc.date.accessioned2025-01-24T12:02:07Z
dc.date.available2025-01-24T12:02:07Z
dc.date.issued2021
dc.description.abstractObjectives: The objective of the study is to present the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) conceptual approach to the assessment of certainty of evidence from modeling studies (i.e., certainty associated with model outputs). Study Design and Setting: Expert consultations and an international multidisciplinary workshop informed development of a conceptual approach to assessing the certainty of evidence from models within the context of systematic reviews, health technology assessments, and health care decisions. The discussions also clarified selected concepts and terminology used in the GRADE approach and by the modeling community. Feedback from experts in a broad range of modeling and health care disciplines addressed the content validity of the approach. Results: Workshop participants agreed that the domains determining the certainty of evidence previously identified in the GRADE approach (risk of bias, indirectness, inconsistency, imprecision, reporting bias, magnitude of an effect, dose–response relation, and the direction of residual confounding) also apply when assessing the certainty of evidence from models. The assessment depends on the nature of model inputs and the model itself and on whether one is evaluating evidence from a single model or multiple models. We propose a framework for selecting the best available evidence from models: 1) developing de novo, a model specific to the situation of interest, 2) identifying an existing model, the outputs of which provide the highest certainty evidence for the situation of interest, either “off-the-shelf” or after adaptation, and 3) using outputs from multiple models. We also present a summary of preferred terminology to facilitate communication among modeling and health care disciplines. Conclusion: This conceptual GRADE approach provides a framework for using evidence from models in health decision-making and the assessment of certainty of evidence from a model or models. The GRADE Working Group and the modeling community are currently developing the detailed methods and related guidance for assessing specific domains determining the certainty of evidence from models across health care–related disciplines (e.g., therapeutic decision-making, toxicology, environmental health, and health economics). © 2020
dc.identifier.doihttps://doi.org/10.1016/j.jclinepi.2020.09.018
dc.identifier.eid2-s2.0-85093682805
dc.identifier.pmid32980429
dc.identifier.urihttp://hdl.handle.net/10938/31477
dc.language.isoen
dc.publisherElsevier Inc.
dc.relation.ispartofJournal of Clinical Epidemiology
dc.sourceScopus
dc.subjectCertainty of evidence
dc.subjectGrade
dc.subjectGuidelines
dc.subjectHealth care decision making
dc.subjectMathematical models
dc.subjectModelling studies
dc.subjectClinical decision-making
dc.subjectEvidence-based medicine
dc.subjectGrade approach
dc.subjectHumans
dc.subjectInterdisciplinary communication
dc.subjectProfessional competence
dc.subjectPublication bias
dc.subjectSystematic reviews as topic
dc.subjectTechnology assessment, biomedical
dc.subjectAdult
dc.subjectArticle
dc.subjectBiomedical technology assessment
dc.subjectConsultation
dc.subjectContent validity
dc.subjectDecision making
dc.subjectDose response
dc.subjectEnvironmental health
dc.subjectFemale
dc.subjectHealth economics
dc.subjectHuman
dc.subjectMale
dc.subjectNomenclature
dc.subjectPractice guideline
dc.subjectReporting bias
dc.subjectRisk assessment
dc.subjectSystematic review
dc.subjectToxicology
dc.subjectClinical decision making
dc.subjectEvidence based medicine
dc.subjectOrganization and management
dc.subjectProcedures
dc.subjectPublishing
dc.titleGRADE Guidelines 30: the GRADE approach to assessing the certainty of modeled evidence—An overview in the context of health decision-making
dc.typeArticle

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