Predictive survival model with time-dependent prognostic factors: Development of computer-aided SAS Macro program

Li Sheng Chen, Ming Fang Yen, Hui Min Wu, Chao Sheng Liao, Der Ming Liou, Hsu Sung Kuo, Tony Hsiu Hsi Chen

Research output: Contribution to journalArticle

11 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)181-193
Number of pages13
JournalJournal of Evaluation in Clinical Practice
Volume11
Issue number2
DOIs
Publication statusPublished - Apr 2005
Externally publishedYes

Keywords

  • SAS Macro program
  • Small hepatocellular carcinoma
  • Survival
  • Time-dependent Cox regression model

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health Information Management
  • Nursing(all)

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