Network Meta-Analysis

Thursday, June 14, 2018 - Friday, June 15, 2018 8:30 AM - 12:30 PM

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Course Description

Traditional meta-analytical methods commonly used for synthesizing evidence from clinical trials are limited in comparing two interventions at a time. However, for any given condition there is usually a plethora of alternative treatment options. This situation has motivated the development of network meta-analysis which is an extension of conventional meta-analysis that allows the simultaneous synthesis of data from networks of trials. By combining direct and indirect information, network meta-analysis can inform every possible treatment comparison, even those for which no head-to-head trials exist.


This course will focus on the role of network meta-analyses in comparative effectiveness research. We will examine the statistical methods and methodological aspects involved, the assumptions underlying the method and the potential sources of bias that can invalidate the results. Finally, we will discuss methods for reporting and critically appraising the results from network meta-analyses.

Course Objectives

By the end of the course, participants will be able to:

  1. Understand the concept and principles of network meta-analysis
  2. Describe and the different steps of conducting a network meta-analysis of (framing question, forming the network, evaluating the assumptions, synthesizing evidence, interpreting findings)
  3. To synthesize the data from a network of trials using Stata
  4. Interpret the results of a network meta-analysis
  5. Identify the limitations and potential sources of bias
  6. Critically appraise the results from a meta-analysis and know the reporting guidelines in this field (PRISMA extension)


Some previous experience with systematic reviews and meta-analyses and basic knowledge of statistics is required for all participants. Basic knowledge of Stata is also desirable. All participants should bring a laptop, with Stata software installed (version 13 or a more recent version).

Course Reading List


Mavridis D, Giannatsi M, Cipriani A, Salanti G. 2015. A Primer on Network Meta-Analysis with Emphasis on Mental Health. Evidence-Based Mental Health 18:40–46.


Caldwell DM, Ades AE, Higgins JP. 2005. Simultaneous Comparison of Multiple Treatments: Combining Direct and Indirect Evidence. BMJ 331: 897–900.


Cipriani A, Higgins JP, Geddes JR, Salanti G. 2013. Conceptual and Technical Challenges in Network Meta-Analysis. Ann Intern Med. 159: 130–37.


Salanti G. 2012. Indirect and Mixed-Treatment Comparison, Network, or Multiple-Treatments Meta-Analysis: Many Names, Many Benefits, Many Concerns for the next Generation Evidence Synthesis Tool. Res Synth Meth 3 (2): 80–97.


Chaimani A, Higgins JPT, Mavridis D, Spyridonos P, Salanti G. 2013. Graphical Tools for Network Meta-Analysis in STATA. PLoS.One. 8 (10): e76654.



Anna Chaimani

Anna Chaimani is a Junior Chair at Paris Descartes University. She studied mathematics and then obtained a MSc in Biostatistics from the University of Athens in 2011 and a PhD in Epidemiology from the University of Ioannina School of Medicine, Greece in 2014. Her research interests focus on methodology for pairwise and network meta-analysis. She has worked on models for small-study effects for network meta-analysis and network meta-epidemiological models. She also works on software development for meta-analysis and she is the author of the network graphs package in Stata. She is a close collaborator of the Comparing Multiple Interventions Methods Group of The Cochrane Collaboration and has worked on the incorporation of network meta-analysis in Cochrane Reviews including the preparation of a new chapter for network meta-analysis in the Cochrane Handbook for Systematic Reviews of Interventions. She has published to date 25 peer-reviewed articles indexed in PubMed.

Course Fee

Registration for this course is $400.00


The registration period has closed for this event.


Hammer LL107

Hammer Health Sciences Building
701 West 168th Street
New York, NY 10032

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