An ultrasound-based nomogram for predicting axillary node pathologic complete response after neoadjuvant chemotherapy in breast cancer: Modeling and external validation.

INTRODUCTION: The staging and treatment of axillary nodes in breast cancer have become a focus of research. For breast cancer patients with fine-needle aspiration-or core needle biopsy-confirmed positive nodes, axillary lymph node dissection (ALND) after neoadjuvant chemotherapy (NAC) is still a standard treatment. However, some patients achieve an axillary pathologic complete response (pCR) after NAC. In this study, the authors sought to construct a model to predict axillary pCR in patients with positive axillary lymph nodes (cN+) breast cancer. METHODS: Data from patients with pathologically proven cN+ breast cancer treated with NAC followed by ALND between January 2010 and April 2019 at the Peking University Cancer Hospital were reviewed. Axillary lymph node status was assessed using ultrasonography before and after NAC. The patient cohort was assigned to the construction and internal validation cohorts according to admission time. A nomogram was constructed based on the significant factors associated with axillary pCR. The predictive performance of the model was externally validated using data from Peking University First Hospital. RESULTS: This study included 953 and 267 patients from Peking University Cancer Hospital and Peking University First Hospital, respectively. In the construction cohort, 39.7% (238 of 600) of patients achieved axillary pCR after NAC. The result of multivariate logistic regression analysis showed that tumor grade, clinical nodal response, NAC regimen, tumor pCR, lymphovascular invasion, and tumor biologic subtype were significant independent predictors of ypN0 (p < 0.05). The areas under the receiver operating characteristic curves for the construction, validation, and independent testing cohorts were 0.87 (95% confidence interval [CI], 0.84-0.90), 0.83 (95% CI, 0.79-0.87), and 0.84 (0.79-0.89), respectively. CONCLUSIONS: A nomogram was constructed to predict the pCR of axillary lymph nodes after NAC for breast cancer. Validation of both the internal and external cohorts achieved good predictive performance, indicating that the model has preliminary clinical application prospects.

De novo metastatic lobular breast carcinoma: A population-based study from SEER database.

PURPOSE: Patients with metastatic lobular breast carcinoma constitute a heterogeneous group with distinguishing features. Our aim was to describe the features and survival of them, and further subdivide them into subcategories for prognostic stratification and treatment planning. PATIENTS AND METHODS: Patients with de novo metastatic breast cancer from 2010 to 2018 were identified using the SEER database. Multivariate logistic regression analysis was conducted to calculate odds ratios. The within-pair difference was minimized by propensity score matching. Multiple comparisons based on Cox proportional hazards model were performed to investigate the interactions of M1 subcategory and treatment modality on survival. RESULTS: A total of 1,675 patients with de novo metastatic lobular breast carcinoma were identified, they were more likely to have HR+/HER2- subtype, low histologic grade, low T/N stage, fewer metastatic sites, but worse prognosis compared with patients with metastatic ductular breast carcinoma. The M1 stage was subdivided into 3 subcategories with significantly different prognoses. The benefits of primary tumor surgery were more pronounced in M1a/b disease, whereas the benefits of chemotherapy increased with the progression of metastatic disease. CONCLUSION: Patients with metastatic lobular breast carcinoma have unique clinicopathological characteristics and metastatic patterns. M1 subcategory assists prognosis stratification and treatment planning for such patients.