Prediction of axillary lymph node metastases in breast cancer patients based on pathologic information of the primary tumor.
BACKGROUND
Axillary lymph nodes (ALN) are the most commonly involved site of disease in breast cancer that has spread outside the primary lesion. Although sentinel node biopsy is a reliable way to manage ALN, there are still no good methods of predicting ALN status before surgery. Since morbidity in breast cancer surgery is predominantly related to ALN dissection, predictive models for lymph node involvement may provide a way to alert the surgeon in subgroups of patients.


METHODS
A total of 1325 invasive breast cancer patients were analyzed using tumor biological parameters that included age, tumor size, grade, estrogen receptor, progesterone receptor, lymphovascular invasion, and HER2, to test their ability to predict ALN involvement. A support vector machine (SVM) was used as a classification model. The SVM is a machine-learning system developed using statistical learning theories to classify data points into 2 classes. Notably, SVM models have been applied in bioinformatics.


RESULTS
The SVM model correctly predicted ALN metastases in 74.7% of patients using tumor biological parameters. The predictive ability of luminal A, luminal B, triple negative, and HER2 subtypes using subgroup analysis showed no difference, and this predictive performance was inferior, with only 60% accuracy.


CONCLUSIONS
With an SVM model based on clinical pathologic parameters obtained in the primary tumor, it is possible to predict ALN status in order to alert the surgeon about breast cancer counseling and in decision-making for ALN management.
Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan.
Jia-Long
JL
Wu
Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan.
Hsin-Shun
HS
Tseng
Department of Surgery, Changhua Christian Hospital, Changhua, Taiwan.
Li-Heng
LH
Yang
Department of Medical Imaging, Changhua Christian Hospital, Changhua County, Taiwan.
Hwa-Koon
HK
Wu
Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan.
Shou-Jen
SJ
Kuo
Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan.
Shou-Tung
ST
Chen
Comprehensive Breast Cancer Center, Changhua Christian Hospital, Changhua, Taiwan.
Dar-Ren
DR
Chen
D001365:Axilla / Q000473:pathology*; D001943:Breast Neoplasms / Q000473:pathology*; D005260:Female; D006801:Humans; D008198:Lymph Nodes / Q000473:pathology*; D008207:Lymphatic Metastasis / Q000175:diagnosis* / Q000473:pathology; D008875:Middle Aged; D011379:Prognosis; D012372:ROC Curve; D060388:Support Vector Machine