3014 - The Role of Postoperative Radiotherapy Based on Nomogram Risk Stratification Model in De Novo Metastatic Breast Cancer

03:00pm - 04:00pm PT

Hall F

Screen: 3

POSTER

Presenter(s)

Ling-xiao Xie, MS - the First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui

L. X. Xie¹, J. Wang¹, Y. Zhang¹, T. Wang¹, and Y. C. Zhou^1,2; ¹Department of Radiation Oncology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China, ²Anhui Province Key Laboratory of Respiratory Tumor and Infectious Disease, Bengbu Medical University, Bengbu, China

Purpose/Objective(s):

With the widespread application of novel therapeutic agents and evolving paradigms in treatment concepts, the prognosis of de novo Metastatic Breast Cancer (dnMBC) has undergone substantial improvement. However, the efficacy of primary lesion resection (PLR) combined with postoperative radiotherapy (PORT) in enhancing survival outcomes for dnMBC patients remains controversial. This study aims to evaluate clinical outcomes in dnMBC patients following PLR and employ a nomogram-based risk stratification model to identify potential beneficiaries of PORT.

Materials/Methods:

A retrospective analysis of dnMBC patients from the SEER database (2016-2021) assessed the impact of PLR on Overall survival (OS) and breast cancer-specific survival (BCSS). Cox regression identified prognostic factors in the non-PORT cohort, which were used to construct a nomogram validated through ROC, calibration, and decision curve analysis (DCA). X-tile determined optimal risk thresholds, and PSM balanced baseline characteristics between PLR and non-PLR groups.

Results:

The clinical data of 21,241 patients were included. The median follow-up duration was 29 months, with a corresponding median BCSS of 33 months. Among these patients, 3,750 (17.6%) underwent PLR, and their BCSS was significantly prolonged compared to Non-PLR cohort (P<0.001). In the non-PORT cohort, multivariate Cox regression analysis identified prognostic factors associated with longer BCSS: age <65 years, pathological grade I-II, early TNM stage, non-triple-negative subtype, absence of brain/bone/liver metastasis, and receipt of chemotherapy (P<0.05 for all). These factors were integrated into a nomogram to predict survival outcomes. The model demonstrated excellent discriminative performance in the training set, with a C-index of 0.72 (95% CI: 0.70-0.75). Calibration curves and DCA confirmed good predictive accuracy and clinical utility. Based on nomogram scores, patients were stratified into low-risk (0-100), intermediate-risk (101-179), and high-risk (180-338) groups, with significantly different BCSS across groups (P<0.001). PSM adjusted survival analysis revealed that PORT improved BCSS in the overall postoperative population (P<0.001). Subgroup analysis showed significant benefits in low- and intermediate-risk groups (P<0.001), whereas high-risk patients exhibited no survival advantage from PORT (P=0.224).

Conclusion: (1) Large-sample data based on the modern treatment model indicate that PLR improves the long-term survival in dnMBC patients, and PORT demonstrating additional prognostic benefits. (2) The risk stratification model shows good predictive performance. Patients classified as low- and intermediate-risk may derive significant survival benefits from PORT.