Development and validation of a nomogram model for predicting disease-free survival in breast cancer patients after neoadjuvant chemotherapy

Motivation: Assessing prognosis and identifying high-risk factors for breast cancer patients after neoadjuvant chemotherapy (NAC) remains challenging. This study aims to improve prognostic accuracy and support clinical decision-making in this patient population. Goal(s): To evaluate the predictive performance of a nomogram based on clinicopathological and baseline MRI features for estimating disease-free survival (DFS) in breast cancer patients after NAC. Approach: Clinicopathological and MRI features were selected using univariate Cox and Lasso-Cox analyses to construct a nomogram, which was validated in an independent cohort. Results: The combined nomogram, integrating clinicopathological and MRI features, demonstrated a C-index of 0.706 in the training cohort for predicting DFS. Impact: This nomogram model facilitates early identification of high-risk recurrence factors, enabling personalized treatment and potentially improving survival outcomes for breast cancer patients post-NAC.