Survival-Time Classi cation of Breast Cancer Patients

Abstract

The identi cation of breast cancer patients for whom chemother- apy could prolong survival time is treated here as a data mining prob- lem. This identi cation is achieved by clustering 253 breast cancer patients into three prognostic groups: Good, Poor and Intermediate. Each of the three groups has a signi cantly distinct Kaplan-Meier survival curve. Of particular signi cance is the Intermediate group, because patients with chemotherapy in this group do better than those without chemotherapy in the same group. This is the reverse case to that of the overall population of 253 patients for which patients un- dergoing chemotherapy have worse survival than those who do not. We also prescribe a procedure that utilizes three nonlinear smooth support vector machines (SSVMs) for classifying breast cancer pa- tients into the three above prognostic groups. These results suggest that the patients in the Good group should not receive chemotherapy while those in the Intermediate group should receive chemotherapy based on our survival curve analysis. To our knowledge this is the rst instance of a classi able group of breast cancer patients for which chemotherapy can possibly enhance survival.