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Cure Mixture Models in Breast Cancer Survival Studies

In: Lifetime Data: Models in Reliability and Survival Analysis

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  • Nahida H. Gordon

    (Case Western Reserve University, Department of Epidemiology and Biostatistics)

Abstract

A considerable proportion of breast cancer patients will die of unrelated causes, thus complicating the analysis of the effect of prognostic factors or treatment. I assume the survival function of breast cancer patients to be a mixture of two survival functions representing those who will die from other causes (i.e., cured) and those from breast cancer. The hazard function for breast cancer death incorporates covariates representing breast cancer risk factors. Using the proposed cure mixture model, I consider the questions whether newly diagnosed node positive breast cancer is a late manifestation of node negative breast cancer or whether it is an inherently more aggressive disease. Using census and clinical trial data, I estimate the proportion of patients dying of other causes and of breast cancer for each of the node negative and node positive groups. An estimated 55.9% and 26.0% of node negative and positive patients, respectively, will die from other causes. Of those patients who will die from breast cancer, node positive patients were prone to have a significantly higher breast cancer death rate indicating that their disease is not simply a late manifestation of node negative disease.

Suggested Citation

  • Nahida H. Gordon, 1996. "Cure Mixture Models in Breast Cancer Survival Studies," Springer Books, in: Nicholas P. Jewell & Alan C. Kimber & Mei-Ling Ting Lee & G. A. Whitmore (ed.), Lifetime Data: Models in Reliability and Survival Analysis, pages 107-112, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-5654-8_16
    DOI: 10.1007/978-1-4757-5654-8_16
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