Meta-DiSc 2.0: a web application for meta-analysis of diagnostic test accuracy data

Maria N. Plana; Ingrid Arevalo-Rodriguez; Silvia Fernández-García; Javier Soto; Martin Fabregate; Teresa Pérez; Marta Roqué; Javier Zamora

doi:10.1186/s12874-022-01788-2

Meta-DiSc 2.0: a web application for meta-analysis of diagnostic test accuracy data

Maria N. Plana^*, Ingrid Arevalo-Rodriguez, Silvia Fernández-García, Javier Soto, Martin Fabregate, Teresa Pérez, Marta Roqué, Javier Zamora

^*Corresponding author for this work

Metabolism and Systems Science

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

92 Downloads (Pure)

Abstract

Background: Diagnostic evidence of the accuracy of a test for identifying a target condition of interest can be estimated using systematic approaches following standardized methodologies. Statistical methods for the meta-analysis of diagnostic test accuracy (DTA) studies are relatively complex, presenting a challenge for reviewers without extensive statistical expertise. In 2006, we developed Meta-DiSc, a free user-friendly software to perform test accuracy meta-analysis. This statistical program is now widely used for performing DTA meta-analyses. We aimed to build a new version of the Meta-DiSc software to include statistical methods based on hierarchical models and an enhanced web-based interface to improve user experience.

Results: In this article, we present the updated version, Meta-DiSc 2.0, a web-based application developed using the R Shiny package. This new version implements recommended state-of-the-art statistical models to overcome the limitations of the statistical approaches included in the previous version. Meta-DiSc 2.0 performs statistical analyses of DTA reviews using a bivariate random effects model. The application offers a thorough analysis of heterogeneity, calculating logit variance estimates of sensitivity and specificity, the bivariate I-squared, the area of the 95% prediction ellipse, and the median odds ratios for sensitivity and specificity, and facilitating subgroup and meta-regression analyses. Furthermore, univariate random effects models can be applied to meta-analyses with few studies or with non-convergent bivariate models.

The application interface has an intuitive design set out in four main menus: file upload; graphical description (forest and ROC plane plots); meta-analysis (pooling of sensitivity and specificity, estimation of likelihood ratios and diagnostic odds ratio, sROC curve); and summary of findings (impact of test through downstream consequences in a hypothetical population with a given prevalence).

All computational algorithms have been validated in several real datasets by comparing results obtained with STATA/SAS and MetaDTA packages.

Conclusion: We have developed and validated an updated version of the Meta-DiSc software that is more accessible and statistically sound. The web application is freely available at www.metadisc.es.

Original language	English
Article number	306
Number of pages	8
Journal	BMC Medical Research Methodology
Volume	22
Issue number	1
DOIs	https://doi.org/10.1186/s12874-022-01788-2
Publication status	Published - 28 Nov 2022

Bibliographical note

Funding Information:
Meta-DiSc 2.0 has been developed with funding from an intramural project by the Ramón y Cajal Research Institute ("Rapid diagnostic reviews for decision-making in healthcare: analysis of critical points and software development", 2018). It has also been funded by Instituto de Salud Carlos III through the project "PI19/00481" (Co-funded by European Regional Development Fund/European Social Fund; “A way to make Europe”/"Investing in your future"). The Biomedical Research Networking Center in Epidemiology and Public Health (CIBERESP) funds the subscription to the shinyapps.io platform where the app is hosted. The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Funding Information:
Project name: Meta-DiSc 2.0 Project home page: https://metadisc.sourceforge.io Operating system(s): Platform independent Programming language: R Other requirements: Internet browser License: GNU General Public License version 3.0 (GPLv3) Any restrictions to use by non-academics: None

Funding Information:
The development of this web application was led by the Clinical Biostatistics Unit of the Ramón y Cajal Research Institute (IRYCIS), a unit that has broad experience in diagnostic test synthesis research focused on supporting informed decision-making in the healthcare area. This constitutes a collaborative project for knowledge transfer between IRYCIS and the Complutense University of Madrid and is supported by an intramural project funded by the Ramón y Cajal Research Institute ("Rapid diagnostic reviews for decision-making in healthcare: analysis of critical points and software development", 2018). This project has also been funded by Instituto de Salud Carlos III through the project "PI19/00481" (Co-funded by European Regional Development Fund/European Social Fund; “A way to make Europe”/"Investing in your future"). The Biomedical Research Networking Center in Epidemiology and Public Health (CIBERESP) funds the subscription to the shinyapps.io platform where the app is hosted.

