Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Network meta-analysis: from key concepts to advanced methods
Time:
Sunday, 24/Aug/2025:
11:00am - 12:30pm
Location:Biozentrum U1.141
Biozentrum, 124 seats
Presentations
[Single Presentation of ID 116]: 1
Network meta-analysis: from key concepts to advanced methods
Virginia Chiocchia1, Konstantina Chalkou1, Orestis Efthimiou2, Tasnim Hamza1, Georgia Salanti1
1Institute of Social and Preventive Medicine, University of Bern, Switzerland; 2Institute of Primary Health Care (BIHAM), University of Bern, Switzerland
Network meta-analysis is an extension of pairwise meta-analysis that allows us to compare three or more interventions simultaneously, by combining direct and indirect evidence from a network of studies. Network meta-analysis can be used to estimate the relative treatmenteffects between any pair of interventions in the network, it increases precision compared to using only direct evidence, and it can produce a hierarchy of the interventions.
In the morning session of this full-day course we will demonstrate the assumptions and methods of network meta-analysis and network meta-regression with interactive lectures and practical exercise. In the afternoon we will introduce advanced topics in network meta-analysis, such as the use of individual participant data, component network meta-analysis for composite interventions, and dose-response analysis.
The course is designed for participants who are familiar with meta-analysis and Bayesian statistics. By the end of the course, participants will be able to:
Understand and assess the assumptions underlying the validity of indirect comparisonsand network meta-analysis
Estimate the relative treatment effects between any pair of interventions within a network of studies and present them in a transparent way
Assess and test for inconsistency within a network of interventions
Formulate a network meta-regression model and interpret the results and output
Obtain an overview of advanced methods and extensions in network meta-analysis
The practical exercises will be performed in the statistical software R.
