Nonsentinel node metastasis in breast cancer patients: Assessment of an existing and a new predictive nomogram

Amy C. Degnim, Carol Reynolds, Gouri Pantvaidya, Shaheen Zakaria, Tanya Hoskin, Sunni Barnes, Margaret V. Roberts, Peter C. Lucas, Kevin Oh, Meryem Koker, Michael S. Sabel, Lisa A. Newman

Research output: Contribution to journalArticle

188 Scopus citations

Abstract

Background: The accurate prediction of nonsentinel node (NSN) metastasis in breast cancer patients remains uncertain. Methods: The medical records of 574 breast cancer patients from 2 different institutions (Mayo Clinic and University of Michigan) with sentinel lymph node biopsy examination and completion axillary lymph node dissection were reviewed for multiple clinicopathologic variables. The Memorial Sloan Kettering Cancer Center nomogram performance for prediction of NSN metastases was assessed. A new model was developed with clinically relevant variables and possible advantages. Results: The Memorial Sloan Kettering Cancer Center nomogram predicted the likelihood of NSN metastasis with an area under the receiver operating characteristic curve of .72 and .86. For predicted probability cut-off points of 5% and 10%, the false-negative rates were 0% and 14% (Mayo), and 17% and 11% (Michigan). A new model was developed with similar area under the curve but lower false-negative rates for low-probability subgroups. Conclusions: Predictive models for NSN tumor burden are imperfect.

Original languageEnglish (US)
Pages (from-to)543-550
Number of pages8
JournalAmerican journal of surgery
Volume190
Issue number4
DOIs
StatePublished - Oct 1 2005

Keywords

  • Breast cancer
  • Non-sentinel lymph node metastases
  • Predictive models
  • Sentinel lymph node

ASJC Scopus subject areas

  • Surgery

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