A model to predict antiviral treatment in HB eAg negative chronic hepatitis B with alanine aminotransferase ≤2 upper limit of normal

Background & Aims Liver histological assessment is essential for predicting antiviral therapy in HB eAg negative chronic hepatitis B ( CHB ) patients with serum alanine aminotransferase ( ALT ) ≤2 upper limit of normal ( ULN ). The aim was to establish a model to predict antiviral treatment for those patients without liver biopsy. Methods Three hundred and one consecutive treatment naive HB eAg negative CHB patients with HBV DNA ≥2000 IU/ml and ALT ≤2 ULN were retrospectively enrolled, among which 158 patients were for the training set and 143 for validation set. A multivariate logistic regression model was constructed in the training set and validated in the validation set. Results Our model identified four independent factors for the timing of treatment: Age ( OR 1.050, 95% CI 1.004–1.098), Ln(aspartate aminotransferase) ( OR 17.425, 95% CI 5.394–56.292), Log 10 [ HBV DNA ] ( OR 0.704, 95% CI 0.514–0.963) and platelet ( OR 0.980, 95% CI 0.970–0.990). It showed 94% sensitivity, 88% negative predictive value ( NPV ) in the training set and 93% sensitivity, 85% NPV in the validation set using the low cut‐off point of 5.16. Meanwhile, it showed 92% specificity, 88% positive predictive value ( PPV ) in the training set and 94% specificity, 92% PPV in the validation set using the high cut‐off point of 7.26. It could predict treatment for 179 of 301(59%) patients without biopsy. Conclusions We established a model to predict antiviral therapy in HB eAg negative CHB patients with ALT ≤2 ULN. Antiviral treatment should be initiated if the model value >7.26 and not if its value ≤5.16. Liver biopsy is needed only when its value between the two points.