Predictive survival model with time-dependent prognostic factors: development of computer-aided SAS Macro program |
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Authors: | Chen Li-Sheng Yen Ming-Fang Wu Hui-Min Liao Chao-Sheng Liou Der-Ming Kuo Hsu-Sung Chen Tony Hsiu-Hsi |
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Institution: | Institute of Public Health and Institute of Health Informatics and Decision Making, School of Medicine, National Yang-Ming University, Taipei, Taiwan. |
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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. |
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Keywords: | SAS Macro program small hepatocellular carcinoma survival time-dependent Cox regression model |
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