TY - JOUR
T1 - SAS macro program for non-homogeneous Markov process in modeling multi-state disease progression
AU - Hui-Min, Wu
AU - Ming-Fang, Yen
AU - Hsiu-Hsi Chen, Tony
PY - 2004/8
Y1 - 2004/8
N2 - 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.
AB - 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.
KW - Exponential regression model
KW - Markov model
KW - Multi-state model
UR - http://www.scopus.com/inward/record.url?scp=2942748361&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=2942748361&partnerID=8YFLogxK
U2 - 10.1016/j.cmpb.2003.12.001
DO - 10.1016/j.cmpb.2003.12.001
M3 - Article
C2 - 15212852
AN - SCOPUS:2942748361
SN - 0169-2607
VL - 75
SP - 95
EP - 105
JO - Computer Methods and Programs in Biomedicine
JF - Computer Methods and Programs in Biomedicine
IS - 2
ER -