RSURV: A function to perform relative survival analysis with S-PLUS or R

被引:12
作者
Giorgi, R [1 ]
Payan, J [1 ]
Gouvernet, J [1 ]
机构
[1] Univ Mediterranee, Fac Med, LERTIM, F-13385 Marseille, France
关键词
relative survival; proportional hazards models; non-proportional hazards models; time-dependent covariates; survival analysis;
D O I
10.1016/j.cmpb.2005.01.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Relative survival. is a method used to estimate net survival using the expected mortality in the general population. This method is frequently used in cancer registries, more particularly with the Esteve et at. regressive proportional hazards model. Recently, extensions of this model have been developed to account for time-dependent covariate and for time-dependent hazards using B-spline functions. We propose a function, RSurv, to take into account these extensions. Written in the R/S Language this function has the same structure of the standard Cox function coxph of R and S-PLUS software with the goal to homogenise survival functions and to take advantages of the power of R and S-PLUS software. We also propose a function, plot. RSurv, for plotting relative survival curves and time-dependent hazards ratio. The usage of these functions is exemplified by a study of a breast cancer hospital-based data set. (c) 2005 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:175 / 178
页数:4
相关论文
共 12 条
[1]  
BERRINO F, 1999, IARC SCI PUBLICATION, V151
[2]  
Bolard P, 2002, J Cancer Epidemiol Prev, V7, P113
[3]   Modelling time-dependent hazard ratios in relative survival: Application to colon cancer [J].
Bolard, P ;
Quantin, C ;
Esteve, J ;
Faivre, J ;
Abrahamowicz, M .
JOURNAL OF CLINICAL EPIDEMIOLOGY, 2001, 54 (10) :986-996
[4]  
BUCKLEY JD, 1983, BIOMETRICS, V39, P941
[5]  
COX DR, 1972, J R STAT SOC B, V34, P187
[6]   RELATIVE SURVIVAL AND THE ESTIMATION OF NET SURVIVAL - ELEMENTS FOR FURTHER DISCUSSION [J].
ESTEVE, J ;
BENHAMOU, E ;
CROASDALE, M ;
RAYMOND, L .
STATISTICS IN MEDICINE, 1990, 9 (05) :529-538
[7]   A relative survival regression model using B-spline functions to model non-proportional hazards [J].
Giorgi, R ;
Abrahamowicz, M ;
Quantin, C ;
Bolard, P ;
Esteve, J ;
Gouvernet, J ;
Faivre, J .
STATISTICS IN MEDICINE, 2003, 22 (17) :2767-2784
[8]  
HAKULINEN T, 1987, J R STAT SOC C-APPL, V36, P309
[9]   Cancer survival increases in Europe, but international differences remain wide [J].
Sant, M ;
Capocaccia, R ;
Coleman, MP ;
Berrino, F ;
Gatta, G ;
Micheli, A ;
Verdecchia, A ;
Faivre, J ;
Hakulinen, T ;
Coebergh, JWW ;
Martinez-Garcia, C ;
Forman, D ;
Zappone, A .
EUROPEAN JOURNAL OF CANCER, 2001, 37 (13) :1659-1667
[10]   Proportional excess hazards [J].
Sasieni, PD .
BIOMETRIKA, 1996, 83 (01) :127-141