A Noninvasive Model to Predict Liver Histology for Antiviral Therapy Decision in Chronic Hepatitis B with Alanine Aminotransferase＜2 Upper Limit of Normal

Abstract

Background and Aim: Although liver biopsy is currently the gold standard to evaluate liver histology, it has many limitations, such as sampling error, cost and risk of complications. This study aims to construct a noninvasive model to predict liver histology for antiviral therapy in chronic hepatitis B (CHB) with alanine aminotransferase (ALT)＜2 times upper limit of normal(ULN).Methods: We retrospectively analyzed 577 patients with CHB who received liver biopsy and whose ALT was less than 2 ULN. Then they were randomly divided into a training group and a validation group. Through logistic regression analysis, a novel predictive model was constructed in the training group to predict significant changes in liver histology [necro-inflammatory activity grade (G) ≥2 or fibrosis stage (S) ≥2] and then validated in the validation group.Results: If liver biopsy showed moderate or severe inflammation or significant fibrosis, antiviral treatment was recommended. Aspartate aminotransferase (AST), anti-hepatitis B virus core antibody (anti-HBC) and glutamine transpeptidase (GGT) were identified as independent predictors for antiviral therapy, with area under the ROC curve (AUROC) of 0.649, 0.647 and 0.616, respectively. Our novel model index, which combined AST, anti- HBC and GGT with AUROC of 0.700 and 0.742 in estimation set and validation set.Conclusions: This study established a noninvasive model to predict liver histology for antiviral treatment decision in patients with CHB with ALT < 2 ULN, which can reduce the clinical needs of liver biopsy.

A noninvasive model discriminating significant histological changes in treatment-naive chronic hepatitis B patients with normal ALT

“…A noninvasive [29]. AGH model composed of AST, hepatitis B core antigen and GGT is a reliable index to predict moderate to severe inflammation or significant fibrosis, which helps to determine the initiation of antiviral therapy [30]. But the predictive value of our model is better than AGH model.…”

Correction to: A noninvasive model to predict liver histology for antiviral therapy decision in chronic hepatitis B with alanine aminotransferase < 2 upper limit of normal

“…Following publication of the original article [ 1 ], the authors identified incorrect corresponding author mentioned. Correct corresponding author is Haijun Huang.…”