VAROC: Value Added Receiver Operating Characteristics Curve

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Authors: Danielle Brister, Yunro Chung
Cited by: 1
References: 29

Abstract

The receiver operating characteristics (ROC) curve has been widely used to evaluate the discrimination performance of biomarkers, but it has been criticized for overlooking their underlying distributions. In this paper, we propose a continuous version of the ROC curve that can assess not only the discrimination performance of biomarkers but also their continuity performance. Our method summarizes the biomarker values as conditional tail expectations at varying thresholds and compare them with true positive and false positive rates. The proposed method is particularly useful for an early phase of biomarker study that enrolls heterogeneous disease populations. Analysis of data from an ovarian cancer biomarker study illustrates the practical utility of the proposed method over the standard ROC curve analysis. The proposed methods are implemented in the R package varoc.

Fields of Study & Subjects

Sepsis Diagnosis and Treatment AI in cancer detection Ovarian cancer diagnosis and treatment

Publication details

Journal / source
Journal of Data Science
Publisher
School of Statistics, Renmin University of China
Pages
1–18
Publication date
1 January 2026
Language
EN