L’N-ratio linfonodale nel Tumore al Seno costituirebbe una alternativa alla stadiazione clinica basata sul TNM .

Nell’attuale sistema di classificazione TNM, lo status linfonodale del Tumore al seno si basa sul numero di linfonodi coinvolti e non tiene conto del numero totale di linfonodi rimossi. In questo studio è stato valutato il valore prognostico dell’N Ratio linfonodale LNRs (vale a dire del rapporto linfonodi positivi su quelli escissi, LNR).Dal Registro Tumori di Ginevra sono state individuate tutte le donne con diagnosi di linfonodo-positivo e Tumore al seno tra il 1980 e il 2004 (n = 1829). Il valore prognostico del LNRs è stato calcolato attraverso l’analisi della regressione di Cox e convalidato col metodo del bootstrap.
LNRs è fortemente associato con la mortalità per cancro al seno, predice la sopravvivenza dopo la diagnosi in modo più accurato rispetto alla classificazione chirurgica tradizionale e dovrebbe essere considerata come un’alternativa al TNM-staging.

JCO Early Release, published online ahead of print Jan 21 2009 Journal of Clinical Oncology, 10.1200/JCO.2008.18.6965

Received June 17, 2008 Accepted September 30, 2008

Lymph Node Ratio as an Alternative to pN Staging in Node-Positive Breast Cancer

Vincent Vinh-Hung,* Helena M. Verkooijen, Gerald Fioretta, Isabelle Neyroud-Caspar, Elisabetta Rapiti, Georges Vlastos, Carole Deglise, Massimo Usel, Jean-Michel Lutz, and Christine Bouchardy

Purpose: In the current pTNM classification system, nodal status of breast cancer is based on the number of involved lymph nodes and does not account for the total number of lymph nodes removed. In this study, we assessed the prognostic value of the lymph node ratio (LNR; ie, ratio of positive over excised lymph nodes) as compared with pN staging and determined its optimal cutoff points.

Patients and Methods: From the Geneva Cancer Registry, we identified all women diagnosed with node-positive breast cancer between 1980 and 2004 (n = 1,829). The prognostic value of LNRs was calculated for values ranging from 0.05 to 0.95 by Cox regression analysis and validated by bootstrapping. Based on maximum likelihood, we identified cutoff points classifying women into low-, intermediate-, and high-risk LNR groups.

Results: Optimal cutoff points classified patients into low- ( 0.20), intermediate- (> 0.20 and 0.65), and high-risk (> 0.65) LNR groups, corresponding to 10-year disease-specific survival rates of 75%, 63%, and 40%, and adjusted mortality risks of 1 (reference), 1.78 (95% CI, 1.46 to 2.18), and 3.21 (95% CI, 2.54 to 4.06), respectively. In contrast to LNR risk categories, survival curves of pN2 and pN3 crossed after 15 years, and their adjusted mortality risks showed overlapping CIs: 2.07 (95% CI, 1.69 to 2.53) and 2.84 (95% CI, 2.23 to 3.61), respectively.

Conclusion: LNR predicts survival after breast cancer more accurately than pN classification and should be considered as an alternative to pN staging.