Establishment and validation of new predictive model for immune tolerance stage of chronic HBV infection based on liver histopathological changes

Objective To modify more accurate clinical and viral indicators and establish the new model for differentiating the different stages of chronic hepatitis B virus (HBV) infection based on liver histopathological changes. Methods The clinical and liver pathology data of chronic hepatitis B (CHB) patients undergoing liver biopsy were collected for retrospective analysis in the test and validation group. The area under the curve (AUC) of the receiver operating characteristic (ROC) was used to evaluate the diagnostic value for differentiating the different stages of chronic HBV infection. Results A total of 118 patients and 73 patients who met the diagnostic and exclusion criteria were selected as the test group and validation group. Multivariate analysis showed that HBeAg independently correlated with the IT and IC stages. The cutoff value of HBeAg used to quantitatively differentiate between IT and IC was 1335 and the AUC was 0.921 (95% confidence interval (CI): 0.836 to 0.971). A new prediction model of IT stage was established by using three indicators including HBeAg, HBsAg and HBV DNA. The AUC is 92.3% (95% CI: 86.4-98.2, P<0.001) using this prediction model. The sensitivity and specificity are 85.5% and 95.2%. Conclusions The high levels of HBeAg rather than HBeAg positive might help to identify patients with the “true” IT stage. A predictive model for immune tolerance stage are established by combining three indicators. The new prediction model has significantly reduced the error rate compared with others standards.