MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard
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 Accurac...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-05-01
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| Series: | BMC Medical Research Methodology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12874-023-01910-y |
| _version_ | 1827939867238072320 |
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| author | Enzo Cerullo Alex J. Sutton Hayley E. Jones Olivia Wu Terry J. Quinn Nicola J. Cooper |
| author_facet | Enzo Cerullo Alex J. Sutton Hayley E. Jones Olivia Wu Terry J. Quinn Nicola J. Cooper |
| author_sort | Enzo Cerullo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-13T09:00:52Z |
| format | Article |
| id | doaj.art-d7642c9e86e045ba914e00b1ace4d2e0 |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-03-13T09:00:52Z |
| publishDate | 2023-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-d7642c9e86e045ba914e00b1ace4d2e02023-05-28T11:20:20ZengBMCBMC Medical Research Methodology1471-22882023-05-0123112010.1186/s12874-023-01910-yMetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standardEnzo Cerullo0Alex J. Sutton1Hayley E. Jones2Olivia Wu3Terry J. Quinn4Nicola J. Cooper5Biostatistics Research Group, Department of Population Health Sciences, University of LeicesterBiostatistics Research Group, Department of Population Health Sciences, University of LeicesterPopulation Health Sciences, University of Bristol, Bristol Medical SchoolComplex Reviews Support Unit, University of Leicester & University of GlasgowComplex Reviews Support Unit, University of Leicester & University of GlasgowBiostatistics Research Group, Department of Population Health Sciences, University of LeicesterAbstract 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.https://doi.org/10.1186/s12874-023-01910-yMeta-AnalysisDiagnostic test accuracyApplicationImperfect gold standardLatent class |
| spellingShingle | Enzo Cerullo Alex J. Sutton Hayley E. Jones Olivia Wu Terry J. Quinn Nicola J. Cooper MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard BMC Medical Research Methodology Meta-Analysis Diagnostic test accuracy Application Imperfect gold standard Latent class |
| title | MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard |
| title_full | MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard |
| title_fullStr | MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard |
| title_full_unstemmed | MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard |
| title_short | MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard |
| title_sort | metabayesdta codeless bayesian meta analysis of test accuracy with or without a gold standard |
| topic | Meta-Analysis Diagnostic test accuracy Application Imperfect gold standard Latent class |
| url | https://doi.org/10.1186/s12874-023-01910-y |
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