PREDICTIVE SURVIVAL MODEL WITH TIME- DEPENDENT PROGNOSTIC FACTORS: DEVELOPMENT OF COMPUTER-AIDED SAS MACRO PROGRAM
Resource
JOURNAL OF EVALUATION IN CLINICAL PRACTICE v.11 n.2 pp.181-193
Journal
JOURNAL OF EVALUATION IN CLINICAL PRACTICE
Journal Volume
v.11
Journal Issue
n.2
Pages
181-193
Date Issued
2005
Date
2005
Author(s)
Chen, Li-Sheng
Yen, Ming-Fang
Wu, Hui-Min
Liao, Chao-Sheng
Liou, Der-Ming
Kuo, Hsu-Sung
Chen, Tony Hsiu-Hsi
Abstract
Aims and objectives: Computer program for the prediction of survival with respect to time-dependent proportional hazards regression model has been rarely addressed. We therefore developed a SAS Macro program for time-dependent Cox regression predictive model for empirical survival data associated with time-dependent covariates. Method: Time- dependent proportional hazards regression model and partial likelihood in association with time-varying predictors were explicitly delineated. Baseline hazard using Andersen's method was incorporated into proportional hazards regression model to predict the dynamic change of cumulative survival in respect of time-varying predictors. Two SAS Macro programs for time-dependent predictive survival model and model validation using receiver operative characteristics were written with SAS IML language. Results: The computer program was applied to data on clinical surveillance of small hepatocellular carcinoma (HCC) treated by percutaneous ethanol injection (PEI) or transcatheter arterial embolization (TAE) with time-varying predictors such as alpha-feto protein (AFP) and other biological markers. Conclusion: The program is very useful for real-time prediction of cumulative survival on the basis of time- dependent covariates.
Subjects
SAS Macro program
small hepatocellular carcinoma
survival
time-dependent Cox regression model
Type
journal article