Approaches in modelling long‐term survival: an application to breast cancer | Zendy

Perperoglou Aris | Zendy; Keramopoullos Antonis | Zendy; van Houwelingen Hans C. | Zendy

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Approaches in modelling long‐term survival: an application to breast cancer

Author(s) -

Perperoglou Aris,

Keramopoullos Antonis,

van Houwelingen Hans C.

Publication year - 2006

Publication title -

statistics in medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.996

H-Index - 183

eISSN - 1097-0258

pISSN - 0277-6715

DOI - 10.1002/sim.2729

Subject(s) - proportional hazards model , covariate , breast cancer , computer science , term (time) , survival analysis , brier score , hazard , hazard model , statistics , econometrics , medicine , cancer , mathematics , artificial intelligence , machine learning , physics , chemistry , organic chemistry , quantum mechanics

Several modelling techniques have been proposed for non‐proportional hazards. In this work we consider different models which can be classified into three wide categories: models with time‐varying effects of the covariates; frailty models and cure rate models. We present those different extensions of the proportional hazards model on an application of 2433 breast cancer patients with a long follow‐up. We comment on the differences and similarities among the models and evaluate their performance using survival and hazard plots, Brier scores and pseudo‐observations. Copyright © 2006 John Wiley & Sons, Ltd.

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