Development and Validation of a Nomogram for Individually Predicting Pathologic Complete Remission After Preoperative Chemotherapy in Chinese Breast Cancer: A Population-Based Study.

PURPOSE: To explore the independent predictors of pathologic complete remission response (pCR) for Chinese patients with breast cancer (BC) after preoperative chemotherapy and to develop an individualized nomogram for predicting the probability of pCR.

PATIENTS AND

METHODS

The clinicopathologic data of clinical stage I-III BC patients who received preoperative chemotherapy in Xijing Hospital were retrospectively analyzed. A total of 689 BC patients diagnosed in 2015-2017 were included in the training set to develop a nomogram. A separate cohort of 357 patients in the same center was regarded as a validation set for externally examining the performance of the model. The area under the receiver operating characteristic curve and calibration curve were used to verify the predictive performance of the nomogram.

RESULTS

Multivariate logistic regression analysis showed that independent predictors of pCR were menopause status at diagnosis, family history of BC, initial tumor size, estrogen receptor status, HER2/neu (human epidermal growth factor receptor 2) status, and Ki-67 expression. On the basis of these factors, a nomogram was developed using R software. Our nomogram had good discrimination in the training and validation set (area under the receiver operating characteristic curve, 0.762 and 0.768, respectively). The calibration curves further confirmed that the model performs well.

CONCLUSION

Menopause status and family history of BC were independent predictors of pCR after preoperative chemotherapy for the first time. The nomogram can accurately predict pCR rate in BC, which may provide some guidelines for breast surgery options and patient counseling.