Publisher Copyright:
© 2022, The Author(s).

Keywords

Diagnosis
Heterogeneity
Meta-analysis
Sensitivity
Specificity
Systematic review

ASJC Scopus subject areas

Epidemiology
Health Informatics

Access to Document

10.1186/s12874-022-01788-2Licence: Creative Commons: Attribution (CC BY)

PlanaM2022MetaFinal published version, 1.59 MBLicence: Creative Commons: Attribution (CC BY)

Cite this

@article{db0d574ad39b4cf18d54d54c570af7ce,

title = "Meta-DiSc 2.0: a web application for meta-analysis of diagnostic test accuracy data",

abstract = "Background: Diagnostic evidence of the accuracy of a test for identifying a target condition of interest can be estimated using systematic approaches following standardized methodologies. Statistical methods for the meta-analysis of diagnostic test accuracy (DTA) studies are relatively complex, presenting a challenge for reviewers without extensive statistical expertise. In 2006, we developed Meta-DiSc, a free user-friendly software to perform test accuracy meta-analysis. This statistical program is now widely used for performing DTA meta-analyses. We aimed to build a new version of the Meta-DiSc software to include statistical methods based on hierarchical models and an enhanced web-based interface to improve user experience. Results: In this article, we present the updated version, Meta-DiSc 2.0, a web-based application developed using the R Shiny package. This new version implements recommended state-of-the-art statistical models to overcome the limitations of the statistical approaches included in the previous version. Meta-DiSc 2.0 performs statistical analyses of DTA reviews using a bivariate random effects model. The application offers a thorough analysis of heterogeneity, calculating logit variance estimates of sensitivity and specificity, the bivariate I-squared, the area of the 95% prediction ellipse, and the median odds ratios for sensitivity and specificity, and facilitating subgroup and meta-regression analyses. Furthermore, univariate random effects models can be applied to meta-analyses with few studies or with non-convergent bivariate models. The application interface has an intuitive design set out in four main menus: file upload; graphical description (forest and ROC plane plots); meta-analysis (pooling of sensitivity and specificity, estimation of likelihood ratios and diagnostic odds ratio, sROC curve); and summary of findings (impact of test through downstream consequences in a hypothetical population with a given prevalence). All computational algorithms have been validated in several real datasets by comparing results obtained with STATA/SAS and MetaDTA packages. Conclusion: We have developed and validated an updated version of the Meta-DiSc software that is more accessible and statistically sound. The web application is freely available at www.metadisc.es.",

keywords = "Diagnosis, Heterogeneity, Meta-analysis, Sensitivity, Specificity, Systematic review",

author = "Plana, {Maria N.} and Ingrid Arevalo-Rodriguez and Silvia Fern{\'a}ndez-Garc{\'i}a and Javier Soto and Martin Fabregate and Teresa P{\'e}rez and Marta Roqu{\'e} and Javier Zamora",

