This study aimed to construct nomograms for predicting overall survival (OS), breast cancer-specific survival (BCSS) and risk stratification in breast cancer (BC) patients not achieving pathological complete response (pCR) after neoadjuvant chemotherapy (NACT).
Data on 500 consecutive BC patients who cannot attain pCR after NACT at two independent centers, were respectively collected. Cox proportional hazards regression (CPHR) analysis was implemented to confirm independent prognostic variables for survival. With respect to the discrimination, calibration ability, and clinical utility, we used the C-index, calibration plots and decision curve analysis (DCA) to assess the performance of the nomograms. The predictive accuracy of the models were compared with that of the traditional AJCC TNM staging system using C-index.
On multivariate CPHR analysis, seven determinant factors for survival were pointed out, including age, pathological T stage, pathological N stage, histological grade, ER, Ki67, and lymphovascular invasion. The C-indexs of the established OS- and BCSS-nomograms significantly outperformed than that of the AJCC TNM classification (0.789 vs 0.654; 0.803 vs 0.667, all p < 0.001). The calibration curves shown the good agreements between nomograms prediction and actual observations. Furthermore, DCA demonstrated that both OS- and BCSS-nomograms were superior to the AJCC TNM classification with the wider range of threshold probabilities. The risk stratification on the basis of the OS- and BCSS-nomograms indicated significant differences between Kaplan-Meier curves (p < 0.001).
We established and externally validated nomograms to accurately predict survival outcomes and make effective risk stratification in BC patients not achieving pCR after NACT.
Clinical trial identification
Legal entity responsible for the study
Sun Yat-sen Memorial Hospital, Sun Yat-sen University.
Has not received any funding.
All authors have declared no conflicts of interest.