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Title: Score model for predicting acute-on-chronic liver failure risk in chronic hepatitis B.
Author: Gao FY, Liu Y, Li XS, Ye XQ, Sun L, Geng MF, Wang R, Liu HM, Zhou XB, Gu LL, Liu YM, Wan G, Wang XB.
Journal: World J Gastroenterol; 2015 Jul 21; 21(27):8373-81. PubMed ID: 26217089.
Abstract:
AIM: To establish a clinical scoring model to predict risk of acute-on-chronic liver failure (ACLF) in chronic hepatitis B (CHB) patients. METHODS: This was a retrospective study of 1457 patients hospitalized for CHB between October 2008 and October 2013 at the Beijing Ditan Hospital, Capital Medical University, China. The patients were divided into two groups: severe acute exacerbation (SAE) group (n = 382) and non-SAE group (n = 1075). The SAE group was classified as the high-risk group based on the higher incidence of ACLF in this group than in the non-SAE group (13.6% vs 0.4%). Two-thirds of SAE patients were randomly assigned to risk-model derivation and the other one-third to model validation. Univariate risk factors associated with the outcome were entered into a multivariate logistic regression model for screening independent risk factors. Each variable was assigned an integer value based on the regression coefficients, and the final score was the sum of these values in the derivation set. Model discrimination and calibration were assessed using area under the receiver operating characteristic curve and the Hosmer-Lemeshow test. RESULTS: The risk prediction scoring model included the following four factors: age ≥ 40 years, total bilirubin ≥ 171 μmol/L, prothrombin activity 40%-60%, and hepatitis B virus DNA > 10(7) copies/mL. The sum risk score ranged from 0 to 7; 0-3 identified patients with lower risk of ACLF, whereas 4-7 identified patients with higher risk. The Kaplan-Meier analysis showed the cumulative risk for ACLF and ACLF-related death in the two risk groups (0-3 and 4-7 scores) of the primary cohort over 56 d, and log-rank test revealed a significant difference (2.0% vs 33.8% and 0.8% vs 9.4%, respectively; both P < 0.0001). In the derivation and validation data sets, the model had good discrimination (C index = 0.857, 95% confidence interval: 0.800-0.913 and C index = 0.889, 95% confidence interval: 0.820-0.957, respectively) and calibration demonstrated by the Hosmer-Lemeshow test (χ (2) = 4.516, P = 0.808 and χ (2) = 1.959, P = 0.923, respectively). CONCLUSION: Using the scoring model, clinicians can easily identify patients (total score ≥ 4) at high risk of ACLF and ACLF-related death early during SAE.

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