Open AccessMultiple treatment and indirect treatment comparisons: An overview of network meta-analysis
Author(s) -
Nidhi Bhatnagar,
P V M Lakshmi,
Kathiresan Jeyashree
Publication year - 2014
Publication title -
perspectives in clinical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.649
H-Index - 8
eISSN - 2229-5488
pISSN - 2229-3485
DOI - 10.4103/2229-3485.140550
Subject(s) - frequentist inference , randomized controlled trial , bayesian probability , computer science , sample size determination , meta analysis , bayesian statistics , consistency (knowledge bases) , statistics , statistical power , econometrics , data mining , medicine , artificial intelligence , bayesian inference , mathematics , surgery
Randomized control trials and its meta-analysis has occupied the pinnacle in levels of evidence available for research. However, there were several limitations of these trials. Network meta-analysis (NMA) is a recent tool for evidence-based medicine that draws strength from direct and indirect evidence generated from randomized control trials. It facilitates comparisons across multiple treatment options, direct comparisons of which have not been attempted till date due to multitude of reasons. These indirect treatment comparisons of randomized controlled trials are based on similarity and consistency assumptions that follow Bayesian or frequentist statistics. Most NMAuntil date use Microsoft Windows WinBUGs Software for analysis which relies on Bayesian statistics. Methodology of NMA is expected to undergo further refinements and become robust with usage. Power and precision of indirect comparisons in NMA is a concern as it is dependent on effective number of trials, sample size and complete statistical information. However, NMA can synthesize results of considerable relevance to experts and policy makers.