Title: An approach to evaluate and compare biomarkers to diagnose a disease
Authors: Maria del Carmen Pardo - Complutense University of Madrid (Spain) [presenting]
Christos T Nakas - University of Bern (Switzerland)
Alba Franco-Pereira - Universidad Complutense de Madrid (Spain)
Abstract: The index of the Area Under the ROC curve (AUC) reflects the amount of separation of the biomarker distributions in the two samples of subjects derived from the non-diseased and diseased populations. Along with the AUC, the maximum of the Youden index, $J$, is often used for the comparison of competing biomarkers. We study the utility of the Length of the binormal model-based ROC Curve (LoC) as an index of diagnostic accuracy for biomarker evaluation. In a simulation study, the performance of LoC is compared with approaches based on AUC and $J$, both for the case of the assessment of a single biomarker and for the comparison of two biomarkers, in a parametric framework. We provide an interpretation for the proposed index and illustrate with an application on biomarkers from a colorectal cancer study.