A nomogram prediction model for assessing the risk of cirrhosis in patients with chronic hepatitis B based on Lasso regression
10.3760/cma.j.cn114452-20231221-00369
- VernacularTitle:基于Lasso回归构建慢性乙型肝炎患者发生肝硬化风险的列线图预测模型
- Author:
Peng JIANG
1
;
Haiyan DENG
;
Tiantian PENG
;
Xiuru GUAN
Author Information
1. 哈尔滨医科大学附属第一医院检验科，哈尔滨150000
- Keywords:
Hepatitis B, chronic;
Liver cirrhosis;
Prediction model
- From:
Chinese Journal of Laboratory Medicine
2024;47(8):902-909
- CountryChina
- Language:Chinese
-
Abstract:
Objective:Employ Lasso regression to develop a nomogram model for predicting the risk of liver cirrhosis in patients with chronic hepatitis B (CHB).Methods:A retrospective analysis was conducted on age, gender, laboratory test results, and liver ultrasound results of 1218 patients diagnosed with CHB at the First Affiliated Hospital of Harbin Medical University between 1 January 2023 and 30 November 2023. Based on the R caret package, patients were divided into a training set ( n=853) and an internal validation set ( n=365) at a ration of 7∶3, and an additional 185 patients with CHB treated at the First Affiliated Hospital of Harbin Medical University Qunli campus during the same period was included as an external validation set. Lasso regression and multiple logistic regression were employed for variable selection and nomogram model construction. The discriminative ability, calibration, and clinical utility of the prediction model were evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, Decision Curve Analysis (DCA), respectively. Results:Age, platelet, gamma-glutamine transpeptidase, prealbumin, portal vein diameter, and spleen thickness were selected as predictive variables for the occurrence of liver cirrhosis in CHB patients ( P<0.05), and a nomogram model was constructed based on the aforementioned variables. The AUC values for the ROC curves in the internal validation set and external validation set were 0.934 (95% CI 0.910-0.959) and 0.881 (95% CI 0.820-0.942), respectively. The fitting degree of calibration curve was observed in both sets (Internal validation set P=0.881; External validation set P=0.478). DCA curves demonstrated the high clinical utility of the model. Conclusion:Age, platelet, gammaglutamine transpeptidase, prealbumin, portal vein diameter, and spleen thickness were risk factors for the occurrence of liver cirrhosis in CHB patients. The constructed nomogram model exhibits good predictive value and clinical utility.
