Background: Completion axillary lymph node dissection is recommended for patients with metastases to the sentinel lymph node (SLN) in breast cancer although nonsentinel lymph nodes (NSLN) are often negative for tumor. Online nomograms are available to predict risk of NSLN disease.

Objective: To compare the accuracy of the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram (using 9 variables) with the Stanford nomogram (using 3 variables) in predicting NSLN metastasis.

Setting: A single academic center.

Patients: Prospectively maintained database of patients with breast cancer who underwent SLN biopsy from October 1, 1999, through January 31, 2008.

Methods: Risk of NSLN metastasis was calculated using each nomogram's online calculator. Results from the axillary lymph node dissection were reviewed for positive NSLNs. Nomograms were evaluated using the area under the receiver operating characteristic curve, false-negative rates, positive predictive value, and calibration plot.

Main Outcome Measures: Nomogram scores and axillary lymph node dissection results.

Results: Of 579 patients who underwent SLN biopsy, 179 (30.9%) had a positive SLN. For 123 patients who underwent axillary lymph node dissection, the area under the curve for the MSKCC and Stanford nomograms was 0.72 and 0.70, respectively. False-negative rates for nomogram values of 10% or less were low (4.1% for the MSKCC and 7.8% for the Stanford). The positive predictive value for nomogram probabilities of 80% or greater was higher for MSKCC than for Stanford (90.9% vs 61.8%). The Stanford nomogram performed more accurately in low-risk patients with isolated tumor cells or micrometastatic SLN disease; however, the MSKCC nomogram more accurately predicted NSLN outcomes across the entire study population.

Conclusion: Although the MSKCC and Stanford nomograms performed similarly on the basis of the area under the curve, the MSKCC nomogram was consistently more reliable in predicting actual NSLN outcomes.

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Source
http://dx.doi.org/10.1001/archsurg.2011.201DOI Listing

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