The Prognostic Significance of the Lymph Node Ratio in Axillary Lymph Node Positive Breast Cancer.
10.4048/jbc.2011.14.3.204
- Author:
Ji Yoon KIM
1
;
Mi Ryeong RYU
;
Byung Ock CHOI
;
Woo Chan PARK
;
Se Jeong OH
;
Jong Man WON
;
Su Mi CHUNG
Author Information
1. Department of Radiation Oncology, The Catholic University of Korea College of Medicine, Seoul, Korea. sumic@catholic.ac.kr
- Publication Type:Original Article
- Keywords:
Breast neoplasms;
Lymph nodes;
Prognosis
- MeSH:
Breast;
Breast Neoplasms;
Cohort Studies;
Disease-Free Survival;
Estrogens;
Follow-Up Studies;
Humans;
Lymph Nodes;
Multivariate Analysis;
Neoplasm Metastasis;
Prognosis;
Receptors, Progesterone;
Recurrence
- From:Journal of Breast Cancer
2011;14(3):204-212
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: This study evaluated the prognostic impact of the lymph node ratio (LNR; i.e., the ratio of positive to dissected lymph nodes) on recurrence and survival in breast cancer patients with positive axillary lymph nodes (LNs). METHODS: The study cohort was comprised of 330 breast cancer patients with positive axillary nodes who received postoperative radiotherapy between 1987 and 2004. Ten-year Kaplan-Meier locoregional failure, distant metastasis, disease-free survival (DFS) and disease-specific survival (DSS) rates were compared using Kaplan-Meier curves. The prognostic significance of the LNR was evaluated by multivariate analysis. RESULTS: Median follow-up was 7.5 years. By minimum p-value approach, 0.25 and 0.55 were the cutoff values of LNR at which most significant difference in DFS and DSS was observed. The DFS and DSS rates correlated significantly with tumor size, pN classification, LNR, histologic grade, lymphovascular invasion, the status of estrogen receptor and progesterone receptor. The LNR based classification yielded a statistically larger separation of the DFS curves than pN classification. In multivariate analysis, histologic grade and pN classification were significant prognostic factors for DFS and DSS. However, when the LNR was included as a covariate in the model, the LNR was highly significant (p<0.0001), and pN classification was not statistically significant (p>0.05). CONCLUSION: The LNR predicts recurrence and survival more accurately than pN classification in our study. The pN classification and LNR should be considered together in risk estimates for axillary LNs positive breast cancer patients.
