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A Nomogram for Predicting the Likelihood of Additional Nodal Metastases in Breast Cancer Patients With a Positive Sentinel Node Biopsy
Authors:Kimberly?J.?Van?Zee  author-information"  >  author-information__contact u-icon-before"  >  mailto:vanzeek@mskcc.org"   title="  vanzeek@mskcc.org"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Donna-Marie?E.?Manasseh,Jose?L.?B.?Bevilacqua,Susan?K.?Boolbol,Jane?V.?Fey,Lee?K.?Tan,Patrick?I.?Borgen,Hiram?S.?Cody  Suffix"  >III,Michael?W.?Kattan
Affiliation:(1) Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, New York;(2) Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York;(3) Department of Urology, Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York;(4) Memorial Sloan-Kettering Cancer Center, 1275 York Ave., MRI-1026, New York, NY, 10021
Abstract:Background:The standard of care for breast cancer patients with sentinel lymph node (SLN) metastases includes complete axillary lymph node dissection (ALND). However, many question the need for complete ALND in every patient with detectable SLN metastases, particularly those perceived to have a low risk of non-SLN metastases. Accurate estimates of the likelihood of additional disease in the axilla could assist greatly in decision-making regarding further treatment.Methods:Pathological features of the primary tumor and SLN metastases of 702 patients who underwent complete ALND were assessed with multivariable logistic regression to predict the presence of additional disease in the non-SLNs of these patients. A nomogram was created using pathological size, tumor type and nuclear grade, lymphovascular invasion, multifocality, and estrogen-receptor status of the primary tumor; method of detection of SLN metastases; number of positive SLNs; and number of negative SLNs. The model was subsequently applied prospectively to 373 patients.Results:The nomogram for the retrospective population was accurate and discriminating, with an area under the receiver operating characteristic (ROC) curve of 0.76. When applied to the prospective group, the model accurately predicted likelihood of non-SLN disease (ROC, 0.77).Conclusions:We have developed a user-friendly nomogram that uses information commonly available to the surgeon to easily and accurately calculate the likelihood of having additional, non-SLN metastases for an individual patient.Drs. Manasseh and Bevilacqua contributed equally to the work.Dr. Bevilacqua is currently affiliated with Hospital Sírio Libanes, Instituto Brasileiro de Controle do Câncer, and Disciplina de Cirurgia Geral, Departamento de Cirurgia, Faculdade de Medicina da Univerdidade de Sao Paulo. São Paulo, Brazil; Dr. Boolbol is currently affiliated with Beth Israel Medical Center, New York, New York.
Keywords:Axillary metastases  Breast cancer  Nomogram  Prediction  Sentinel node
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