Nomogram construction for overall survival in breast angiosarcoma based on clinicopathological features: a population-based cohort study.

Abstract

Background: Breast angiosarcoma (BAS) is a rare, aggressive malignancy with a poor prognosis, often challenging to assess due to its unique biology. This study aimed to develop a nomogram to predict 3- and 5-year overall survival (OS) for BAS patients using key clinicopathological factors.

Methods: Data from 450 BAS patients diagnosed between 2000 and 2021 were extracted from SEER database. Key variables, including age, tumor size, tumor grade, and distant metastasis status, were identified through univariate and multivariate Cox regression analyses. These factors were incorporated into a nomogram for OS prediction. The model was validated internally and externally using the concordance index (C-index), calibration curves, and decision curve analysis (DCA) to assess its predictive accuracy and clinical utility.

Results: The nomogram demonstrated good predictive accuracy, with a C-index of 0.68 in the training set and 0.72 in the test set. ROC analysis indicated strong short-term predictive power, with AUC values of 0.81 and 0.75 for 1-year survival in the training and test sets, respectively, though predictive performance declined over time. DCA showed substantial clinical benefit for 12-month predictions, which diminished over longer time frames. The model effectively distinguished high-risk BAS patients and provided individualized survival estimates, supporting its potential use in clinical decision-making.

Conclusion: This study presents the first BAS nomogram for OS prediction, showing robust short-term accuracy. The long-term utility is limited by heterogeneity and sample size, highlighting the need for external validation to confirm generalizability and clinical applicability.