Plana, NievesArevalo-Rodriguez, IngridFernández-García, SilviaSoto, JavierFabregate, MartíinPérez Pérez, TeresaRoqué, MartaZamora Romero, Javier2024-11-182024-11-182022-11-28Plana MN, Arevalo-Rodriguez I, Fernández-García S, et al. Meta-DiSc 2.0: a web application for meta-analysis of diagnostic test accuracy data. BMC Med Res Methodol. 2022;22(1):306. Published 2022 Nov 28. doi:10.1186/s12874-022-01788-210.1186/s12874-022-01788-2https://hdl.handle.net/20.500.14352/110678Background: 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 .engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/journal articlehttps://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-022-01788-2https://pubmed.ncbi.nlm.nih.gov/36443653/open accessDiagnosisHeterogeneityMeta-analysisSensitivitySpecificitySystematic reviewEstadísticaMedicina1209 Estadística3212 Salud Publica3210 Medicina Preventiva