A three-state disease model with interval-censored data: estimation and applications to AIDS and cancer.
In presence of interval-censored data, we propose a general three-state disease model with covariates. Such data can arise, for example, in epidemiologic studies of infectious disease where both the times of infection and disease onset are not directly observed, or in cancer studies where the time of disease metastasis is known up to a specified interval. The proposed model allows the distributions of the transition times between states to depend on covariates and the time in the previous state. An estimation procedure for the underlying distributions and the model coefficients is suggested with the EM algorithm. The EMS algorithm (Smoothed EM algorithm) is also considered to obtain smooth estimates of the distributions. The proposed method is illustrated with data from an AIDS study and a study of patients with malignant melanoma.
Leung
K M
KM
Department of Biostatistics, UCLA School of Public Health 90024, USA. moon@ucla.edu
Elashoff
R M
RM
D000163:Acquired Immunodeficiency Syndrome / Q000209:etiology; D000465:Algorithms; D003627:Data Interpretation, Statistical; D006801:Humans; D015993:Life Tables; D008297:Male; D008545:Melanoma / Q000401:mortality / Q000628:therapy; D008954:Models, Biological; D016016:Proportional Hazards Models; D013269:Stochastic Processes; D013997:Time Factors