Survival Analysis of Breast Cancer Patients Using Accelerated Failure Time (AFT) Model: A Parametric Approach

Authors

  • Swapan Bhattacharjee Department of Statistics, Tangla College, Tangla – 785421, India
  • Surobhi Deka Department of Statistics, University of Cotton, Panbazar, Guwahati – 781001, India

DOI:

https://doi.org/10.13052/jrss0974-8024.19219

Keywords:

Breast cancer, AFT model, AIC, BIC

Abstract

The primary objective of this study is to identify which covariates of breast cancer patients increase or decrease survival time. The study includes 802 breast cancer patients and during the study period 157 deaths occurred and 645 cases are censored. In this study, four parametric accelerated failure time models are used to identify the best-fitting model: exponential AFT, Weibull AFT, Lognormal AFT, and Log-logistic AFT. To determine the best-fitting model, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) are used. The lowest AIC and BIC values indicate the best-fitting model. The mean age of the breast cancer patients was 47.5 ± 11.008 years. The overall 5 year survival rate of breast cancer patients was 21%. In this study, we found that the Log-Logistic AFT model best fits the breast cancer data set. The AFT model is an alternative to Cox proportional hazard model. In an AFT model, the effect of covariates accelerates or decelerates the time to the event of interest.

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Author Biographies

Swapan Bhattacharjee, Department of Statistics, Tangla College, Tangla – 785421, India

Swapan Bhattacharjee received the master’s degree in Statistics from Cotton University in 2017. He is currently working as an Assistant Professor in the Department of Statistics at Tangla College, Tangla. He has more than 8 years of teaching experience and has published research papers in reputable journals and presented his research at national and international conferences. His research areas include medical research and population research.

Surobhi Deka, Department of Statistics, University of Cotton, Panbazar, Guwahati – 781001, India

Surobhi Deka serves as an Assistant Professor in the Department of Statistics at Cotton University, Guwahati, Assam, India. She holds a PhD from Tezpur University, where her doctoral research focused on statistical modeling of climate variables in the North East Region of India. Her expertise lies in applied statistics, with particular emphasis on extreme value distributions and survival analysis. She has authored numerous research papers published in refereed journals, successfully led a DST-funded project on flood hazard modeling under the Women Scientists Scheme, and actively contributes to the academic community as a reviewer for several international journals.

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Published

2026-10-02

How to Cite

Bhattacharjee, S. ., & Deka, S. . (2026). Survival Analysis of Breast Cancer Patients Using Accelerated Failure Time (AFT) Model: A Parametric Approach. Journal of Reliability and Statistical Studies, 19(02), 717–732. https://doi.org/10.13052/jrss0974-8024.19219

Issue

2026: Vol 19 Iss 2

Section

Articles