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Updated: May 16, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Survival analysis of breast cancer patients using Cox and frailty models
Javad Faradmal1, Atefeh Talebi, Abbas Rezaianzadeh
1Department of Biostatistics & Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran. javad.faradmal@umsha.ac.ir.
Background:
Cox proportional hazard (CPH) model is the most widely used model for survival analysis. When there are unobserved/unmeasured individuals factor, then the results of the Cox proportional hazard model may not be reliable. The purpose of this study was to compare the results of CPH and frailty models in breast cancer (BC) patients.
Methods:
A historical cohort study was carried out using medical records gathered from the Fars Province Cancer Registry. The dataset consisted of 769 women having BC referred to Shiraz Namazi Hospital, south of Iran. These patients had been followed for 6 years. After selecting the most important prognostic risk factors on survival, CPH and gamma-frailty Cox models were used to estimate the effects of the risk factors.
Results:
The results of CPH model showed that, tumor characteristics and number of involved lymph nodes increase the mortality hazard of BC(P<0.05). In addition, the frailty model showed that there is at least a latent factor in the model (P=0.005).
Conclusion:
Both of the frailty and CPH model emphasis that the early detection of BC improves survival in BC patients.
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