Lung Cancer Survival Analysis: A Comparative Evaluation of Cox Proportional Hazards and Accelerated Failure Time Models: An Analytical Study

Abstract

Objective: This study aims to evaluate and compare the Cox Proportional Hazards (PH) model and Accelerated Failure Time (AFT) models in the survival analysis of lung cancer patients. The analysis focuses on survival times across different cell types, prior therapies, and treatment groups. Material and Methods: The study was conducted using a dataset containing survival times, censoring indicators, and variables such as cell type, prior therapy, and treatment group. The Cox PH model and 3 AFT models (Weibull, Log-Normal, Log-Logistic) were applied. While the Cox PH model does not assume a specific distribution for survival times, AFT models assume parametric distributions. Model performance was evaluated using the Akaike Information Criterion (AIC). Results: The Smallcell type was identified as the most aggressive cancer type, with the lowest survival probability. AFT models, particularly the Weibull AFT model, provided a better fit to the data than the Cox PH model, as indicated by lower AIC values. Prior therapy was associated with lower survival probabilities, suggesting higher risk among these patients. The standard treatment group showed slightly better survival over time. Conclusion: This study highlights the importance of selecting an appropriate survival analysis model based on the characteristics of lung cancer data. While the Cox PH model offers flexibility, the Weibull AFT model provided better insights and fit. These findings emphasize the critical role of model selection in accurately understanding and predicting patient outcomes in lung cancer survival analysis. © 2025 by Türkiye Klinikleri.