Huang YS, Gao W, Sun AJ, Pu CW, Xu SS. Clinical characteristics of patients with hepatitis and cirrhosis and the construction of a prediction model. World J Hepatol 2025; 17(2): 96506 [DOI: 10.4254/wjh.v17.i2.96506]
Corresponding Author of This Article
Ai-Jun Sun, Doctor, Dean, Department of Infectious Diseases, Dalian Public Health Clinical Center, No. 269 Huibai Road, Lu Gang, Ganjingzi District, Dalian 116031, Liaoning Province, China. 2244518005@qq.com
Research Domain of This Article
Infectious Diseases
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Yu-Shuang Huang, Ai-Jun Sun, Shuang-Shuang Xu, Department of Infectious Diseases, Dalian Public Health Clinical Center, Dalian 116031, Liaoning Province, China
Wei Gao, Department of Gastroenterology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, Liaoning Province, China
Chun-Wen Pu, Dalian Public Health Clinical Center, Dalian Municipal Research Institute for Public Health, Dalian 116031, Liaoning Province, China
Co-first authors: Yu-Shuang Huang and Wei Gao.
Author contributions: Huang YS contributed to data management, manuscript preparation, software, visualization, survey; Gao W contributed to conceptualization, methodology, and validation; Xu SS and Pu CW contributed to data management; Sun AJ contributed to conceptualization, methodology, writing-review and editing, validation.
Supported by the “Climbing Program” Construction Project “High Peak Project” Department of Major Infectious Disease Prevention and Control.
Institutional review board statement: This study was reviewed by the Ethics Committee of Dalian Public Health Clinical Center, No. 2023-021(KY)-001.
Informed consent statement: The data used in this study are from the biological sample data resource library of Dalian Public Health Clinical Center. All have signed the broad informed consent form.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: All data used or analyzed during this study are included in this article and its supplementary information files.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ai-Jun Sun, Doctor, Dean, Department of Infectious Diseases, Dalian Public Health Clinical Center, No. 269 Huibai Road, Lu Gang, Ganjingzi District, Dalian 116031, Liaoning Province, China. 2244518005@qq.com
Received: May 8, 2024 Revised: September 30, 2024 Accepted: January 2, 2025 Published online: February 27, 2025 Processing time: 287 Days and 14.6 Hours
Abstract
BACKGROUND
Hepatitis B-associated cirrhosis is an important disease burden in China. However, there is a lack of effective predictors in clinical practice to drive delivery and enable early treatment to delay disease progression.
AIM
To analyzing the clinical characteristics of patients with hepatitis and cirrhosis, the nomogram model was established and validated.
METHODS
The clinical data of 1070 patients with hepatitis B who were treated in our hospital from October 2015 to July 2022 were collected. In a 7:3 ratio, 749 cases were divided into training cohorts and 321 cases were divided into validation cohorts. In addition, the training cohort and validation cohort were further divided into hepatitis group and hepatitis B-related cirrhosis group based on whether the patient progressed to cirrhosis. Binary logistic regression was used to analyze the influencing factors of hepatitis progression to cirrhosis. A roadmap prediction model was established, and the predictive effect of the model was evaluated by patient-subject receiver operating characteristic curve (ROC), and the effectiveness of the model was evaluated by decision curve analysis.
RESULTS
Binary logistic regression analysis was performed using hepatitis B-related cirrhosis = 1 and hepatitis = 0 as dependent variables, and univariate analysis of serological indicators was used as covariates. The results showed that glutamic oxaloacetate aminotransferase/glutamate acetone aminotransferase levels, prothrombin time activity, and hepatitis B e antigen levels were all contributing factors to the progression of hepatitis to cirrhosis. The area under the ROC curve was 0.693 [95% confidence interval (CI): 0.631 to 0.756] for the training cohort and 0.675 (95%CI: 0.561 to 0.790) for the validation cohort. In addition, the decision analysis curves of the prediction models of both the training cohort and the validation cohort confirmed the effectiveness of the nomogram prediction model.
CONCLUSION
Three independent factors influencing the progression to cirrhosis in patients with hepatitis B were identified. The construction of a nomogram prediction model from hepatitis to cirrhosis has high application value as a tool for predicting the occurrence of liver cirrhosis in hepatitis B patients.
Core Tip: In order to analyze the clinical characteristics of patients with hepatitis and cirrhosis, a nomogram model was established and verified. The clinical records of 1070 patients with hepatitis B who were treated in our hospital were selected for study, and they were divided into 749 cases in the modeling cohort and 321 cases in the model validation cohort in a 7:3 ratio. At the same time, the model validation cohort was divided into hepatitis group (n = 688) and hepatitis cirrhosis group (n = 61), and the model validation cohort was divided into hepatitis group (n = 295) and hepatitis cirrhosis group (n = 26) according to whether the patients had liver cirrhosis. The levels of albumin hepatitis B E antigen, white blood cell, red blood cell, hemoglobin, absolute neutrophil count and absolute lymphocyte count in patients with hepatitis cirrhosis were significantly lower in the modeling cohort than those in patients with hepatitis, while the levels of the ratio of aspartate aminotransferase, plasma prothrombin time, hyaluronic acid, laminin and platelet count were significantly higher than those in patients with hepatitis (all P < 0.05). The area under the receiver operating characteristic curve (AUC) of the nomogram prediction model established by cohort modeling was 0.693 [95% confidence interval (CI): 0.631 to 0.756], and AUC of the nomogram prediction model was 0.675 (95%CI: 0.561 to 0.790). The actual result curves of the nomograms generated by the modeling and validation cohorts deviate from the calibration curves with little tolerance.
