Establishment and external validation of a prognostic model for predicting disease-free survival and risk stratification in breast cancer patients treated with neoadjuvant chemotherapy

Background: The eighth edition of the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system for survival prediction and risk stratification in breast cancer (BC) patients after neoadjuvant chemotherapy (NCT) is of limited efficacy. This study aimed to establish a novel prognostic nomogram for predicting disease-free survival (DFS) in BC patients after NCT. Patients and methods: A total of 567 BC patients treated with NCT, from two independent centers, were included in this study. Cox proportional-hazards regression (CPHR) analysis was conducted to identify the independent prognostic factors for DFS, in order to develop a model. Subsequently, the discrimination and calibration ability of the prognostic model were assessed in terms of its concordance index (C-index), risk group stratification, and calibration curve. The performance of the nomogram was compared with that of the eighth edition of the AJCC TNM staging system via C-index. Results: Based on the CPHR model, eight prognostic predictors were screened and entered into the nomogram. The prognostic model showed better performance (p<0.01) in terms of DFS prediction (C-index: 0.738; 95% CI: 0.698-0.779) than the eighth edition of the AJCC TNM staging system (C-index: 0.644; 95% CI: 0.604-0.684). Stratification into three risk groups highlighted significant differences between the survival curves in the training cohort and those in the validation cohort. The calibration curves for likelihood of 3- and 5-year DFS indicated optimal agreement between nomogram predictions and actual observations. Conclusion: We constructed and externally validated a novel nomogram scoring system for individualized DFS estimation in BC patients treated with NCT. This user-friendly predictive tool may help oncologists to make optimal clinical decisions.