COMPARATIVE SURVIVAL MODELS OF PATIENTS WITH CHRONIC HEPATITIS B: A CASE STUDY AT THE FEDERAL MEDICAL CENTRE, NGURU - Bala Doma, Ahmad; Muhammad Auwal, Abubakar; Obini Nwaze, Nweze; Ibrahim Musa, Saleh (FUDMA Journal of Sciences, 2025)
Chronic Hepatitis B Virus (HBV) infection is a leading cause of cirrhosis and hepatocellular carcinoma worldwide, with a particularly high burden in Nigeria. Identifying prognostic factors and selecting the best-fitting survival model are critical for improving patient outcomes. A study of 150 patients with chronic HBV managed at Federal Medical Centre, Nguru, between 2019 and 2024 was analyzed. Survival probabilities were estimated using the Kaplan–Meier method. The Cox proportional hazards (CPH) model and four Accelerated Failure Time (AFT) models. Exponential, Weibull, Log-logistic, and Lognormal models were fitted and compared using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Covariates included age at diagnosis, gender, METAVIR fibrosis stage, baseline AST and ALT levels, viral load, comorbidities, and antiviral therapy.The Kaplan–Meier curve revealed a gradual decline in survival. Model selection criteria identified the Lognormal AFT model as the best fit (AIC = 71.52; BIC = 101.63), outperforming both the Cox model and other parametric models. Significant predictors of reduced survival included older age (TR = 0.99, p < 0.01), advanced fibrosis (TR = 0.24, p < 0.001), elevated AST and ALT levels (p < 0.05), and comorbidities (TR = 0.26, p < 0.001). Antiviral therapy was strongly protective, increasing survival time by more than fourfold (TR = 4.01, p < 0.001). The Lognormal AFT model provides the most reliable characterization of survival among chronic HBV patients. Early diagnosis, fibrosis staging, and timely initiation of antiviral therapy are essential for improving survival outcomes and reducing HBV-related mortality in Northern Nigeria.
Keywords: Chronic Hepatitis B; Survival Analysis; Accelerated Failure Time Models; Lognormal Model