Using IPDmada to perform statistical analyses of diagnostic accuracy in primary studies: explanation and elaboration with a case study

IPDmada is web -based R Shiny application recently developed for individual patient data metaanalysis (IPD-MA) of diagnostic test accuracy (DTA). IPDmada provides a wide range of analyses in IPD-MA, which are also applicable in primary studies of diagnostic accuracy. These analyses include summary table of patient characteristics (usually referred to as "Table 1"); calculation of all the test performance measures; forest plots of sensitiviy and specificity and summary receiver operating characteristic (ROC) plots for dichotomized tests; distribution of test results and ROC curves for continuous test; forest plots of areas under the curve (AUCs) for continuous tests; distribution of covariates and covariate adjusted ROC curves for covariate analysis, which provide more than enough results for a complete DTA study. In this explanation and elaboration document, we use IPDmada to perform both basic and advanced statistical analyses in evaluating a diagnostic test, to show the feasibility of applying IPDmada in primary studies of DTA. The data source used in this case study is from a previous publication by Norton et al., which investigated the diagnostic accuracy of transient evoked otoacoustic emissions (TEOAEs), distortion product otoacoustic emissions (DPOAEs), and auditory brain stem responses (ABRs) for neonatal hearing impairment. In conclusion, IPDmada is an easy -to -use tool, which can provide an one -stop solution to researchers without strong statistical background for all the analyses needed in a DTA study.