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.
Keywords: area under curve; breast neoplasms; nomograms; sentinel lymph node.
© 2019 The Authors. Journal of Surgical Oncology Published by Wiley Periodicals, Inc.