Development and Validation of Models to Predict Functional Cure in Patients With CHB After Peg-IFN Based Therapy

Hepatitis B virus (HBV) infection is prevalent across the world. Functional cure is the optimal endpoint of antiviral therapy for chronic hepatitis B virus (HBV) infection. Currently available anti-HBV therapy includes nucleoside analogs (NAs) and peginterferon-α (Peg-IFNα). Combination of Peg-IFNα and NAs, each with different mechanisms of action, is an attractive approach for treating chronic HBV infection. In this study, we aim to establish logistic regression models to predict durable functional cure in patients with CHB treated by combination of Peg-IFNα and NAs, which might be useful for clinical physicians to make personalized treatment decisions. These models will be constructed using baseline routine clinical laboratory indicators with high diagnostic accuracy. These models might be widely applicable to almost all medical institutions and will effectively promote the application of Peg IFN α plus NAs therapy in clinical work. The findings in this study might greatly improve the functional cure rate of CHB and reducing the incidence rate and mortality of HBV related end-stage liver diseases.