A nomogram to predict disease-free survival in patients with residual triple-negative breast cancer after neoadjuvant chemotherapy based on clinicopathological and sonographic features.
[BACKGROUND] Patients with triple-negative breast cancer (TNBC) who failed to achieve pathological complete response after neoadjuvant chemotherapy (NAC) may have a poorer prognosis.
- p-value P=0.004
- p-value P=0.027
- 95% CI 1.152-10.359
- HR 3.455
APA
Zheng Q, Jin Z, et al. (2026). A nomogram to predict disease-free survival in patients with residual triple-negative breast cancer after neoadjuvant chemotherapy based on clinicopathological and sonographic features.. Translational cancer research, 15(1), 56. https://doi.org/10.21037/tcr-2025-aw-2182
MLA
Zheng Q, et al.. "A nomogram to predict disease-free survival in patients with residual triple-negative breast cancer after neoadjuvant chemotherapy based on clinicopathological and sonographic features.." Translational cancer research, vol. 15, no. 1, 2026, pp. 56.
PMID
41674992
Abstract
[BACKGROUND] Patients with triple-negative breast cancer (TNBC) who failed to achieve pathological complete response after neoadjuvant chemotherapy (NAC) may have a poorer prognosis. This study aimed to explore the factors associated with the adverse outcomes of these patients, and to develop a nomogram model for predicting disease-free survival (DFS).
[METHODS] Patients diagnosed with TNBC at our institution between 2013 and 2022 were retrospectively evaluated. Clinicopathological and sonographic features associated with DFS were identified through multivariate Cox regression analysis to establish a nomogram model. The predictive performance of the nomogram model was assessed using receiver operating characteristic (ROC) curves and calibration curves.
[RESULTS] A total of 103 TNBC patients with residual lesions following NAC were included in this study, with 15 cases (14.6%) experiencing DFS events. Multivariate analysis revealed that the pathological type of non-invasive ductal carcinoma [hazard ratio (HR) =7.741, 95% confidence interval (CI): 1.928-31.081, P=0.004], lymph node involvement (HR =3.455, 95% CI: 1.152-10.359, P=0.027), and the presence of a hyperechoic halo on ultrasound images (HR =4.43, 95% CI: 1.164-16.852, P=0.029) were independent prognostic factors associated with poor DFS. Patients with multiple risk factors exhibited worse survival outcomes. The areas under the ROC curve for predicting 2-, 3-, 4-, and 5-year DFS rates in the nomogram model were 0.767, 0.786, 0.785, and 0.739, respectively. The calibration curves demonstrated excellent consistency between the nomogram-predicted and actual survival probabilities.
[CONCLUSIONS] Our study developed a nomogram model to predict poor survival outcomes in TNBC patients with residual lesions after NAC, which may provide guidance for treatment strategies in high-risk populations.
[METHODS] Patients diagnosed with TNBC at our institution between 2013 and 2022 were retrospectively evaluated. Clinicopathological and sonographic features associated with DFS were identified through multivariate Cox regression analysis to establish a nomogram model. The predictive performance of the nomogram model was assessed using receiver operating characteristic (ROC) curves and calibration curves.
[RESULTS] A total of 103 TNBC patients with residual lesions following NAC were included in this study, with 15 cases (14.6%) experiencing DFS events. Multivariate analysis revealed that the pathological type of non-invasive ductal carcinoma [hazard ratio (HR) =7.741, 95% confidence interval (CI): 1.928-31.081, P=0.004], lymph node involvement (HR =3.455, 95% CI: 1.152-10.359, P=0.027), and the presence of a hyperechoic halo on ultrasound images (HR =4.43, 95% CI: 1.164-16.852, P=0.029) were independent prognostic factors associated with poor DFS. Patients with multiple risk factors exhibited worse survival outcomes. The areas under the ROC curve for predicting 2-, 3-, 4-, and 5-year DFS rates in the nomogram model were 0.767, 0.786, 0.785, and 0.739, respectively. The calibration curves demonstrated excellent consistency between the nomogram-predicted and actual survival probabilities.
[CONCLUSIONS] Our study developed a nomogram model to predict poor survival outcomes in TNBC patients with residual lesions after NAC, which may provide guidance for treatment strategies in high-risk populations.
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