Predicting Non-Sentinel Lymph Node Status in Breast Cancer Patients with Sentinel Lymph Node Involvement: Evaluation of Two Scoring Systems

Alex Sanjuan*, Georgia Escaramis, Sergi Vidal-Sicart, Miriam Illa, Gabriel Zanon, Jaume Pahisa, Sebastia Rubi, Martin Velasco, Gorane Santamaria, Blanca Farrus, Montse Munoz, Yolanda Garcia, Pedro Luis Fernandez, Francesca Pons

*Autor corresponent d’aquest treball

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Resum

The aim of this study was to validate a nomogram and a scoring system to predict non-sentinel lymph node status in breast cancer patients with sentinel lymph node (SLN) involvement. A total of 516 breast cancer patients underwent sentinel lymph node biopsy at our institution from January 2001 to August 2006. A prospective database was used to identify breast cancer patients with a positive SLN biopsy examination who underwent a completion axillary lymph node dissection. A total of 114 patients were identified. The Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram and an axilla scoring system from Paris (Hopital Tenon) were used to predict the probability of having non-SLN involvement. One hundred fourteen patients were included in the study. The areas under the receiver operating characteristics (ROC) curves were 0.671 (95% CI: 0.552-0.790) for the MSKCC nomogram and 0.703 (95% CI: 0.596-0.811) for the Tenon score. The univariate analysis shows that size of SLN metastases, the number of positive and negative SLN and the proportion of positive SLN were statistically significant. On multivariate logistic regression analysis, the size of SLN metastases and the proportion of positive SLN were statistically significant. The two scoring systems are similar according to their area under ROC curves, but should be improved to be valid and determinant to the general population. Meanwhile, the use of scoring systems could be applied in an individual manner in some patients.

Idioma originalAnglès
Pàgines (de-a)134-140
Nombre de pàgines7
RevistaBreast J
Volum16
Número2
DOIs
Estat de la publicacióPublicada - 2010

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