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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. Step 3 Study Data & Results. Step 1 Basic Study Design. Step 2
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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
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
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
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
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
3 Main dimensions of Quality Weak STRENGTH OF ASSOCIATION Strong Indirect DIRECTNESS Direct Poor DESIGN & METHODS Good
Quality of Evidence: dimensionsExample: likely publication bias and indirectness
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