note = "Funding Information: Meta-DiSc 2.0 has been developed with funding from an intramural project by the Ram{\'o}n y Cajal Research Institute ({"}Rapid diagnostic reviews for decision-making in healthcare: analysis of critical points and software development{"}, 2018). It has also been funded by Instituto de Salud Carlos III through the project {"}PI19/00481{"} (Co-funded by European Regional Development Fund/European Social Fund; “A way to make Europe”/{"}Investing in your future{"}). The Biomedical Research Networking Center in Epidemiology and Public Health (CIBERESP) funds the subscription to the shinyapps.io platform where the app is hosted. The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Funding Information: Project name: Meta-DiSc 2.0 Project home page: https://metadisc.sourceforge.io Operating system(s): Platform independent Programming language: R Other requirements: Internet browser License: GNU General Public License version 3.0 (GPLv3) Any restrictions to use by non-academics: None Funding Information: The development of this web application was led by the Clinical Biostatistics Unit of the Ram{\'o}n y Cajal Research Institute (IRYCIS), a unit that has broad experience in diagnostic test synthesis research focused on supporting informed decision-making in the healthcare area. This constitutes a collaborative project for knowledge transfer between IRYCIS and the Complutense University of Madrid and is supported by an intramural project funded by the Ram{\'o}n y Cajal Research Institute ({"}Rapid diagnostic reviews for decision-making in healthcare: analysis of critical points and software development{"}, 2018). This project has also been funded by Instituto de Salud Carlos III through the project {"}PI19/00481{"} (Co-funded by European Regional Development Fund/European Social Fund; “A way to make Europe”/{"}Investing in your future{"}). The Biomedical Research Networking Center in Epidemiology and Public Health (CIBERESP) funds the subscription to the shinyapps.io platform where the app is hosted. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = nov,

day = "28",

doi = "10.1186/s12874-022-01788-2",

language = "English",

volume = "22",

journal = "BMC Medical Research Methodology",

issn = "1471-2288",

publisher = "Springer",

number = "1",

}

TY - JOUR

T1 - Meta-DiSc 2.0

T2 - a web application for meta-analysis of diagnostic test accuracy data

AU - Plana, Maria N.

AU - Arevalo-Rodriguez, Ingrid

AU - Fernández-García, Silvia

AU - Soto, Javier

AU - Fabregate, Martin

AU - Pérez, Teresa

AU - Roqué, Marta

AU - Zamora, Javier

N1 - Funding Information: Meta-DiSc 2.0 has been developed with funding from an intramural project by the Ramón y Cajal Research Institute ("Rapid diagnostic reviews for decision-making in healthcare: analysis of critical points and software development", 2018). It has also been funded by Instituto de Salud Carlos III through the project "PI19/00481" (Co-funded by European Regional Development Fund/European Social Fund; “A way to make Europe”/"Investing in your future"). The Biomedical Research Networking Center in Epidemiology and Public Health (CIBERESP) funds the subscription to the shinyapps.io platform where the app is hosted. The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Funding Information: Project name: Meta-DiSc 2.0 Project home page: https://metadisc.sourceforge.io Operating system(s): Platform independent Programming language: R Other requirements: Internet browser License: GNU General Public License version 3.0 (GPLv3) Any restrictions to use by non-academics: None Funding Information: The development of this web application was led by the Clinical Biostatistics Unit of the Ramón y Cajal Research Institute (IRYCIS), a unit that has broad experience in diagnostic test synthesis research focused on supporting informed decision-making in the healthcare area. This constitutes a collaborative project for knowledge transfer between IRYCIS and the Complutense University of Madrid and is supported by an intramural project funded by the Ramón y Cajal Research Institute ("Rapid diagnostic reviews for decision-making in healthcare: analysis of critical points and software development", 2018). This project has also been funded by Instituto de Salud Carlos III through the project "PI19/00481" (Co-funded by European Regional Development Fund/European Social Fund; “A way to make Europe”/"Investing in your future"). The Biomedical Research Networking Center in Epidemiology and Public Health (CIBERESP) funds the subscription to the shinyapps.io platform where the app is hosted. Publisher Copyright: © 2022, The Author(s).

