학술논문

MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard
Document Type
article
Source
BMC Medical Research Methodology, Vol 23, Iss 1, Pp 1-20 (2023)
Subject
Meta-Analysis
Diagnostic test accuracy
Application
Imperfect gold standard
Latent class
Medicine (General)
R5-920
Language
English
ISSN
1471-2288
Abstract
Abstract Background The statistical models developed for meta-analysis of diagnostic test accuracy studies require specialised knowledge to implement. This is especially true since recent guidelines, such as those in Version 2 of the Cochrane Handbook of Systematic Reviews of Diagnostic Test Accuracy, advocate more sophisticated methods than previously. This paper describes a web-based application - MetaBayesDTA - that makes many advanced analysis methods in this area more accessible. Results We created the app using R, the Shiny package and Stan. It allows for a broad array of analyses based on the bivariate model including extensions for subgroup analysis, meta-regression and comparative test accuracy evaluation. It also conducts analyses not assuming a perfect reference standard, including allowing for the use of different reference tests. Conclusions Due to its user-friendliness and broad array of features, MetaBayesDTA should appeal to researchers with varying levels of expertise. We anticipate that the application will encourage higher levels of uptake of more advanced methods, which ultimately should improve the quality of test accuracy reviews.