The establishment of a predictive model for hepatic encephalopathy secondary to chronic hepatitis B-related cirrhosis based on LASSO regression

Abstract

Abstract: Objective This study aims to establish a predictive model for hepatic encephalopathy secondary to chronic hepatitis B-related cirrhosis using LASSO regression analysis. Methods The study population consisted of 189 patients with chronic hepatitis B-related cirrhosis admitted from January 2022 to January 2024. Patients with hepatic encephalopathy were designated as the observation group, while the others were served as the control group. The baseline data and biochemical indices of all patients were collected and compared between the two groups. LASSO-logistic regression analysis was employed to identify the predictive factors for hepatic encephalopathy and construct a predictive mode. The model′s fit was evaluated using the akaike information criterion (AIC) and bayesian information criterion (BIC), comparing the traditional logistic and LASSO-logistic regression models, and validated by calibration curves. Results Among the 189 patients with hepatitis B-related cirrhosis, 32.28% (61/189) developed hepatic encephalopathy. The baseline data of patients in the observation group were as the following: age (56.2±7.2) years, alanine aminotransferase (ALT) (32.15±4.51) U/L, aspartate aminotransferase (AST) (46.72±5.48) U/L, total bilirubin (TBil) (40.01±5.53) μmol/L, alkaline phosphatase (ALP) (95.67±10.28) U/L, blood ammonia (51.03±7.34) μmol/L, and model for end-stage liver disease (MELD) score (10.13±2.54), all of which were higher than those of (53.0±4.5) years, (28.83±4.10) U/L, (40.88±5.11) U/L, (28.78±5.11) μmol/L, (89.14±9.77) U/L, (30.28±5.93) μmol/L, and (7.23±8.205), respectively, in patients of the control group. Additionally, the levels of hemoglobin (Hb) and albumin (Alb) were lower than those of the observation group, with statistically significant differences (P<0.05). According to LASSO-logistic regression analysis, advanced age, high blood ammonia, high MELD score, and low albumin (Alb) were identified as independent risk factors for the development of hepatic encephalopathy. The AIC and BIC values for the LASSO-logistic regression model were 20.221 and 39.672, respectively, indicating a good fit of the model. Conclusion The LASSO-logistic regression model, based on the selected variables, shows good fit and predictive accuracy for assessing hepatic encephalopathy in patients with chronic hepatitis B-related cirrhosis.

Key words: Chronic hepatitis B-related cirrhosis, Hepatic encephalopathy, LASSO regression analysis, Risk factor analysis

YE Xiao-xin, LI Wei, GAO Yu-feng, XIAO An-ling, LIU Nan-nan. The establishment of a predictive model for hepatic encephalopathy secondary to chronic hepatitis B-related cirrhosis based on LASSO regression[J]. Chinese Hepatolgy, 2026, 31(2): 172-176.

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