Network meta-analysis: application and practice using Stata

Abstract

This review aimed to arrange the concepts of a network meta-analysis (NMA) and to demonstrate the analytical process of NMA using Stata software under frequentist framework. The NMA tries to synthesize evidences for a decision making by evaluating the comparative effectiveness of more than two alternative interventions for the same condition. Before conducting a NMA, 3 major assumptions—similarity, transitivity, and consistency—should be checked. The statistical analysis consists of 5 steps. The first step is to draw a network geometry to provide an overview of the network relationship. The second step checks the assumption of consistency. The third step is to make the network forest plot or interval plot in order to illustrate the summary size of comparative effectiveness among various interventions. The fourth step calculates cumulative rankings for identifying superiority among interventions. The last step evaluates publication bias or effect modifiers for a valid inference from results. The synthesized evidences through five steps would be very useful to evidence-based decision-making in healthcare. Thus, NMA should be activated in order to guarantee the quality of healthcare system.

Comparative Efficacy of Targeted Therapies in Patients with Non-Small Cell Lung Cancer: A Network Meta-Analysis of Clinical Trials

“…We measured inconsistency, which implies statistical disagreement between direct and indirect comparisons [12,13]. The generalized linear model was applied for the Bayesian NMA [14].…”

The vaginal microbiota, human papillomavirus and cervical dysplasia: a systematic review and network meta‐analysis

“…The cumulative proportions of the different CSTs in each study were pooled and weighted, and presented as percentages. To enable direct and indirect comparisons between all CSTs, we used a fixed network meta‐analysis approach, and a classic pairwise meta‐analysis to validate the results and explore heterogeneity (see Supplementary material, Appendix S1).…”

Medications to reduce emergence coughing after general anaesthesia with tracheal intubation: a systematic review and network meta-analysis

“…We performed statistical significance tests for global and local loop inconsistency using the STATA commands network meta inconsistency and network sidesplit all respectively, whereby a P-value of <0.05 may potentially indicate significant inconsistency. 31 A surface under the cumulative ranking curve analysis (SUCRA) generated cumulative ranking values between 0% and 100%, with values closer to 100% indicating a greater cumulative likelihood that the treatment was a higher rank. The SUCRA value is relative and conditional on the treatments being compared.…”