PY - 2022/11/28

Y1 - 2022/11/28

N2 - Background: Diagnostic evidence of the accuracy of a test for identifying a target condition of interest can be estimated using systematic approaches following standardized methodologies. Statistical methods for the meta-analysis of diagnostic test accuracy (DTA) studies are relatively complex, presenting a challenge for reviewers without extensive statistical expertise. In 2006, we developed Meta-DiSc, a free user-friendly software to perform test accuracy meta-analysis. This statistical program is now widely used for performing DTA meta-analyses. We aimed to build a new version of the Meta-DiSc software to include statistical methods based on hierarchical models and an enhanced web-based interface to improve user experience. Results: In this article, we present the updated version, Meta-DiSc 2.0, a web-based application developed using the R Shiny package. This new version implements recommended state-of-the-art statistical models to overcome the limitations of the statistical approaches included in the previous version. Meta-DiSc 2.0 performs statistical analyses of DTA reviews using a bivariate random effects model. The application offers a thorough analysis of heterogeneity, calculating logit variance estimates of sensitivity and specificity, the bivariate I-squared, the area of the 95% prediction ellipse, and the median odds ratios for sensitivity and specificity, and facilitating subgroup and meta-regression analyses. Furthermore, univariate random effects models can be applied to meta-analyses with few studies or with non-convergent bivariate models. The application interface has an intuitive design set out in four main menus: file upload; graphical description (forest and ROC plane plots); meta-analysis (pooling of sensitivity and specificity, estimation of likelihood ratios and diagnostic odds ratio, sROC curve); and summary of findings (impact of test through downstream consequences in a hypothetical population with a given prevalence). All computational algorithms have been validated in several real datasets by comparing results obtained with STATA/SAS and MetaDTA packages. Conclusion: We have developed and validated an updated version of the Meta-DiSc software that is more accessible and statistically sound. The web application is freely available at www.metadisc.es.

AB - Background: Diagnostic evidence of the accuracy of a test for identifying a target condition of interest can be estimated using systematic approaches following standardized methodologies. Statistical methods for the meta-analysis of diagnostic test accuracy (DTA) studies are relatively complex, presenting a challenge for reviewers without extensive statistical expertise. In 2006, we developed Meta-DiSc, a free user-friendly software to perform test accuracy meta-analysis. This statistical program is now widely used for performing DTA meta-analyses. We aimed to build a new version of the Meta-DiSc software to include statistical methods based on hierarchical models and an enhanced web-based interface to improve user experience. Results: In this article, we present the updated version, Meta-DiSc 2.0, a web-based application developed using the R Shiny package. This new version implements recommended state-of-the-art statistical models to overcome the limitations of the statistical approaches included in the previous version. Meta-DiSc 2.0 performs statistical analyses of DTA reviews using a bivariate random effects model. The application offers a thorough analysis of heterogeneity, calculating logit variance estimates of sensitivity and specificity, the bivariate I-squared, the area of the 95% prediction ellipse, and the median odds ratios for sensitivity and specificity, and facilitating subgroup and meta-regression analyses. Furthermore, univariate random effects models can be applied to meta-analyses with few studies or with non-convergent bivariate models. The application interface has an intuitive design set out in four main menus: file upload; graphical description (forest and ROC plane plots); meta-analysis (pooling of sensitivity and specificity, estimation of likelihood ratios and diagnostic odds ratio, sROC curve); and summary of findings (impact of test through downstream consequences in a hypothetical population with a given prevalence). All computational algorithms have been validated in several real datasets by comparing results obtained with STATA/SAS and MetaDTA packages. Conclusion: We have developed and validated an updated version of the Meta-DiSc software that is more accessible and statistically sound. The web application is freely available at www.metadisc.es.

KW - Diagnosis

KW - Heterogeneity

KW - Meta-analysis

KW - Sensitivity

KW - Specificity

KW - Systematic review

UR - http://www.scopus.com/inward/record.url?scp=85142786523&partnerID=8YFLogxK

U2 - 10.1186/s12874-022-01788-2

DO - 10.1186/s12874-022-01788-2

M3 - Article

C2 - 36443653

AN - SCOPUS:85142786523

SN - 1471-2288

VL - 22

JO - BMC Medical Research Methodology

JF - BMC Medical Research Methodology

IS - 1

M1 - 306

ER -

Meta-DiSc 2.0: a web application for meta-analysis of diagnostic test accuracy data

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this