Factors Affecting Pathologic Complete Response Following Neoadjuvant Chemotherapy in Breast Cancer: Development and Validation of a Predictive Nomogram

Background: There is an increasing need to develop a more accurate prediction model for pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer. Purpose: To develop a nomogram based on MRI and clinical-pathologic variables to predict pCR. Materials and Methods: In this single-center retrospective study, consecutive women with stage II-III breast cancer who underwent NAC followed by surgery between January 2011 and December 2017 were considered for inclusion. The women were divided into a development cohort between January 2011 and September 2015 and a validation cohort between October 2015 and December 2017. Clinical-pathologic data were collected, and mammograms and MRI scans obtained before and after NAC were analyzed. Logistic regression analyses were performed to identify independent variables associated with pCR in the development cohort from which the nomogram was created. Nomogram performance was assessed with the area under the receiver operating characteristic curve (AUC) and calibration slope. Results: A total of 359 women (mean age, 49 years. 10 [standard deviation]) were in the development cohort and 351 (49 years. 10) in the validation cohort. Hormone receptor negativity (odds ratio [OR], 3.1; 95% CI: 1.4, 7.1; P =.006), high Ki-67 index (OR, 1.05; 95% CI: 1.03, 1.07; P < .001), and post-NAC MRI variables, including small tumor size (OR, 0.6; 95% CI: 0.4, 0.9; P =.03), low lesion-to-background parenchymal signal enhancement ratio (OR, 0.2; 95% CI: 0.1, 0.6; P =.004), and absence of enhancement in the tumor bed (OR, 3.8; 95% CI: 1.4, 10.5; P =.009) were independently associated with pCR. The nomogram incorporating these variables showed good discrimination (AUC, 0.90; 95% CI: 0.86, 0.94) and calibration abilities (calibration slope, 0.91; 95% CI: 0.69, 1.13) in the independent validation cohort. Conclusion: A nomogram incorporating hormone receptor status, Ki-67 index, and MRI variables showed good discrimination and calibration abilities in predicting pathologic complete response. (C) RSNA, 2021

Automated summary

A nomogram incorporating MRI and clinical-pathologic variables was developed to predict pathologic complete response after neoadjuvant chemotherapy in breast cancer. The nomogram showed good discrimination and calibration abilities, effectively identifying independent variables associated with pCR.