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GRADE guidelines: 12. Preparing summary of findings tables-binary outcomes
Gordon H Guyatt1, Andrew D Oxman, Nancy Santesso
1Department of Clinical Epidemiology and Biostatistics, McMaster University, West Hamilton, Ontario L8N 3Z5, Canada. guyatt@mcmaster.ca
Journal of Clinical Epidemiology
|May 22, 2012
Summary
Summary of Findings (SoF) tables guide evidence-based decisions by detailing study numbers, participant counts, evidence quality, and effect estimates. These tables help interpret treatment effects using direct or surrogate evidence, and compare randomized trials with observational studies.
Area of Science:
- Evidence-based medicine
- Systematic reviews
- Clinical decision-making
Background:
- Summary of Findings (SoF) tables are crucial for synthesizing evidence.
- They present key information on study characteristics, quality, and treatment effects.
- Challenges include selecting direct vs. indirect evidence and comparing different study designs.
Purpose of the Study:
- To outline the structure and content of Summary of Findings (SoF) tables.
- To discuss the choices and challenges in preparing these tables for clinical use.
- To provide guidance on presenting effect estimates and handling uncertainty.
Main Methods:
- SoF tables summarize data for up to seven key outcomes.
- They include the number of studies and participants, quality of evidence, and effect estimates.
- Relative risks (RRs) are preferred for binary outcomes, with absolute risks derived from baseline risks.
Main Results:
- SoF tables present direct or surrogate evidence, comparing randomized trials with observational studies.
- They address choices in evidence selection and handling discrepant results.
- Methods for presenting absolute and relative effects, including handling non-significant findings, are detailed.
Conclusions:
- SoF tables provide a comprehensive overview of evidence for patient-important outcomes.
- Careful consideration of evidence sources and presentation methods is essential for accurate interpretation.
- These tables support informed clinical decision-making by clearly communicating treatment effect uncertainties.
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