Furthermore, ‘PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Network Meta-Analysis checklist’, as a guideline for reporting NMA research outcomes, was also developed. In 2011, the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) defined the concepts related to NMA and established guidelines relating to methodological and statistical issues to help researchers conduct NMA in a valid manner. įrom 2008 onwards, the number of publications based on NMA increased at a rapid pace. Since then, many methodological developments have taken place, and articles introducing SAS ( ) and Stata ( ) program commands have been presented. proposed an NMA approach based on the frequentist framework using random-effects models. However, if the prior probability is not established in the study hypothesis, Bayesian analysis poses many limitations for ordinary researchers using NMA because the problem of establishing prior probability is rather more complex than the problem of testing the research hypothesis, that is, the original purpose of the analysis. Because part of NMA has indirect, multiple comparisons, Bayesian framework seems logically more valid, and 60-70% of NMA studies have taken a Bayesian approach. Statistical approaches to NMA are largely classified as frequentist and Bayesian frameworks. Accordingly, an analytic approach called network meta-analysis (NMA) was developed to include in the meta-analysis not only direct comparisons, but also indirect comparisons based on logical inference in the latter case, no comparisons are actually performed. In contrast, the necessity for indirect comparisons among various drugs of the same efficacy used in clinical practice became greater. Conventional meta-analysis on the treatment effects of new drugs is conducted on the effect size based on pairwise head-to-head direct comparison, but data from direct comparisons are relatively limited. Thus, NMA should be activated in order to guarantee the quality of healthcare system.Īs newly developed drugs conducted the third stage of randomized clinical trials (RCT) are approved for marketing, and enter into the armamentarium of treatment, there is a need for comparative effectiveness research (CER) to evaluate the effectiveness of drugs used for the same treatment goal and meta-analysis to synthesize the results of the CER.
The synthesized evidences through five steps would be very useful to evidence-based decision-making in healthcare. The last step evaluates publication bias or effect modifiers for a valid inference from results. The fourth step calculates cumulative rankings for identifying superiority among interventions.
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 second step checks the assumption of consistency. The first step is to draw a network geometry to provide an overview of the network relationship. The statistical analysis consists of 5 steps. Before conducting a NMA, 3 major assumptions-similarity, transitivity, and consistency-should be checked. 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.
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.