Development of Nomogram for Predicting Axillary Pathologic Complete Response after Neoadjuvant Therapy in Breast Cancer Patients without Distant Metastasis
Author(s): Jian Zhang, Hong-Ming Cao, Gao-Yuan Wang, Chang-Bo Nie, Shou-Min Bai, Shuang Ma
Background: For N+ breast cancer patients treated with neoadjuvant therapy, the response to the treatment, especially the probability of axillary pathological complete response (apCR), can guide the choice of subsequent surgical strategy.
Method: 50 N+ breast cancer patients were treated with neoadjuvant therapy, with the response to neoadjuvant therapy guiding subsequent surgical modalities. Logistic regression was used to calculate the coefficients of the significant predictors for axillary pathologic complete response (apCR), and a nomogram was developed based on the logistic model and internally validated.
Results: 4 variables were found to be related to the probability of apCR: pathological grade and molecular subtype (HER2+), neu-trophil-to-lymphocyte ratio (NLR), and monocyte-to-lymphocyte ratio (MLR). The nomogram based predictive cooperating pathological features and hematological test results can be used to predict apCR in N+ breast cancer patients who had received neoadjuvant chemotherapy (NAC). The receiver operating characteristic (ROC) curve for the nomogram model is 0.929 [95% confi-dence interval (CI): 0.859–0.998], indicating a good discrimination.
Conclusion: A comprehen-sive predictive model using clinical data is a useful tool to predict the probability of apCR in N+ breast cancer patients receiving NAC.