Establishment Of A Noninvasive Liver Histology Model Of Chronic Hepatitis B With Alanine Aminotransferase ≤ 2 Times The Upper Limit Of Normal

Objective: Currently,liver biopsy is the “gold standard” for evaluating liver histology.However,it is an invasive test with its own limitations.In recent years,most studies have focused on the evaluation of non-invasive predictive models.This study aimed to explore non-invasive predictors of liver histology in chronic hepatitis B（CHB）patients with alanine aminotransferase（ALT）≤ 2 times the upper limit of normal（ULN）to determine whether to initiate antiviral therapy.Method: This study retrospectively analyzed 720 patients with CHB who underwent liver biopsy with ALT≤ 2ULN.These patients were randomly divided into training and validation sets.Independent predictors of liver necro-inflammation and liver fibrosis were screened out by univariate and multivariate regression analysis.A predictive model was constructed in the training set based on the above serological indictors to predict the severity of liver histology,which was then validated in the validation set.Results: Aspartate aminotransferase（AST）,prothrombin time（PT）,glutamyl transpeptidase（GGT）and core antibody（Anti-HBC）were identified as independent predictors of moderate to severe（G≥2）necrotizing inflammation in the CHB with ALT≤ 2ULN.A non-invasive prediction model was constructed based on AST、PT、GGT and Anti-HBC.The area under curve of the model in the training set was 0.767,the area under curve in the validation set was 0.714.The prediction effect of the combined factors was higher than that of each independent predictor.A non-invasive predictive model was constructed based on AST、GGT and Anti-HBC.The model is of great significant for identifying significant liver inflammation and liver fibrosis,and the predictive effect of the model is higher than that of each independent predictor.Conclusion: AST,PT,GGT and Anti-HBC were independent predictors of significant liver inflammation and AST、GGT and Anti-HBC identified significant liver inflammation and liver fibrosis in the CHB patients with ALT≤ 2ULN.A non-invasive predictive model was constructed based on each independent index,and its diagnostic performance was better than that of each independent predictor to determine whether to start antiviral therapy.