Development and validation of a survival-predicting nomogram for HER2-negative T1-3N0-1 breast cancer treated with breast-conserving surgery: a Surveillance, Epidemiology, and End Results (SEER) database analysis.

Background: Human epidermal growth factor receptor 2 (HER2)-negative early-stage breast cancer (BC) exhibits significant heterogeneity, complicating personalized treatment decisions after breast-conserving surgery (BCS). Robust tools integrating baseline risk, treatment response, and sociodemographic factors are needed to optimize survival while minimizing unnecessary toxicity. This study aimed to create a clinical decision-support tool that leverages these multifaceted factors to optimize survival outcomes and minimize treatment toxicity for these patients. Methods: Utilizing population-level data from the Surveillance, Epidemiology, and End Results (SEER) program (cases from 2010 to 2016; n=8,384), we constructed and validated prognostic nomograms for overall survival (OS) and cancer-specific survival (CSS) in a cohort of HER2-negative, T1-3N0-1 BC patients who underwent BCS followed by radiotherapy. Key prognostic variables were identified through multivariable Cox proportional hazards regression. The performance of the nomograms was rigorously assessed using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA). Finally, risk stratification was performed by applying optimal cut-off points determined via X-tile software. Results: Key independent predictors included tumor grade, tumor (T) stage, estrogen receptor (ER)/progesterone receptor (PR) status, marital status, and single primary tumor status. Nomograms significantly outperformed American Joint Committee on Cancer (AJCC) 7th staging (OS C-index: 0.69 Conclusions: We developed the first validated nomograms integrating tumor biology, treatment response, and social factors to optimize HER2-negative BC management. Identifying 'single primary tumor' status as a novel prognostic indicator point to novel tumorigenesis mechanisms. Critically, our findings enable actionable strategies: low-risk patients (33%) may be candidates for avoiding chemotherapy toxicity, while high-risk patients (27%) are potential candidates for more intensive treatment strategies. Patients who fail to achieve a CR should be considered for enrollment in adjuvant trials with novel agents. Adding prospective biomarkers will further refine these precision approaches.