Abstract
Systematic reviews and meta-analyses have long been fundamental tools for evidence-based clinical practice. Initially, meta-analyses were proposed as a technique that could improve the accuracy and the statistical power of previous research from individual studies with small sample size. However, one of its main limitations has been the fact of being able to compare no more than two treatments in an analysis, even when the clinical research question necessitates that we compare multiple interventions. Network meta-analysis (NMA) uses novel statistical methods that incorporate information from both direct and indirect treatment comparisons in a network of studies examining the effects of various competing treatments, estimating comparisons between many treatments in a single analysis. Despite its potential limitations, NMA applications in clinical epidemiology can be of great value in situations where there are several treatments that have been compared against a common comparator. Also, NMA can be relevant to a research or clinical question when many treatments must be considered or when there is a mix of both direct and indirect information in the body of evidence.