Predicting the extent of nodal involvement for node positive breast cancer patients: Development and validation of a novel tool

Ingrid van den Hoven, David van Klaveren, Nicole C. Verheuvel, Raquel F. D. van la Parra, Adri C. Voogd*, Wilfred K. de Roos, Koop Bosscha, Esther M. Heuts, Vivianne C. G. Tjan-Heijnen, Rudi M. H. Roumen, Ewout W. Steyerberg

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background This study aimed to develop an easy to use prediction model to predict the risk of having a total of 1 to 2, >= 3, or >= 4 positive axillary lymph nodes (LNs), for patients with sentinel lymph node (SLN) positive breast cancer. Methods Data of 911 SLN positive breast cancer patients were used for model development. The model was validated externally in an independent population of 180 patients with SLN positive breast cancer. Results Final pathology after ALND showed additional positive LN for 259 (28%) of the patients. A total of 726 (81%) out of 911 patients had a total of 1 to 2 positive nodes, whereas 175 (19%) had >= 3 positive LNs. The model included three predictors: the tumor size (in mm), the presence of a negative SLN, and the size of the SLN metastases (in mm). At external validation, the model showed a good discriminative ability (area under the curve = 0.82; 95% confidence interval = 0.74-0.90) and good calibration over the full range of predicted probabilities. Conclusion This new and validated model predicts the extent of nodal involvement in node-positive breast cancer and will be useful for counseling patients regarding their personalized axillary treatment.
Original languageEnglish
Pages (from-to)578-586
Number of pages9
JournalJournal of Surgical Oncology
Volume120
Issue number4
Early online date23 Jul 2019
DOIs
Publication statusPublished - Sep 2019

Keywords

  • area under curve
  • breast neoplasms
  • nomograms
  • sentinel lymph node
  • SENTINEL LYMPH-NODE
  • INTERNATIONAL MULTICENTER TOOL
  • METASTASES
  • ULTRASOUND
  • NOMOGRAM
  • DISEASE
  • BIOPSY
  • RISK

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