Journal of the American College of Surgeons · 2010
Improved staging in node-positive breast cancer patients using lymph node ratio: results in 1,788 patients with long-term follow-up.
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Danko Melissa E, Bennett Kyla M, Zhai Jun, Marks Jeffrey R, Olson John A
Аннотация
BACKGROUND: Axillary lymph node status remains the most important prognostic factor in breast cancer. Established staging systems emphasize the absolute number of positive nodes, without regard for the total number of lymph nodes examined. We sought to confirm that a ratio of positive nodes to total nodes examined (LNR) has prognostic value beyond the current TNM classification for women with node-positive breast cancer.
STUDY DESIGN: Using the Duke University Medical Center breast cancer tumor registry, we identified women diagnosed with node-positive breast cancer between 1985 and 2005 (n = 1,788). Variables analyzed for impact on disease-free survival (DFS) included the number of positive nodes, N classification, and the calculated LNR. Based on LNR, the patients were divided into low- (< or =0.2), intermediate- (>0.2 and < or =0.65), and high- (>0.65) risk groups. Kaplan-Meier survival analysis was performed with groups compared by the log-rank test. Values of p < 0.05 were considered significant.
RESULTS: For all patients, the 10-year actuarial DFS rates for the low-, intermediate-, and high-risk LNR groups were 69%, 60%, and 45%, respectively. The DFS curves for the 3 LNR groups were significantly different (p < 0.0001). Furthermore, when patients were stratified by pN status, the DFS curves for the LNR groups remained significantly different. The LNR discerned groups of patients with divergent survival probabilities across all pN groups.
CONCLUSIONS: Our data show that LNR has prognostic value in assessing breast cancer survival beyond the current TNM classification. This study supports the inclusion of LNR for enhanced risk stratification beyond traditional pN classification.
STUDY DESIGN: Using the Duke University Medical Center breast cancer tumor registry, we identified women diagnosed with node-positive breast cancer between 1985 and 2005 (n = 1,788). Variables analyzed for impact on disease-free survival (DFS) included the number of positive nodes, N classification, and the calculated LNR. Based on LNR, the patients were divided into low- (< or =0.2), intermediate- (>0.2 and < or =0.65), and high- (>0.65) risk groups. Kaplan-Meier survival analysis was performed with groups compared by the log-rank test. Values of p < 0.05 were considered significant.
RESULTS: For all patients, the 10-year actuarial DFS rates for the low-, intermediate-, and high-risk LNR groups were 69%, 60%, and 45%, respectively. The DFS curves for the 3 LNR groups were significantly different (p < 0.0001). Furthermore, when patients were stratified by pN status, the DFS curves for the LNR groups remained significantly different. The LNR discerned groups of patients with divergent survival probabilities across all pN groups.
CONCLUSIONS: Our data show that LNR has prognostic value in assessing breast cancer survival beyond the current TNM classification. This study supports the inclusion of LNR for enhanced risk stratification beyond traditional pN classification.