A Nomogram to Predict Breast Tumor Regression Patterns after Neoadjuvant Chemotherapy Based on Baseline Characteristics

Background Breast cancers show different regression patterns after neoadjuvant chemotherapy. Certain regression patterns are associated with more reliable margins in breast-conserving surgery. Our study aims to establish a nomogram based on clinicopathological factors and laboratory indicators to predict regression patterns in breast cancer patients. Methods We retrospectively reviewed 320 patients with stage II-III breast cancer who received neoadjuvant chemotherapy and had definitive surgery in our center from January 2016 to December 2019. Tumor regression patterns were categorized as type 1 (concentric regression + pCR) and type 2 (multifocal residues + SD + PD) based on mass pathological results. A multivariate logistic regression model was applied to distinguish predictive factors for tumor regression patterns. A nomogram was built based on five predictive factors from the multivariate logistic regression model. Results Molecular subtypes were not significantly associated with tumor regression patterns. Multivariate analysis identified five independent indicators: menopausal status, estrogen receptor status, T stage, N stage and lymphocyte to monocyte ratio. The nomogram yielded an area under the curve (AUC) of 0.70 (95% confidence interval 0.62-0.78) based on these factors. The calibration plot accompanied by the Hosmer–Lemeshow goodness-of-fit (GOF) test ( p -value =0.9) showed good consistency between the estimated probabilities and the actual rate of type 1 cases. Conclusion HR+/HER2- breast cancers are more likely to have type 2 regression after neoadjuvant chemotherapy. Five baseline factors, including clinicopathological factors and laboratory indexes, were incorporated to establish a nomogram, which exhibited a satisfactory discriminatory ability for predicting different patterns of tumor regression.