TITLE:
A Comparison of Breast Surgeon and Nomogram-Generated Risk Predictions of Sentinel and Non-Sentinel Node Metastases
AUTHORS:
Luisa Sugaya, Paulo R. de Alcantara Filho, Bruna Salani Mota, Sujata Patil, Kimberly J. Van Zee, José Luiz B. Bevilacqua
KEYWORDS:
Sentinel Lymph Node Biopsy; Nomogram; Predictions; Breast Cancer; Completion Axillary Lymph Node Dissection
JOURNAL NAME:
Journal of Cancer Therapy,
Vol.4 No.7A,
July
17,
2013
ABSTRACT: Memorial Sloan-Kettering Cancer Center
(MSKCC) has developed 2 nomograms: the Sentinel Lymph Node Nomogram (SLNN), which is used to predict
the likelihood of sentinel lymph node (SLN) metastases in patients with
invasive breast cancer, and the Non-Sentinel Lymph Node Nomogram (NSLNN), which
is used to predict the likelihood of residual axillary disease after a
positive SLN biopsy. Our purpose was to compare the accuracy of MSKCC nomogram
predictions with those made by breast surgeons. Two questionnaires were built
with characteristics of two sets of 33 randomly selected patients from the
MSKCC Sentinel Node Database. The first included only patients with invasive
breast cancer, and the second included only patients with invasive breast
cancer and positive SLN biopsy. 26 randomly selected Brazilian breast surgeons
were asked about the probability of each patient in the first set having SLN metastases and each patient in the second set
having additional non-SLN metastases. The predictions of the nomograms and
breast surgeons were compared. There was no correlation between nomogram risk
predictions and breast surgeon risk prediction estimates for either the SLNN or
the NSLNN. The area under the receiver operating characteristics curves (AUCs)
were 0.871 and 0.657 for SLNN and breast surgeons, respectively (p 0.0001), and 0.889 and 0.575 for the
NSLNN and breast surgeons, respectively (p 0.0001). The nomograms were
significantly more accurate as prediction tools than the risk predictions of
breast surgeons in Brazil. This study demonstrates the potential utility of
both nomograms in the decision-making process for patients with invasive breast
cancer.