title: Nomogram for the prediction of having four or more involved nodes for sentinel lymph node-positive breast cancer.
abstract: OBJECTIVE
  The standard of care for patients with a positive (+) sentinel lymph node (SLN) is axillary dissection; however, for various reasons, some SLN+ patients do not undergo dissection. The purpose of this study was to define possible predictors of having four or more involved nodes to provide information for clinicians and patients making decisions about adjuvant chemotherapy and radiation.
  
  
  METHODS
  We reviewed the records of 402 patients with invasive breast cancer and one to three involved SLNs who underwent completion axillary dissection at two academic cancer centers. None of these patients received neoadjuvant chemotherapy. Factors associated with having four or more involved axillary nodes (SLNs and non-SLNs) were evaluated by univariate and multivariate logistic regression analysis.
  
  
  RESULTS
  Eighty-seven patients had four or more positive nodes. On multivariate analysis, having four or more SLNs was associated with tumor histology, primary tumor size, lymphovascular space invasion, extranodal extension, the number of involved SLNs, the number of uninvolved SLNs, and the size of the largest SLN metastasis. A nomogram to predict the probability of having four or more nodes based on patients' pathologic data was developed from the multivariate logistic regression model. A separate previously published data set of 206 SLN+ patients treated at a community hospital in another city was used to validate this model.
  
  
  CONCLUSIONS
  Patients with a low probability of having four or more nodes can be identified from known pathologic features. The nomogram developed will be helpful to clinicians making adjuvant treatment recommendations.
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, 100 Blossom St, Cox 301, Boston, MA 02114, USA. abkatz@partners.org
authors.forename: Angela
authors.initials: A
authors.lastname: Katz
authors.forename: Barbara L
authors.initials: BL
authors.lastname: Smith
authors.forename: Mehra
authors.initials: M
authors.lastname: Golshan
authors.forename: Andrzej
authors.initials: A
authors.lastname: Niemierko
authors.forename: Wendy
authors.initials: W
authors.lastname: Kobayashi
authors.forename: Rita Abi
authors.initials: RA
authors.lastname: Raad
authors.forename: Alexandra
authors.initials: A
authors.lastname: Kelada
authors.forename: Levi
authors.initials: L
authors.lastname: Rizk
authors.forename: Julia S
authors.initials: JS
authors.lastname: Wong
authors.forename: Jennifer R
authors.initials: JR
authors.lastname: Bellon
authors.forename: Michele
authors.initials: M
authors.lastname: Gadd
authors.forename: Michelle
authors.initials: M
authors.lastname: Specht
authors.forename: Alphonse G
authors.initials: AG
authors.lastname: Taghian
mesh_terms: D000328:Adult; D000368:Aged; D001900:Boston; D001943:Breast Neoplasms / Q000473:pathology* / Q000628:therapy; D018270:Carcinoma, Ductal, Breast / Q000473:pathology* / Q000628:therapy; D018275:Carcinoma, Lobular / Q000473:pathology* / Q000628:therapy; D017024:Chemotherapy, Adjuvant; D005260:Female; D006801:Humans; D016015:Logistic Models; D008207:Lymphatic Metastasis; D008408:Mastectomy; D015412:Mastectomy, Segmental; D008875:Middle Aged; D008954:Models, Biological; D009361:Neoplasm Invasiveness; D049451:Nomograms; D018579:Patient Selection; D011237:Predictive Value of Tests; D012372:ROC Curve; D018714:Radiotherapy, Adjuvant; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D021701:Sentinel Lymph Node Biopsy