The analysis of asthma control under a Markov assumption with use of covariates.
In studies of disease states and their relation to evolution, data on the state are usually obtained at in frequent time points during follow-up. Moreover in many applications, there are measured covariates on each individual under study and interest centres on the relationship between these covariates and the disease evolution. We developed a continuous-time Markov model with use of time-dependent covariates and a Markov model with piecewise constant intensities to model asthma evolution. Methods to estimate the effect of covariates on transition intensities, to test the assumption of time homogeneity and to assess goodness-of-fit are proposed. We apply these methods to asthma control. We consider a three-state model and we discuss in detail the analysis of asthma control evolution.
Saint-Pierre
P
P
Laboratoire de Biostatistique, Institut Universitaire de Recherche Clinique, 641 avenue de Doyen Gaston Giraud, Montpellier 34093, France. stpeirre@iurc.montp.inserm.fr
Combescure
C
C
Daurès
J P
JP
Godard
P
P
D001249:Asthma / Q000473:pathology / Q000517:prevention & control / Q000628:therapy*; D018450:Disease Progression; D005500:Follow-Up Studies; D006801:Humans; D016013:Likelihood Functions; D008137:Longitudinal Studies; D008390:Markov Chains