The “Sentinel Chain”: a new concept for prediction of axillary node status in breast cancer patients

Assessment of the performance of the Stanford Online Calculator for the prediction of nonsentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients

BACKGROUND

Several models for the prediction of nonsentinel lymph node (NSLN) metastasis in sentinel lymph node (SLN)-positive breast cancer patients have been proposed. In this study, the authors evaluate the Stanford Online Calculator (SOC), which was designed to predict the likelihood of NSLN metastasis using only 3 variables: primary tumor size, SLN metastasis size, and angiolymphatic invasion status. They compared it with the Mayo and Memorial Sloan-Kettering Cancer Center (MSKCC) nomograms.

METHODS

The SOC was used to calculate the probability of NSLN metastasis in 464 breast cancer patients with SLN metastasis who underwent completion axillary lymph node dissection at the Mayo Clinic. The area under the receiver operating characteristic curve (AUC) was calculated for each model. Mean probabilities of patients with and without NSLN metastasis were compared. Patients with <or=5%, <or=10%, and 100% NSLN metastasis probabilities were examined.

RESULTS

The AUCs of the Stanford, MSKCC, and Mayo models were 0.72, 0.74, and 0.77, respectively (P=.13). The mean Stanford probabilities for patients with and without NSLN metastasis were 0.75 (range, 0.06-1.0) and 0.50 (range, 0.05-1.0), respectively (P<.0001). The false-negative rates for patients with a Stanford probability of <or=5% and <or=10% were 0% and 13%, respectively. Of the patients with a Stanford probability of 100%, 26% did not have NSLN metastasis.

CONCLUSIONS

Despite using only 3 variables, the Stanford nomogram appears to perform on a par with, but not better than, the MSKCC and Mayo nomograms. Further validation in other patient populations is needed.