Comparative Study of Cox Proportional Hazard and Accelerated Failure Time Models on Survival of Diabetes Mellitus and Hypertension Patients

Comparative analysis of survival models for hypertension and diabetics carried out in this study. The study compared the performance of Cox Proportional Hazard (CPH) and Accelerated Failure Time (AFT) models with and without random effects in analyzing hypertension and diabetes survival data obtained from General Hospital Keffi and General Hospital Nasarawa for the period of five years (2018-2022). Models evaluated include CPH, AFT (Exponential, Weibull, Log-Logistic) and their corresponding random effect counterparts. The Weibull AFT random effect model outperformed all other models in terms of goodness-of-fit, predictive accuracy and interpretability. This model accounted for individual heterogeneity and clustering effects, providing a more nuanced understanding of risk factors’ impact on survival rates. The Weibull AFT random effects model is the most suitable choice for analyzing hypertension and diabetes survival data, offering improved predictive power and insight into the complex relationships between risk factors and time-to-event outcomes. These findings have significant implications for healthcare professionals, policymakers, and researchers seeking to optimize survival analysis methodologies.