A Novel Prediction Model for Risk of Acute-on-Chronic Liver Failure in Chronic Hepatitis B Virus-Infected Patients With Flare of Hepatitis

Abstract

Background: Chronic patients with flare of hepatitis B virus (HBV) may progress to acute-on-chronic liver failure (ACLF), which is characterized by high mortality. Uniform models to predict risk of ACLF are lacking. We aimed to present an accurate risk prediction model that incorporates clinical manifestations and laboratory results in chronic HBV-infected patients with flare of hepatitis. Methods: We selected the best variable combination using recursive feature elimination (RFE) from a perspective cohort including 360 patients with hepatitis flare at the Third Affiliated Hospital of Sun Yat-sen University to develop a risk prediction model and nomogram scoring system, then validated the model using two external independent sets consisting of 96 and 65 individuals, and compared its performance with End-Stage Liver Disease (MELD) score model. Findings: An excellent prediction model called the PAT model using the five final identified predictors including prothrombin time (PT), total bilirubin (TBil), ascites, pneumonia and hemoglobin (HGB) was constructed. The model could achieve an Area under the Receiver Operating Characteristic curve (AUROC) of 0.964 (95% confidence interval [CI]: 0.949-0.980) in the development set and performed well in external validation cohorts (validation cohort 1, AUROC = 0.909, 95% CI 0.840-0.977; validation cohort 2, AUROC = 0.898, 95% CI 0.813-0.983, both of which were significantly higher than the MELD score model (P <0.001). Interpretation: The easy-to-use PAT model can accurately predict the risk of ACLF risk in chronic hepatitis B patients with flare of hepatitis, which is expected to become a widely accepted prediction model and guide therapeutic options. Funding Statement: This work was supported by a grant for National Key RD National Natural Science Foundation of China (81773176); Science and Technology Program of Guangzhou (201804010474); the 5010 Project of Clinical Research in Sun Yat-sen University (2016009); Medical Scientific Research Foundation of Guangdong Province (A2017118); Major Science and Technology Projects in 13th Five-Year (2018ZX10715004-001-09); Natural Science Foundation of Guangdong (2018A030310272); Guangdong basic and Applied Basic Research Foundation (2019A1515110166) ; Guangdong Medical Science and Technology Research Fund (A2018366); 3rd Affiliated Hospital of Sun Yat-Sen University, Clinical Research Program (P000-277) and Meizhou Science and Technology Project (2019B0203003). Declaration of Interests: The authors declare that they have no competing interests. Ethics Approval Statement: The study was approved by the institutional ethics committee of the Third Affiliated Hospital of Sun Yat-sen University.