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GRADing Evidence

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This document provides a comprehensive guide to the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) process, aimed at those unfamiliar with its application. It discusses key steps in grading evidence, including study design, methods appraisal, and understanding results. The guide outlines criteria for upgrading and downgrading evidence based on features like association strength and bias. Specific examples highlight practical applications of GRADE, including randomized trials and observational studies, emphasizing the importance of quality dimensions in evaluating evidence.

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GRADing Evidence

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  1. GRADing Evidence • Explaining the GRADE process to those who don’t do GRADing • Some attempts at Figures • 1 & 2 = current Figures • 3 = generic • 4 & 5 specific examples • 6 = some “dimensions” of evidence • 7 = size vs bias

  2. Step 3 Study Data & Results Step 1 Basic Study Design Step 2 Appraisal of Study Methods High Randomised trials Moderate • Upgrade if: • Strong Association • Dose Response • Downgrade if: • Serious Limitations • Indirect outcome Low Observational studies • Downgrade if: • Sparse data • Important inconsistency Very Low

  3. Example 1: GRADing of small, poor quality randomized trial(s) Step 3 Study Data & Results Step 1 Basic Study Design Step 2 Appraisal of Study Methods High Randomised trials • Downgrade for: • Serious Limitations Moderate Low Observational studies • Downgrade for: • Sparse data Very Low

  4. Example 2: GRADing of a high quality cohort study with a strong effect, dose-response gradient and no plausible confounders Step 3 Study Data & Results Step 1 Basic Study Design Step 2 Appraisal of Study Methods High Randomised trials Moderate • Upgrade for: • Strong Association & • Dose Response Low Observational studies Very Low

  5. Example 1: GRADing of small, poor quality randomized trial(s) Step 2 Study Methods Step 3 Study Results Step 1 Basic Study Design High Randomised trial • Downgrade for • Serious Limitations Moderate • Downgrade for: • Sparse data Low Observational studies Very Low

  6. 3 Main dimensions of Quality Weak STRENGTH OF ASSOCIATION Strong Indirect DIRECTNESS Direct Poor DESIGN & METHODS Good

  7. Quality of Evidence: dimensionsExample: likely publication bias and indirectness

  8. Could bias explain the size of effect? Range of bias* could explain effect * Non-randomised studies; serious limitation in study; reporting bias Range of bias cannot explain effect

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