Original Article
Use of peripheral lymphocytes and support vector machine for survival prediction in breast cancer patients
Abstract
Background: This study aimed to identify the influence of peripheral lymphocytes on prognosis and find prognostic markers for breast cancer patients.
Methods: This study enrolled invasive breast cancer patients and they were followed-up for median 4-years over telephone. Distributions of disease-free survival (DFS) and overall survival (OS) between different levels of lymphocytes were estimated with the Kaplan-Meier (K-M) method. Support vector machine (SVM) methods were used to develop a prognostic classifier for breast cancer.
Results: A total of 190 patients were enrolled. Patients with low level of cluster of differentiation (CD)3+ lymphocytes had worse DFS and OS (P<0.05). Strong association was reported between SVM-DFS model and DFS (sensitivity, 97%; specificity, 75%); whereas the SVM-OS model was strongly associated with OS (sensitivity, 67%; specificity, 100%).
Conclusions: Patients with low level of CD3+ lymphocytes could have a poorer survival and the SVM method could predict prognosis in breast cancer patients.
Methods: This study enrolled invasive breast cancer patients and they were followed-up for median 4-years over telephone. Distributions of disease-free survival (DFS) and overall survival (OS) between different levels of lymphocytes were estimated with the Kaplan-Meier (K-M) method. Support vector machine (SVM) methods were used to develop a prognostic classifier for breast cancer.
Results: A total of 190 patients were enrolled. Patients with low level of cluster of differentiation (CD)3+ lymphocytes had worse DFS and OS (P<0.05). Strong association was reported between SVM-DFS model and DFS (sensitivity, 97%; specificity, 75%); whereas the SVM-OS model was strongly associated with OS (sensitivity, 67%; specificity, 100%).
Conclusions: Patients with low level of CD3+ lymphocytes could have a poorer survival and the SVM method could predict prognosis in breast cancer patients.
