Establishment of a multi-parameter prediction model for the functional cure of HBeAg-negative chronic hepatitis B patients treated with pegylated interferonα and decision process based on response-guided therapy strategy

Abstract

Abstract Background & Aims: This study aimed to establish multivariate prediction models according to a response-guided therapy (RGT) based strategy at baseline and week 12 and 24 of follow-up to predict the functional cure for HBeAg-negative patients with chronic hepatitis B (CHB) treated with pegylated interferonα (PEG-IFNα). Methods: A total of 242 HBeAg-negative patients with CHB were treated with PEG-IFNα for 52 weeks and followed up for 24 weeks. Responses at the end of follow-up (EOF) were defined as hepatitis B surface antigen (HBsAg) loss, and patients were defined as either responders or non-responders. Results: The three most meaningful predictors were an age ≤40 years,alanine aminotransferase (ALT) levels ≤40 U/L, and HBsAg levels ≤100 IU/mL at baseline; ALT levels ≥80 U/L, anti-HBc levels ≤8.42 S/CO, and HBsAg levels ≤50 IU/mLat week 12; and ALT levels ≥40 U/L, anti-HBc levels ≤8.46 S/CO, and HBsAg levels ≤0.2 IU/mL at week 24. The response rates of patients with a score of 0–1 and 4–5 at baseline, week 12, and 24 were 13.5%, 7.8%, and 11.7%; and 63.6%, 68.1%, and 98.1%, respectively. At week 12, the cumulative scores were 0–2, 3–4, 5–7, and 8–10 (response rates 5.0%, 18.9%, 41.3%, and 71.4%, respectively). At week 24, the cumulative scores were 0–3, 4–6, 7–10, and 11–15 (response rates: 1.3%, 12.3%, 37.0%, and 92.5%, respectively). Conclusion: We established a multi-parameter prediction model for the functional cure of HBeAg-negative patients with CHB treated with PEG-IFNα.