SAS MACRO PROGRAM FOR NON- HOMOGENEOUS MARKOV PROCESS IN MODELING MULTI-STATE DISEASE PROGRESSION
Resource
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE v.75 n.2 pp.95-105
Journal
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Journal Volume
v.75
Journal Issue
n.2
Pages
95-105
Date Issued
2004
Date
2004
Author(s)
YEN, AMY, MING-FANG
CHEN, TONY, HSIU-HIS
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 cotorectal 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. (C) 2004 Published by Elsevier Ireland Ltd.
Subjects
multi-state model
Markov model
exponential regression model
SDGs
Type
journal article