SAS macro program for non-homogeneous Markov process in modeling multi-state disease progression

Wu Hui-Min, Yen Ming-Fang, Tony Hsiu-Hsi Chen

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Writing a computer program for modeling multi-state disease process for cancer or chronic disease is often an arduous and time-consuming task. We have developed a SAS macro program for estimating the transition parameters in such models using SAS IML. The program is very flexible and enables the user to specify homogeneous and non-homogeneous (i.e. Weibull distribution, log-logistic, etc.) Markov models, incorporate covariates using the proportional hazards form, derive transition probabilities, formulate the likelihood function, and calculate the maximum likelihood estimate (MLE) and 95% confidence interval within a SAS subroutine. The program was successfully applied to an example of a three-state disease model for the progression of colorectal cancer from normal (disease free), to adenoma (pre-invasive disease), and finally to invasive carcinoma, with or without adjusting for covariates. This macro program can be generalized to other k-state models with s covariates.

Original languageEnglish
Pages (from-to)95-105
Number of pages11
JournalComputer Methods and Programs in Biomedicine
Volume75
Issue number2
DOIs
Publication statusPublished - Aug 2004
Externally publishedYes

Fingerprint

Markov Chains
Markov processes
Likelihood Functions
Macros
Disease Progression
Computer simulation
Adenoma
Colorectal Neoplasms
Chronic Disease
Software
Confidence Intervals
Weibull distribution
Subroutines
Carcinoma
Maximum likelihood
Logistics
Computer program listings
Hazards
Neoplasms

Keywords

  • Exponential regression model
  • Markov model
  • Multi-state model

ASJC Scopus subject areas

  • Software

Cite this

SAS macro program for non-homogeneous Markov process in modeling multi-state disease progression. / Hui-Min, Wu; Ming-Fang, Yen; Hsiu-Hsi Chen, Tony.

In: Computer Methods and Programs in Biomedicine, Vol. 75, No. 2, 08.2004, p. 95-105.

Research output: Contribution to journalArticle

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