Identification of Chronic Hepatitis B Patients without Significant Liver Fibrosis by a Simple Noninvasive Predictive Model

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Abstract
Histological assessment of liver fibrosis is important in the management of chronic hepatitis B (CHB) infection but poorly accepted by patients because of its invasiveness. The aim of this study was to develop a noninvasive model to assess liver fibrosis in CHB patients using clinical and routine laboratory data. This was a retrospective study on 235 treatment-naïve viremic CHB patients. Univariate analysis of data from the training cohort (n = 150) followed by multivariate logistic regression were performed to identify independent predictors of significant fibrosis and generate predictive models. The models were validated with the remaining patients or validation cohort (n = 85) and by receiver operating characteristics (ROC) analysis. Body mass index (BMI), platelet count, serum albumin, and total bilirubin levels were identified as independent predictors of bridging fibrosis or cirrhosis (Ishak stage 3–6). ROC analysis was performed using the predictive probabilities derived from the regression models. The area under the ROC curve of the best model was 0.803 (95% CI: 0.729–0.878) for the training cohort, 0.765 (95% CI: 0.644–0.885) for the validation cohort, and 0.791 (95% CI: 0.728–0.854) for the entire cohort. Using the low cut-off probability of 0.15, significant fibrosis could be excluded in 83 patients of the total patient population (negative predictive value 0.92). Our noninvasive model comprising BMI and three routine laboratory tests was accurate in predicting absence of significant fibrosis. Application of this model could provide useful additional information on the stage of disease, guide future management decisions, and potentially decrease the need for liver biopsy in some CHB patients.