Conceptual and technical challenges in network meta-analysis

Ann Intern Med. 2013 Jul 16;159(2):130-7. doi: 10.7326/0003-4819-159-2-201307160-00008.


The increase in treatment options creates an urgent need for comparative effectiveness research. Randomized, controlled trials comparing several treatments are usually not feasible, so other methodological approaches are needed. Meta-analyses provide summary estimates of treatment effects by combining data from many studies. However, an important drawback is that standard meta-analyses can compare only 2 interventions at a time. A new meta-analytic technique, called network meta-analysis (or multiple treatments meta-analysis or mixed-treatment comparison), allows assessment of the relative effectiveness of several interventions, synthesizing evidence across a network of randomized trials. Despite the growing prevalence and influence of network meta-analysis in many fields of medicine, several issues need to be addressed when constructing one to avoid conclusions that are inaccurate, invalid, or not clearly justified. This article explores the scope and limitations of network meta-analysis and offers advice on dealing with heterogeneity, inconsistency, and potential sources of bias in the available evidence to increase awareness among physicians about some of the challenges in interpretation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bias
  • Comparative Effectiveness Research / methods
  • Comparative Effectiveness Research / standards
  • Comparative Effectiveness Research / statistics & numerical data
  • Humans
  • Meta-Analysis as Topic*