Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial
G Salanti, AE Ades, JPA Ioannidis - Journal of clinical epidemiology, 2011 - Elsevier
G Salanti, AE Ades, JPA Ioannidis
Journal of clinical epidemiology, 2011•ElsevierOBJECTIVE: To present some simple graphical and quantitative ways to assist interpretation
and improve presentation of results from multiple-treatment meta-analysis (MTM). STUDY
DESIGN AND SETTING: We reanalyze a published network of trials comparing various
antiplatelet interventions regarding the incidence of serious vascular events using Bayesian
approaches for random effects MTM, and we explore the advantages and drawbacks of
various traditional and new forms of quantitative displays and graphical presentations of …
and improve presentation of results from multiple-treatment meta-analysis (MTM). STUDY
DESIGN AND SETTING: We reanalyze a published network of trials comparing various
antiplatelet interventions regarding the incidence of serious vascular events using Bayesian
approaches for random effects MTM, and we explore the advantages and drawbacks of
various traditional and new forms of quantitative displays and graphical presentations of …
OBJECTIVE
To present some simple graphical and quantitative ways to assist interpretation and improve presentation of results from multiple-treatment meta-analysis (MTM).
STUDY DESIGN AND SETTING
We reanalyze a published network of trials comparing various antiplatelet interventions regarding the incidence of serious vascular events using Bayesian approaches for random effects MTM, and we explore the advantages and drawbacks of various traditional and new forms of quantitative displays and graphical presentations of results.
RESULTS
We present the results under various forms, conventionally based on the mean of the distribution of the effect sizes; based on predictions; based on ranking probabilities; and finally, based on probabilities to be within an acceptable range from a reference. We show how to obtain and present results on ranking of all treatments and how to appraise the overall ranks.
CONCLUSIONS
Bayesian methodology offers a multitude of ways to present results from MTM models, as it enables a natural and easy estimation of all measures based on probabilities, ranks, or predictions.
Elsevier