With the global expansion of breast cancer screening, early-stage detection, particularly clinical stage T1 breast cancer, has become increasingly common. Accurate prognosis for T1 cancer is closely linked to lymph node metastasis status. While breast ultrasound and mammography are standard for screening, they are suboptimal for axillary lymph node assessment. This study aimed to predict lymph node metastasis by analyzing primary tumor imaging characteristics. We retrospectively analyzed 148 patients with pathologically confirmed stage T1 breast cancer. Multivariate logistic regression identified independent risk factors for lymph node metastasis from breast ultrasound and mammography features. Subsequently, a line graph model was established to predict axillary lymph node metastasis. A predictive nomogram was developed and validated, demonstrating good discrimination with area under the receiver operating characteristic curve of 0.78 (training set) and 0.72 (validation set). The model also showed favorable calibration and clinical utility via decision curve analysis. In conclusion, this model can provide risk stratification for clinical T1-stage breast cancer axillary lymph node metastasis, which to some extent aids clinical decision-making, thereby reducing missed diagnoses and unnecessary invasive procedures. However, further prospective validation is still required.
Liang et al. (Fri,) studied this question.