Generalized ROC curve inference for a biomarker subject to a limit of detection and measurement error

Abstract

The receiver operating characteristic (ROC) curve is a tool commonly used to evaluate biomarker utility in clinical diagnosis of disease, especially during biomarker development research. Emerging biomarkers are often measured with random measurement error and subject to limits of detection that hinder their potential utility or mask an ability to discriminate by negatively biasing the estimates of ROC curves and subsequent area under the curve. Methods have been developed to correct the ROC curve for each of these types of sources of bias but here we develop a method by which the ROC curve is corrected for both simultaneously through replicate measures and maximum likelihood. Our method is evaluated via simulation study and applied to two potential discriminators of women with and without preeclampsia.