A novel web-based prognostic nomogram and the features influencing the curative effect of chemotherapy and radiotherapy for Paget's disease with invasive ductal carcinoma

Paget's disease (PD) of the breast is a rare underlying malignant tumor. Approximately 50% to 60% of patients with mammary PD are concurrently diagnosed with invasive ductal carcinoma (PD-IDC), a condition as-sociated with a worse prognosis than IDC without PD. Thus far, there has been a lack of an accurate and efficient prognostic model for PD-IDC, and the factors influencing the effectiveness of chemotherapy and radiotherapy for these patients remain unknown. In this study, we developed a web-based nomogram based on the data from the Surveillance Epidemiology and End Results (SEER) database. We subjected the model to a series of validation meth-ods, including area under the curve (AUC) values, receiver operating characteristic curve (ROC) analysis, calibration curves, and decision curve analysis (DCA). Our results demonstrated that our model exhibited high discrimination, accuracy, and clinical applicability in predicting the overall survival (OS) of patients with PD-IDC (testing set: three -and five-year AUCs, 0.831 and 0.841, respectively). To further validate our nomogram, we used external data from both our institution and sister hospitals (external data: three-and five-year AUCs, 0.892 and 0.914, respectively). Multivariable Cox regression analysis identified several independent unfavorable prognostic factors for the OS of patients with PD-IDC, including increasing age, high grade, widowed status, higher T stages, and the presence of bone metastases. Furthermore, propensity score matching (PSM)-adjusted analysis was conducted, revealing that chemotherapy did not significantly improve the survival of patients with PD-IDC across molecular subtypes, except for those in the grade III/IV group, where it improved both OS and breast cancer-specific survival (BCSS). Addition-ally, our findings indicated that only patients with PD-IDC with T4 and N3 stages benefited from radiotherapy, leading to improvements in both OS and BCSS. In conclusion, we have comprehensively analyzed the clinical characteristics and prognosis of patients with PD-IDC, culminating in the development of a user-friendly web-based nomogram for predicting their survival. Our predictive model is not only highly accurate but also offers simplicity, making it ac-cessible for healthcare providers and patients. Furthermore, our stratified analysis highlights that the pathological grade, rather than the molecular subtype, plays a pivotal role in determining the efficacy of chemotherapy in improv-ing the prognosis for patients with PD-IDC, while radiotherapy confers survival benefits to patients with PD-IDC in T4 and N3 stages.