BACKGROUND AND AIM: Clinically applicable models to predict hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB) response to peginterferon (PEG-IFN) are scarce. This study aimed to develop simple scoring systems, based on multiple parameters, for predicting sustained HBeAg seroconversion to PEG-IFN. METHODS: Eighty-five treatment-naïve patients with HBeAg-positive CHB underwent 52-week PEG-IFN treatment and 24-week follow-up. Logistic regression analysis assessed parameters at baseline and weeks 12, 24, and 52 to predict HBeAg seroconversion at week 24 off-treatment. The best three predictors at each time point were included in prediction models of PEG-IFN therapy efficacy. RESULTS: The three most meaningful predictors were alanine aminotransferase (ALT) > 5 × ULN, HBeAg ≤ 500 S/CO, and antibody to hepatitis B core antigen (anti-HBc) > 10.7 S/CO at baseline; HBeAg ≤ 20 S/CO, anti-HBc > 11.7 S/CO, and HBeAg decline > 1 log10 S/CO at week 12; ALT > 2 × ULN, HBeAg ≤ 15 S/CO, and anti-HBc > 10.4 S/CO at week 24; HBeAg ≤ 5 S/CO, anti-HBc > 11.1 S/CO, and hepatitis B virus DNA decline > 2 log10 copies/mL at week 52. Parameters meeting optimal cutoff thresholds were scored 1 or otherwise scored 0. For total scores of 0 versus 3 at baseline and weeks 12, 24, and 52, response rates were 6.3%, 12.5%, 0%, and 0% versus 90.0%, 83.3%, 76.9%, and 86.4%, respectively. CONCLUSIONS: We successfully established prediction models for PEG-IFN response in HBeAg-positive CHB.
BACKGROUND AND AIM: Clinically applicable models to predict hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB) response to peginterferon (PEG-IFN) are scarce. This study aimed to develop simple scoring systems, based on multiple parameters, for predicting sustained HBeAg seroconversion to PEG-IFN. METHODS: Eighty-five treatment-naïve patients with HBeAg-positive CHB underwent 52-week PEG-IFN treatment and 24-week follow-up. Logistic regression analysis assessed parameters at baseline and weeks 12, 24, and 52 to predict HBeAg seroconversion at week 24 off-treatment. The best three predictors at each time point were included in prediction models of PEG-IFN therapy efficacy. RESULTS: The three most meaningful predictors were alanine aminotransferase (ALT) > 5 × ULN, HBeAg ≤ 500 S/CO, and antibody to hepatitis B core antigen (anti-HBc) > 10.7 S/CO at baseline; HBeAg ≤ 20 S/CO, anti-HBc > 11.7 S/CO, and HBeAg decline > 1 log10 S/CO at week 12; ALT > 2 × ULN, HBeAg ≤ 15 S/CO, and anti-HBc > 10.4 S/CO at week 24; HBeAg ≤ 5 S/CO, anti-HBc > 11.1 S/CO, and hepatitis B virus DNA decline > 2 log10 copies/mL at week 52. Parameters meeting optimal cutoff thresholds were scored 1 or otherwise scored 0. For total scores of 0 versus 3 at baseline and weeks 12, 24, and 52, response rates were 6.3%, 12.5%, 0%, and 0% versus 90.0%, 83.3%, 76.9%, and 86.4%, respectively. CONCLUSIONS: We successfully established prediction models for PEG-IFN response in HBeAg-positive CHB.