Estimation of Transition Probabilities in Ischemic Heart Disease by Markov Model
The purpose of this study is to develop a method of estimating transition probabilities among the disease "states" indicating its severity for the chronic diseases. This method was applied to the analysis of the natural history of patients with coronary heart diseases. The transition process among "states" is assumed to be expressed by a time discrete simple Markov process. The severity of the disease was classified into 3 "states", i. e., S1: single vessel disease, S2 : double vessel disease, S3 : triple vessel disease. Estimation of the transition probabilities was made by the maximum likelihood method, using the follow-up data of the numbers of the survival. The accuracies of the estimated values are evaluated by the asymptotic variances. From the present study the followings were observed : (1) the accuracy of the curve fiitting for the follow-up data was satisfactory, (2) the catenary model was the most prominent in the sense that an information criterion AIC is minimum, and (3) there may exist the reversible transitions among some disease states.