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GRADE guidelines: 1. Introduction—GRADE evidence profiles and summary of findings tables

Journal of Clinical EpidemiologyPublished 4 January 2011
Gordon Guyatt, Andrew D Oxman, Elie A. Akl, Regina Kunz, Gunn Elisabeth Vist, Jan Brożek
Citations10,460
SJR quartileQ1
SJR score3.15
SNIP2.66

TL;DR

The GRADE process begins with asking an explicit question, including specification of all important outcomes, and provides explicit criteria for rating the quality of evidence that include study design, risk of bias, imprecision, inconsistency, indirectness, and magnitude of effect.

Abstract

This article is the first of a series providing guidance for use of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system of rating quality of evidence and grading strength of recommendations in systematic reviews, health technology assessments (HTAs), and clinical practice guidelines addressing alternative management options. The GRADE process begins with asking an explicit question, including specification of all important outcomes. After the evidence is collected and summarized, GRADE provides explicit criteria for rating the quality of evidence that include study design, risk of bias, imprecision, inconsistency, indirectness, and magnitude of effect. Recommendations are characterized as strong or weak (alternative terms conditional or discretionary) according to the quality of the supporting evidence and the balance between desirable and undesirable consequences of the alternative management options. GRADE suggests summarizing evidence in succinct, transparent, and informative summary of findings tables that show the quality of evidence and the magnitude of relative and absolute effects for each important outcome and/or as evidence profiles that provide, in addition, detailed information about the reason for the quality of evidence rating. Subsequent articles in this series will address GRADE's approach to formulating questions, assessing quality of evidence, and developing recommendations.

Keywords

Decision SciencesMedicineEconomics, Econometrics and Finance