ESMARConf2023: {MetaDTA} tutorial

Presenter: Alex Sutton
Authors: Cooper, Nicola; Sutton, Alex
Session: Tutorials 2
Title: MetaDTA: An interactive, web-based Shiny app that conducts meta-analysis of diagnostic test accuracy data through a ‘point and click’ interface and creates novel data visualisations
Abstract: Diagnostic tests form an essential part of current medical practices aiming to distinguish between patients with the disease and healthy individuals. They are used across a diverse range of healthcare settings and are often a pre-requisite to identifying treatment options and enabling access to services. Recommended statistical methods for meta-analysis of diagnostic test accuracy (DTA) studies require the fitting of complex non-standard statistical models which can be a barrier to their application. MetaDTA (https://crsu.shinyapps.io/dta_ma/) is a free interactive online application which meta-analyses DTA studies using the frequently recommended bivariate model. The app is developed using the R package Shiny and leverages existing software packages, including those for DTA meta-analysis. This tutorial demonstrates how the app is used including details of data entry, plotting summary receiver operating characteristic curves and forest plots, conducting sensitivity analyses interactively, and visualising how quality assessment results from the QUADAS-2 tool or other covariates impact test accuracy. A further figure explaining how the accuracy of the test would relate to clinical practice is also considered. All outputs produce can be exported for use in analysis reports etc.
GitHub repository: https://github.com/CRSU-Apps/MetaDTA