A Clinical Model of Bone Angiosarcoma Patients: A Population‐based Analysis of Epidemiology, Prognosis, and Treatment

Abstract

Objective: To investigate the epidemiological data, prognostic factors, and treatment outcomes of bone angiosarcoma (BA). Methods: This retrospective study was based on the Surveillance, Epidemiology, and End Results (SEER) database. The medical records of BA patients were selected from the SEER database from 1975 to 2016. Variables including patients' baseline demographics (age, sex, marital status, and year of diagnosis), tumor characteristics (tumor size, grade, and SEER Historic Stage A), and treatment (surgery and radiotherapy) were selected for further analysis. The research endpoints were overall survival (OS) and cancer-specific survival (CSS). The optimal cutoff values of continuous variables including age, year of diagnosis, and tumor size were identified using the X-tail program. Univariate Cox regression was used to identify potential prognostic factors and multivariate Cox regression was used to identify independent prognostic factors. All prognostic factors were included to predict the survival time compared to the median OS and CSS times via the novel nomograms. To validate the internal validation of nomograms, we analyzed the concordance indices (C-index). Results: This study enrolled a total of 271 patients with malignant vascular bone tumors among residents of the United States between 1975 and 2016. After applying the exclusion criteria (one case without active follow-up), this study included 152 patients with BA. The median survival time of BA was significantly shorter than that of malignant vascular bone tumors for OS (9 months vs 27 months, P < 0.001). Age, year of diagnosis, tumor size, grade, stage, and surgery were identified as potential prognostic factors for OS or CSS in univariate Cox regression. However, only age (P < 0.001, P < 0.001), stage (P = 0.002, P < 0.001), and surgery (P = 0.001, P = 0.002) were independent prognostic factors for CSS and OS, respectively, in the multivariate analysis. Younger patients less than 54 years have significantly better prognosis for CSS/OS than patients between 54 and 67 years (Hazard ratios [HRs]: 1.651 [1.763-3.575], 2.557 [1.395-4.687]) and more than 67 years (HRs: 4.404 [2.237-8.670], 5.113 [2.923-8.942]). For CSS/OS, the survival time of patients with localized stage was significantly longer than that of patients with regional stage (HRs: 1.530 [0.725-3.228], 1.548 [0.834-2.873]) and that of patients with distant stage (HRs: 1.706 [0.899-3.237], 2.101 [1.254-3.520]). Patients with surgery had more survival time than patients without surgery for CSS/OS (HRs: 2.861 [1.542-5.310], 2.103 [1.308-3.379]). All factors were further included to generate nomograms for CSS and OS. The C-indexes for the internal validation of OS and CSS prediction were 0.787 (95% confidence interval [CI]: 0.738-0.836) and 0.768 (95% CI: 0.717-0.819), respectively. Conclusions: Age, stage, and surgery were closely associated with prognosis in patients with BA, and this clinical model was a favorable tool to evaluate survival possibilities.

Prognostic nomograms for predicting overall survival and cancer-specific survival in patients with angiosarcoma, a SEER population-based study

“…As for the histologic grade, a recent study concluded AS with grade III histology tended to experience a shorter survival which was consistent with our result 15 . The median survival time of AS was various in different primary sites 16 – 18 , but which site with the highest mortality has not been well documented. Our study elaborated AS from heart mediastinum harbored the highest risk compared with soft tissue, bone and peritoneum.…”

New nomograms to predict overall and cancer‐specific survival of angiosarcoma

“…It also indirectly led to a poor prognosis for the elderly patients. In fact, morbidity and mortality increase with age in many solid tumors 33,34 . The clinical factors used in the nomogram to predict OS in patients with AS included age.…”

“…In fact, morbidity and mortality increase with age in many solid tumors. 33 , 34 The clinical factors used in the nomogram to predict OS in patients with AS included age. In our study, stage was also identified as an important prognostic factor and it was used for the calculation of nomograms for OS and CSS.…”

Personalized Surgical Planning for Soft Tissue Sarcoma of the Popliteal Fossa with a Novel 3D Imaging Technique

“…Soft tissue sarcomas (STSs) account for approximately 1% of all malignancies in adults and have more than a hundred subtypes 1–4 . An estimated 13,460 new STS diagnoses were made in the U.S. in 2021, along with 5350 related deaths 5 .…”

“…Soft tissue sarcomas (STSs) account for approximately 1% of all malignancies in adults and have more than a hundred subtypes. 1 , 2 , 3 , 4 An estimated 13,460 new STS diagnoses were made in the U.S. in 2021, along with 5350 related deaths. 5 The common histotypes include liposarcoma, leiomyosarcoma, and undifferentiated pleomorphic sarcoma, with the most typical primary sites being the extremities (40%–50%), trunk (13%), and retroperitoneal space (7%).…”