Risk factors for liver cirrhosis in chronic hepatitis B patients with high metabolic risks and establishment of a predictive model
- VernacularTitle:高代谢风险慢性乙型肝炎患者发生肝硬化的影响因素分析及预测模型构建
- Author:
Yuping ZOU
1
;
Li YAO
1
;
Jun ZOU
1
;
Liwei LI
1
;
Fuqing CAI
1
;
Jiean HUANG
1
Author Information
- Publication Type:Journal Article
- Keywords: Hepatitis B， Chronic; High Metabolic Risk; Liver Cirrhosis; Root Cause Analysis; Nomograms
- From: Journal of Clinical Hepatology 2025;41(6):1105-1112
- CountryChina
- Language:Chinese
- Abstract: ObjectiveTo investigate the main risk factors for liver cirrhosis in chronic hepatitis B （CHB） patients with high metabolic risk， to establish a noninvasive predictive model， and to compare the diagnostic efficiency of this model and other models including fibrosis-4 （FIB-4）， aspartate aminotransferase-to-platelet ratio index （APRI）， gamma-glutamyl transpeptidase-to-platelet ratio （GPR）， and Forns index. MethodsA total of 527 CHB patients with high metabolic risks who were admitted to The Second Affiliated Hospital of Guangxi Medical University from September 1， 2017 to October 31， 2022 were enrolled as subjects， and they were randomly divided into modeling group with 368 patients and validation group with 159 patients at a ratio of 7∶3. The LASSO regression analysis and the multivariate Logistic regression analysis were performed for the modeling group to identify independent risk factors， and a nomogram model was established. The receiver operating characteristic （ROC） curve， the calibration curve， and the decision curve analysis were used to validate the nomogram prediction model in the modeling group and the validation group and assess its discriminatory ability， calibration， and clinical practicability. The Delong test was used to compare the area under the ROC curve （AUC） of the nomogram prediction model and other models. ResultsThe multivariate Logistic regression analysis showed that prealbumin （odds ratio ［OR］ = 0.993， 95% confidence interval ［CI］： 0.988 — 0.999， P= 0.019）， thrombin time （OR=1.182， 95% CI： 1.006 — 1.385， P=0.047）， log10 total bilirubin （TBil） （OR=1.710， 95%CI： 1.239 — 2.419， P=0.001）， and log10 alpha-fetoprotein （AFP） （OR=1.327， 95%CI： 1.052 — 1.683， P=0.018） were independent influencing factors for liver cirrhosis in CHB patients with high metabolic risks. A nomogram model for risk prediction was established based on the multivariate analysis， which had an AUC of 0.837 （95%CI： 0.788 — 0.888）， a specificity of 73.5%， and a sensitivity of 84.7%， as well as a significantly higher diagnostic efficiency than the models of FIB-4 （0.739）， APRI （0.802）， GPR （0.800）， and Forns index （0.709） （Z=2.815， 2.271， 1.989， and 2.722， P=0.005， 0.017， 0.045， and 0.006）. ConclusionThe nomogram model established based on prealbumin， thrombin time， log10 TBil， and log10 AFP has a certain clinical application value.
