Predicting sentinel lymph node metastasis in breast cancer: a study based on the SEER database

Area of Science:

• Oncology
• Surgical Oncology
• Biostatistics

Background:

• Sentinel lymph node biopsy (SLNB) is standard for axillary-negative breast cancer but invasive.
• SLNB complications can affect patient quality of life.
• Identifying patients who can safely avoid SLNB is crucial.

Purpose of the Study:

• Develop a nomogram to predict sentinel lymph node metastasis (SLNM).
• Utilize the SEER database for prediction model development.
• Identify breast cancer patients who may benefit from avoiding SLNB.

Main Methods:

• Identified SLNB patients from the SEER database (1-5 lymph nodes examined).
• Randomly assigned patients to training (3:1) and validation cohorts.
• Employed logistic regression and validated the nomogram using ROC curves, calibration curves, and decision curve analysis.

Main Results:

• Identified independent predictive factors for SLNM: age, race, primary site, T/M stage, histological grade, pathological type, ER/PR status.
• Successfully developed a predictive nomogram for sentinel lymph node status.
• Achieved AUC values of 0.711 (training) and 0.700 (validation).

Conclusions:

• Established a nomogram for SLNM prediction with robust clinical efficacy.
• The nomogram offers valuable predictive information for patient management.
• Provides a reference for selecting patients who may be exempt from SLNB.