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BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses
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BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses
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Journal Article
BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses
2019
Overview
Background
Several reviews have noted shortcomings regarding the quality and reporting of network meta-analyses (NMAs). We suspect that this issue may be partially attributable to limitations in current NMA software which do not readily produce all of the output needed to satisfy current guidelines.
Results
To better facilitate the conduct and reporting of NMAs, we have created an R package called “BUGSnet” (
B
ayesian inference
U
sing
G
ibbs
S
ampling to conduct a
Net
work meta-analysis). This R package relies upon Just Another Gibbs Sampler (JAGS) to conduct Bayesian NMA using a generalized linear model. BUGSnet contains a suite of functions that can be used to describe the evidence network, estimate a model and assess the model fit and convergence, assess the presence of heterogeneity and inconsistency, and output the results in a variety of formats including league tables and surface under the cumulative rank curve (SUCRA) plots. We provide a demonstration of the functions contained within BUGSnet by recreating a Bayesian NMA found in the second technical support document composed by the National Institute for Health and Care Excellence Decision Support Unit (NICE-DSU). We have also mapped these functions to checklist items within current reporting and best practice guidelines.
Conclusion
BUGSnet is a new R package that can be used to conduct a Bayesian NMA and produce all of the necessary output needed to satisfy current scientific and regulatory standards. We hope that this software will help to improve the conduct and reporting of NMAs.
Publisher
BioMed Central,BioMed Central Ltd,BMC
