MetaBayesDTA: Codeless Bayesian meta-analysis of test accuracy, with or without a gold standard

Enzo  Cerullo; Alex J.  Sutton; Hayley E Jones; Olivia  Wu; Terry J.  Quinn; Nicola J.  Cooper

doi:10.1186/s12874-023-01910-y

MetaBayesDTA: Codeless Bayesian meta-analysis of test accuracy, with or without a gold standard

Enzo Cerullo^*, Alex J. Sutton, Hayley E Jones, Olivia Wu, Terry J. Quinn, Nicola J. Cooper

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

38 Citations (Scopus)

Abstract

Background: The statistical models developed for meta-analysis of diagnostictest accuracy studies require specialised knowledge to implement. This isespecially true since recent guidelines, such as those in Version 2 of the CochraneHandbook of Systematic Reviews of Diagnostic Test Accuracy, advocate moresophisticated methods than previously. This paper describes a web-basedapplication - MetaBayesDTA - that makes many advanced analysis methods inthis area more accessible.

Results: We created the app using R, the Shiny package and Stan. It allows for abroad array of analyses based on the bivariate model including extensions forsubgroup analysis, meta-regression and comparative test accuracy evaluation. Italso conducts analyses not assuming a perfect reference standard, includingallowing 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. Weanticipate that the application will encourage higher levels of uptake of moreadvanced methods, which ultimately should improve the quality of test accuracyreviews.

Original language	English
Article number	127
Journal	BMC Medical Research Methodology
Volume	23
Issue number	1
DOIs	https://doi.org/10.1186/s12874-023-01910-y
Publication status	Published - 25 May 2023

Bibliographical note

Funding Information:
The work was carried out whilst EC was funded by a National Institute for Health Research (NIHR) Complex Reviews Support Unit (project number 14/178/29) and by an NIHR doctoral research fellowship (project number NIHR302333). The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health. The NIHR had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. This project is funded by the NIHR Applied Research Collaboration East Midlands (ARC EM). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Publisher Copyright:
© 2023, The Author(s).

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Evidence synthesis of diagnostic test performance from a decision-making perspective
Jones, H. E. (Principal Investigator)
12/08/15 → 11/08/19
Project: Research

Cite this

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title = "MetaBayesDTA: Codeless Bayesian meta-analysis of test accuracy, with or without a gold standard",

abstract = "Background: The statistical models developed for meta-analysis of diagnostictest accuracy studies require specialised knowledge to implement. This isespecially true since recent guidelines, such as those in Version 2 of the CochraneHandbook of Systematic Reviews of Diagnostic Test Accuracy, advocate moresophisticated methods than previously. This paper describes a web-basedapplication - MetaBayesDTA - that makes many advanced analysis methods inthis area more accessible. Results: We created the app using R, the Shiny package and Stan. It allows for abroad array of analyses based on the bivariate model including extensions forsubgroup analysis, meta-regression and comparative test accuracy evaluation. Italso conducts analyses not assuming a perfect reference standard, includingallowing 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. Weanticipate that the application will encourage higher levels of uptake of moreadvanced methods, which ultimately should improve the quality of test accuracyreviews.",

author = "Enzo Cerullo and Sutton, \{Alex J.\} and Jones, \{Hayley E\} and Olivia Wu and Quinn, \{Terry J.\} and Cooper, \{Nicola J.\}",

note = "Funding Information: The work was carried out whilst EC was funded by a National Institute for Health Research (NIHR) Complex Reviews Support Unit (project number 14/178/29) and by an NIHR doctoral research fellowship (project number NIHR302333). The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health. The NIHR had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. This project is funded by the NIHR Applied Research Collaboration East Midlands (ARC EM). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. Publisher Copyright: {\textcopyright} 2023, The Author(s).",

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AU - Jones, Hayley E

AU - Wu, Olivia

AU - Quinn, Terry J.

AU - Cooper, Nicola J.

N1 - Funding Information: The work was carried out whilst EC was funded by a National Institute for Health Research (NIHR) Complex Reviews Support Unit (project number 14/178/29) and by an NIHR doctoral research fellowship (project number NIHR302333). The views and opinions expressed herein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health. The NIHR had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. This project is funded by the NIHR Applied Research Collaboration East Midlands (ARC EM). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. Publisher Copyright: © 2023, The Author(s).

PY - 2023/5/25

Y1 - 2023/5/25

N2 - Background: The statistical models developed for meta-analysis of diagnostictest accuracy studies require specialised knowledge to implement. This isespecially true since recent guidelines, such as those in Version 2 of the CochraneHandbook of Systematic Reviews of Diagnostic Test Accuracy, advocate moresophisticated methods than previously. This paper describes a web-basedapplication - MetaBayesDTA - that makes many advanced analysis methods inthis area more accessible. Results: We created the app using R, the Shiny package and Stan. It allows for abroad array of analyses based on the bivariate model including extensions forsubgroup analysis, meta-regression and comparative test accuracy evaluation. Italso conducts analyses not assuming a perfect reference standard, includingallowing 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. Weanticipate that the application will encourage higher levels of uptake of moreadvanced methods, which ultimately should improve the quality of test accuracyreviews.

AB - Background: The statistical models developed for meta-analysis of diagnostictest accuracy studies require specialised knowledge to implement. This isespecially true since recent guidelines, such as those in Version 2 of the CochraneHandbook of Systematic Reviews of Diagnostic Test Accuracy, advocate moresophisticated methods than previously. This paper describes a web-basedapplication - MetaBayesDTA - that makes many advanced analysis methods inthis area more accessible. Results: We created the app using R, the Shiny package and Stan. It allows for abroad array of analyses based on the bivariate model including extensions forsubgroup analysis, meta-regression and comparative test accuracy evaluation. Italso conducts analyses not assuming a perfect reference standard, includingallowing 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. Weanticipate that the application will encourage higher levels of uptake of moreadvanced methods, which ultimately should improve the quality of test accuracyreviews.

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MetaBayesDTA: Codeless Bayesian meta-analysis of test accuracy, with or without a gold standard

Abstract

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Evidence synthesis of diagnostic test performance from a decision-making perspective

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