Application of the theory of finite mixtures for the estimation of 'cure' rates of treated cancer patients.
I assume the survival function of treated cancer patients to be a mixture of two subpopulations, with c equal to the proportion who will die of other causes, and 1--c the proportion who will die of their disease. Using census data, I estimate the parameters of the survival distribution of those patients dying of other causes, and then use follow-up data to determine the maximum likelihood estimates of the proportion constant c and the parameters of the survival function of those dying of their disease. I illustrate the methodology using data from a prospective clinical trial in breast cancer.
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44106.
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D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000401:mortality* / Q000601:surgery; D002423:Cause of Death; D002986:Clinical Trials as Topic; D005260:Female; D006801:Humans; D008198:Lymph Nodes / Q000473:pathology; D008408:Mastectomy; D008875:Middle Aged; D015233:Models, Statistical; D013997:Time Factors