Understanding Network Meta-analysis (NMA) Conclusions Requires Scrutiny of Methods and Results: Introduction to NMA and the Geometry of Evidence

Synthesis of medical literature to determine the best treatment for a given problem is challenging, particularly when multiple options exist. Network meta-analysis (NMA) allows the comparison of different treatment approaches in a single, systematic review including treatments that have never been compared head-to-head. A key to understanding NMA is to focus on the network geometry showing the number of included studies and their relationships: different treatment options are illustrated as nodes. Lines between nodes represent direct comparisons. For nodes not directly compared, indirect effects may be determined by use of the property of transitivity. Limitations of NMA include heterogeneity, where variability among included studies biases pairwise comparisons, and consistency, if direct and indirect comparisons between treatments do not agree. In the end, NMA allows numeric ranking of the estimated effects of each treatment from most to least effective. A disadvantage of NMA ranking methods is that readers may focus overly on what treatment ranks best and focus insufficiently on the methods and results that determine the rankings. The reliability of the rankings requires consideration of the geometry and strength of the network, including evaluation of heterogeneity, consistency, and transitivity. The conclusion of an NMA requires scrutiny of the methods and results.

Automated summary

Network meta-analysis (NMA) allows comparison of different treatment approaches by assessing their relationships to determine effect rankings. However, limitations such as heterogeneity and consistency exist, requiring evaluation of the network's geometry and strength.