Estimation of Volume Under Receiver Operating Characteristic Surface and Asymptotic Variance for Diagnostic Classifier Following Log-Normal Distribution
,
Abstract
Introduction: Clinical diagnosis highlights the essential need to assess biomarker performance for effective disease
screening and diagnosis. The Receiver Operating Characteristic (ROC) curve serves as a fundamental tool for assessing
and interpreting biomarker effectiveness. Numerous models and techniques have been developed to analyze biomarkers
in binary classification settings (Non-Diseased vs. Diseased). This research article seeks to expand the binary classification
framework to a three-class scenario, incorporating Diseased, Suspicious, and Non-Diseased categories under a Log-Normal
distribution.
Methods: It introduces a three-class Log-Normal ROC model based on a Parametric approach, deriving metrics such as
Volume Under the ROC Surface (VUS) and Asymptotic Variance, as well as an alternative Non-Parametric approach. The
model was validated using simulated data generated for the underlying distribution, and a real-life dataset was used to fit
the VUS and ROC curves.
Results: The simulation study was conducted using four sets with varying parameters. In the fourth set, the Non-Parametric
VUS (0.9966) exceeded the Parametric VUS (0.8058), though the difference was smaller compared to the other sets. The
low Standard Error (SE) (0.0472) across all sets indicates high precision in the estimates. Additionally, for the real-life (The
multiple sclerosis (ms) disease) dataset the VUS value is 0.6782 which gives moderate fit of the model.
Conclusion: In this study, we derived the asymptotic variance and VUS for the Log-Normal distribution using simulated
data with varying parameters. The analysis compares diagnostic performance across parameter sets, highlighting the
superiority of Non-Parametric VUS over Parametric VUS. Set 4 demonstrated the highest reliability with the lowest standard
error (SE = 0.0472). The real-life MS dataset provided a moderate fit to the proposed model.
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| Issue | Vol 11 No 3 (2025): . | |
| Section | Articles | |
| Keywords | ||
| Biomarker Gold Standard Three class classification Receiver Operating Characteristics Volume Under the ROC Surface and Asymptotic variance | ||
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