ORIGINAL RESEARCH article
Front. Med.
Sec. Hepatobiliary Diseases
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1650584
This article is part of the Research TopicDigital Technologies in Hepatology: Diagnosis, Treatment, and Epidemiological InsightsView all 12 articles
Risk Factor Analysis and Nomogram Development for Advanced-Stage Hepatic Fibrosis in Patients with Wilson's Disease
Provisionally accepted
Jiafeng Zhou1
Zuolong Li2Junwei Wang1
Zhen zhen Jiang1Tao Wang1Tianyu Xie1Liangchen Wang1Shuai Kang1
Zhuang Tao3*Meixia Wang3- 1Anhui University of Chinese Medicine, Hefei, China
- 2Anhui Agricultural University, Hefei, China
- 3The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China
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Purpose: To investigate the risk factors for advanced-stage hepatic fibrosis in Wilson's disease (WD), and developed a predictive nomogram to screen high risk patients with WD for early prevention and intervention. Methods: We retrospectively analyzed clinical data from WD in The First Affiliated Hospital of Anhui University of Chinese medicine between January 2010 and December 2024. Patients were divided into advanced hepatic fibrosis and non-advanced fibrosis groups according liver stiffness measurement. Identification of the independent risk factors for advanced hepatic fibrosis in WD was conducted through univariate and multivariate Cox regression analyses, followed by the construction of the clinical predictive model. The discriminative power, calibration, and clinical utility of the model were validated by receiver operating characteristic, calibration curves, and decision curve analysis.Results: The study cohort comprised 221 patients. Notably, CER, LN, HDL-C, TG, PLT, SEX, and Apo-A1 were identified as independent risk factors for advanced hepatic fibrosis in WD patients undergoing long-term maintenance therapy. The C-index demonstrated excellent discriminative capacity (training cohort: AUC values of 0.918 at 36 months, 0.914 at 60 months, and 0.935 at 84 months; validation cohort: AUC values of 0.906, 0.917, and 0.888 at corresponding time points). Calibration curves exhibited strong alignment between predicted and observed outcomes. The DCA quantified clinical benefit probability thresholds across varying time intervals. Conclusions: The nomogram predictive model demonstrated high accuracy and provides a practical tool for the early identification and risk prediction of advanced hepatic fibrosis in WD patients undergoing long-term maintenance therapy.
Keywords: Wilson's Disease, predictive model, advanced hepatic fibrosis, Risk factors, Retrospective study
Received: 20 Jun 2025; Accepted: 16 Jul 2025.
Copyright: © 2025 Zhou, Li, Wang, Jiang, Wang, Xie, Wang, Kang, Tao and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Zhuang Tao, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China
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