Predicting pathological complete response after neoadjuvant chemotherapy: A nomogram combining clinical features and ultrasound semantics in patients with invasive breast cancer - Wang, Ke-Nie; Meng, Ya-Jiao; Yu, Yue; Cai, Wen-Run; Wang, Xin; Cao, Xu-Chen; Ge, Jie (Frontiers in Oncology, 2023)
Background Early prediction of patients outcome is required for the sensitivity to neoadjuvant chemotherapy (NAC). So, we aimed to develop a prognostic model based on optimal cut-off points of the largest diameter decrease measured by ultrasound in patients with invasive breast cancer (IBC). Methods Total of 480 IBC patients were enrolled who underwent anthracycline and taxane-based NAC between 2018 and 2020. The decrease rate of the largest diameter was calculated by ultrasound after NAC and their cut-off points were determined among subtypes. Thereafter, a nomogram was constructed based on clinicopathological and ultrasound-related data, and validated using the calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and clinical impact curve (CIC). Results Our analysis showed that pathological complete response (pCR) was achieved in 20.6% of patients, with the highest being in HER2 positive and the absence of luminal A-like subtypes. The optimal cut-off points for predicting pCR were 53.23%, 51.56%, 41.89%, and 53.52% in luminal B-like (HER2 negative), luminal B-like (HER2 positive), HER2 positive, and triple negative, respectively. In addition, time interval, tumor size, molecular subtypes, largest diameter decrease rate, and change of blood perfusion were significantly associated with pCR (all p < 0.05). The prediction model based on the above variables has great predictive power and clinical value. Conclusion Taken together, our data demonstrated that calculated cut-off points of tumor reduction rates could be reliable in predicting pathologic response to NAC and developed nomogram predicting prognosis would help tailor systematic regimens with high precision.