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Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview
Georgia Salanti1, A E Ades, John P A Ioannidis
1Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece. gsalanti@cc.uoi.gr
Journal of Clinical Epidemiology
|August 7, 2010
Summary
This study introduces simple graphical and quantitative methods to enhance the interpretation and presentation of multiple-treatment meta-analysis (MTM) results. Bayesian approaches offer flexible ways to display findings using probabilities, ranks, and predictions for better understanding.
Area of Science:
- Medical Statistics
- Evidence Synthesis
Background:
- Multiple-treatment meta-analysis (MTM) synthesizes evidence from complex networks of studies.
- Effective presentation of MTM results is crucial for informed decision-making.
Purpose of the Study:
- To propose accessible graphical and quantitative methods for interpreting and presenting MTM results.
- To improve the clarity and utility of findings from MTM.
Main Methods:
- Reanalysis of a published network of antiplatelet intervention trials using Bayesian random-effects MTM.
- Exploration of traditional and novel quantitative displays and graphical presentations.
Main Results:
- Results presented using effect size distributions, predictions, ranking probabilities, and probabilities relative to a reference.
- Methods demonstrated for obtaining and presenting treatment rankings and appraising overall ranks.
Conclusions:
- Bayesian methodology provides diverse options for presenting MTM results.
- Natural estimation of probability-based measures, ranks, and predictions enhances MTM interpretation.
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