Micrometastatic Node-Positive Breast Cancer: Long-Term Outcomes and Identification of High-Risk Subsets in a Large Population-Based Series
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The prognostic implication of breast cancer with nodal micrometastases measuring >0.2 mm but ≤2 mm (pNmic) is unclear. This study evaluates survival in pNmic relative to node-negative (N0) and macroscopic node-positive (pNmac) disease in a large population-based series.
Subjects were 9,637 women diagnosed between 1989 and 1999, referred to the British Columbia Cancer Agency with pT1–2, node-negative and node-positive, M0 breast cancer. Kaplan–Meier breast-cancer-specific survival (BCSS) and overall survival (OS) were compared between patients with pN0 (n = 7,988), pNmic (n = 491), and pNmac disease (n = 1,158), according to the number of positive nodes and the lymph node ratio (LNR) of positive to excised nodes. Cox regression and recursive partitioning analyses were performed to identify significant factors associated with survival.
Median follow-up was 8.2 years. Patients with pNmic disease had significantly poorer outcomes compared with pN0 cancers, with progressively lower BCSS and OS with increasing number of positive nodes and with LNR > 0.25. On multivariable analysis, histologic subtype, T stage, number of positive nodes, LNR, grade, lymphovascular invasion, estrogen receptor status, and systemic therapy use were factors significantly associated with BCSS and OS. Recursive partitioning trees for BCSS and OS both selected the pN/LNR variable at the first split, indicating that this variable provided the strongest prognostic separation.
Patients with nodal micrometastases are a heterogeneous population with varying breast cancer mortality risks. The number of positive nodes and the LNR should be considered in conjunction with tumor factors in risk estimates and treatment decisions for patients with nodal micrometastatic breast cancer.
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- Micrometastatic Node-Positive Breast Cancer: Long-Term Outcomes and Identification of High-Risk Subsets in a Large Population-Based Series
Annals of Surgical Oncology
Volume 17, Issue 8 , pp 2138-2146
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- 1. Breast Cancer Outcomes Unit, British Columbia Cancer Agency, Victoria, BC, Canada
- 2. Department of Radiation Oncology, British Columbia Cancer Agency, Vancouver Island Centre, Victoria, BC, Canada
- 3. University of British Columbia, Vancouver, Victoria, BC, Canada
- 4. Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada
- 5. Department of Medical Oncology, British Columbia Cancer Agency, Vancouver Centre, Vancouver, BC, Canada