- Tuesday, February 12th 2019 at 16:00 - 17:00 UK (Other timezones)
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Background: A quantitative synthesis of evidence via standard pair-wise meta-analysis lies on the top of the hierarchy for evaluating the relative effectiveness or safety between two interventions. In most healthcare problems, however, there is a plethora of competing interventions. Network meta-analysis allows to rank competing interventions and evaluate their relative effectiveness even if they have not been compared in an individual trial.
Aim: The aim of this presentation is to explain and discuss the main features of this statistical technique (key assumptions underlying network meta-analysis and graphical methods to visualise results and information in the network).
Methods: We will use one illustrative example that compared the relative effectiveness of 21 antidepressants and placebo in major depression.
Results: A network plot allows to visualise how information flows in the network and reveals important information about network geometry. Discrepancies between direct and indirect evidence can be detected using inconsistency plots. Relative effectiveness or safety of competing interventions can be presented in a league table. A contribution plot reveals the contribution of each direct comparison to each network estimate. A comparison-adjusted funnel plot is an extension of simple funnel plot to network meta-analysis. A rank probability matrix can be estimated to present the probabilities of all interventions assuming each rank and can be represented using rankograms and cumulative probability plots.
Conclusions: Network meta-analysis is very helpful in comparing the relative effectiveness and acceptability of competing treatments. Several issues, however, still need to be addressed when conducting a network meta-analysis for the results to be valid and correctly interpreted.
Prof. Andrea Cipriani
Associate Professor, Department of Psychiatry, University of Oxford
Honorary Consultant Psychiatrist, Oxford Health NHS Foundation Trust, Oxford
Associate Director, R&D, Oxford Health NHS Foundation Trust, Oxford