Multivariate frailty models for two types of recurrent events with a dependent terminal event: application to breast cancer data.
Individuals may experience more than one type of recurrent event and a terminal event during the life course of a disease. Follow-up may be interrupted for several reasons, including the end of a study, or patients lost to follow-up, which are non informative censoring events. Death could also stop the follow-up, hence, it is considered as a dependent terminal event. We propose a multivariate frailty model that jointly analyzes two types of recurrent events with a dependent terminal event. Two estimation methods are proposed: a semiparametrical approach using penalized likelihood estimation where baseline hazard functions are approximated by M-s plines, and another one with piecewise constant baseline hazard functions. Finally, we derived martingale residuals to check the goodness-of-fit. We illustrate our proposals with a real dataset on breast cancer. The main objective was to model the dependency between the two types of recurrent events (locoregional and metastatic) and the terminal event (death) after a breast cancer.
INSERM, ISPED, Centre INSERM U-897-Epidemiologie-Biostatistique, 146 rue Léo Saignat, 33076, Bordeaux Cedex, France; Université Bordeaux Segalen, ISPED, Centre INSERM U-897-Epidemiologie-Biostatistique, Bordeaux, F-33000, France.
Yassin
Y
Mazroui
Simone
S
Mathoulin-Pélissier
Gaetan
G
Macgrogan
Véronique
V
Brouste
Virginie
V
Rondeau
D001699:Biometry / Q000379:methods*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000473:pathology / Q000601:surgery; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D015412:Mastectomy, Segmental; D015233:Models, Statistical; D015999:Multivariate Analysis; D009362:Neoplasm Metastasis; D011379:Prognosis; D012008:Recurrence; D012306:Risk
Breast cancer; Frailty models; Penalized likelihood; Recurrent events