Cargando…

IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy

BACKGROUND: Individual patient data meta‐analyses (IPD‐MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD‐MA have been published in recent years, but...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Junfeng, Keusters, Willem R., Wen, Lingzi, Leeflang, Mariska M. G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7821168/
https://www.ncbi.nlm.nih.gov/pubmed/32808437
http://dx.doi.org/10.1002/jrsm.1444
_version_ 1783639361076592640
author Wang, Junfeng
Keusters, Willem R.
Wen, Lingzi
Leeflang, Mariska M. G.
author_facet Wang, Junfeng
Keusters, Willem R.
Wen, Lingzi
Leeflang, Mariska M. G.
author_sort Wang, Junfeng
collection PubMed
description BACKGROUND: Individual patient data meta‐analyses (IPD‐MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD‐MA have been published in recent years, but there is much variation in how these IPD‐MA were performed. A number of existing methods were found, but there is no consensus as to which methods are preferred as the standard methods for statistical analysis in DTA IPD‐MA. OBJECTIVES: To create a web‐based tool which integrates recommended statistical analyses for DTA IPD‐MA, and allows researchers to analyse the data and visualize the results with interactive plots. METHODS: A systematic methodological review was performed to identify statistical analyses and data visualization methods used in DTA IPD‐MA. Methods were evaluated by the authors and recommended analyses were integrated into the IPDmada tool which is freely available online with the user interface developed with R Shiny package. RESULTS: IPDmada allows users to upload their own data, perform the meta‐analysis with both continuous and dichotomized tests, and incorporate individual level covariate‐adjusted analysis. All tables and figures can be exported as .csv or .pdf files. A hypothetical dataset was used to illustrate the application of IPDmada. CONCLUSIONS: IPDmada will be very helpful to researchers doing DTA IPD‐MA, since it not only facilitates the statistical analysis but also provides a standard framework. The introduction of IPDmada will harmonize the methods used in DTA IPD‐MA and ensure the quality of such analyses. HIGHLIGHTS: IPDmada is a newly developed web‐based tool for performing statistical analysis of individual patient data meta‐analysis of diagnostic accuracy and visualizing the results. The tool is freely available to all the researchers, and requiring no installation of statistical software/packages. The tool has an user‐friendly interface, and allows meta‐analysis on both dichotomized and continuous test results. Researchers can easily use this tool to investigate the threshold effect and covariate effect on the summary accuracy. The introduction and implementation of IPDmada will serve as a useful tool for DTA IPD‐MA and increase the quality of such studies.
format Online
Article
Text
id pubmed-7821168
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-78211682021-01-26 IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy Wang, Junfeng Keusters, Willem R. Wen, Lingzi Leeflang, Mariska M. G. Res Synth Methods Special Issue Papers BACKGROUND: Individual patient data meta‐analyses (IPD‐MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD‐MA have been published in recent years, but there is much variation in how these IPD‐MA were performed. A number of existing methods were found, but there is no consensus as to which methods are preferred as the standard methods for statistical analysis in DTA IPD‐MA. OBJECTIVES: To create a web‐based tool which integrates recommended statistical analyses for DTA IPD‐MA, and allows researchers to analyse the data and visualize the results with interactive plots. METHODS: A systematic methodological review was performed to identify statistical analyses and data visualization methods used in DTA IPD‐MA. Methods were evaluated by the authors and recommended analyses were integrated into the IPDmada tool which is freely available online with the user interface developed with R Shiny package. RESULTS: IPDmada allows users to upload their own data, perform the meta‐analysis with both continuous and dichotomized tests, and incorporate individual level covariate‐adjusted analysis. All tables and figures can be exported as .csv or .pdf files. A hypothetical dataset was used to illustrate the application of IPDmada. CONCLUSIONS: IPDmada will be very helpful to researchers doing DTA IPD‐MA, since it not only facilitates the statistical analysis but also provides a standard framework. The introduction of IPDmada will harmonize the methods used in DTA IPD‐MA and ensure the quality of such analyses. HIGHLIGHTS: IPDmada is a newly developed web‐based tool for performing statistical analysis of individual patient data meta‐analysis of diagnostic accuracy and visualizing the results. The tool is freely available to all the researchers, and requiring no installation of statistical software/packages. The tool has an user‐friendly interface, and allows meta‐analysis on both dichotomized and continuous test results. Researchers can easily use this tool to investigate the threshold effect and covariate effect on the summary accuracy. The introduction and implementation of IPDmada will serve as a useful tool for DTA IPD‐MA and increase the quality of such studies. John Wiley and Sons Inc. 2020-09-09 2021-01 /pmc/articles/PMC7821168/ /pubmed/32808437 http://dx.doi.org/10.1002/jrsm.1444 Text en © 2020 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Special Issue Papers
Wang, Junfeng
Keusters, Willem R.
Wen, Lingzi
Leeflang, Mariska M. G.
IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy
title IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy
title_full IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy
title_fullStr IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy
title_full_unstemmed IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy
title_short IPDmada: An R Shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy
title_sort ipdmada: an r shiny tool for analyzing and visualizing individual patient data meta‐analyses of diagnostic test accuracy
topic Special Issue Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7821168/
https://www.ncbi.nlm.nih.gov/pubmed/32808437
http://dx.doi.org/10.1002/jrsm.1444
work_keys_str_mv AT wangjunfeng ipdmadaanrshinytoolforanalyzingandvisualizingindividualpatientdatametaanalysesofdiagnostictestaccuracy
AT keusterswillemr ipdmadaanrshinytoolforanalyzingandvisualizingindividualpatientdatametaanalysesofdiagnostictestaccuracy
AT wenlingzi ipdmadaanrshinytoolforanalyzingandvisualizingindividualpatientdatametaanalysesofdiagnostictestaccuracy
AT leeflangmariskamg ipdmadaanrshinytoolforanalyzingandvisualizingindividualpatientdatametaanalysesofdiagnostictestaccuracy