A Predictive Model for Axillary Node Pathologic Complete Response after Neoadjuvant Chemotherapy for Breast Cancer

Area of Science:

• Oncology
• Surgical Oncology
• Breast Cancer Research

Background:

• Sentinel lymph node biopsy (SNB) feasibility after neoadjuvant chemotherapy (NAC) is established, but patient selection remains challenging.
• Accurate identification of patients benefiting from SNB post-NAC is crucial for optimizing axillary staging.

Purpose of the Study:

• To develop and validate a predictive model for identifying patients with clinically node-positive (cN+) breast cancer likely to achieve a pathologic node-negative (pN0) response after NAC.
• To guide the selection of appropriate axillary staging procedures (SNB vs. ALND) in the post-NAC setting.

Main Methods:

• Utilized the National Cancer Data Base to identify cN+ breast cancer patients undergoing NAC and subsequent surgery.
• Randomly assigned patients into testing (70%) and validation (30%) cohorts for model development.
• Developed a predictive model based on preoperative factors significantly associated with pN0 response and breast tumor response.

Main Results:

• Multivariate analysis identified younger age, specific hormone receptor/HER2 statuses, high tumor grade, ductal histology, and extent of breast response as significant predictors of pN0.
• A 10-point scoring scale was developed, correlating with increased likelihood of pN0 response.
• The model demonstrated strong predictive accuracy with Area Under the Curve (AUC) values of 0.781 (testing) and 0.788 (validation).

Conclusions:

• The developed model effectively predicts pN0 response in cN+ breast cancer patients treated with NAC using preoperative factors.
• High-scoring patients are more likely to have negative nodes, supporting consideration of SNB over axillary lymph node dissection (ALND).
• This tool can aid in personalized treatment decisions for axillary staging after neoadjuvant chemotherapy.