PMID: 9544528Apr 17, 1998Paper

Gibbs sampling for long-term survival data with competing risks

Biometrics
E C Chao

Abstract

Many researchers use the 5-year survival probability as a measurement of cure for long-term survival data. In addition to this probability, a mixture model with possibility of cure provides a predictive probability of cure given that a patient has survival to a period of time. Such probabilities are more realistic in measuring the effectiveness of the treatment and predicting the long-term survival of the patient than the 5-year survival rate. An extension of the cure model to the competing risks data is developed. The extended model is a finite mixtures model, where the independence of cause-specific failure times is not assumed. A data set consisting of leukemia with bone marrow transplant is used for illustration. Patients have three possible statuses after transplant: cured by the treatment, relapse of leukemia, or non-relapse-related death. Only the last two events are observable. Patients observed with these endpoints are uncensored cases and the transplant is not successful for them. A case is censored if the case is relapse-free and still alive at the end of its follow-up. Only censored cases have the possibility of being cured, but cure is not assumed to be observable. The status of cure is imputed by the posterior pre...Continue Reading

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