Angiosarcoma is a rare aggressive and understudied soft tissue sarcoma with pending evidence-based treatment guidelines due to varying study cohorts and inconsistent outcome measures. Surgery with wide resection is currently considered to be the cornerstone in management. In a population-based cohort identified from Danish National Health Registers between 2000 and 2017, this study aimed to define prognostic factors in patients with newly diagnosed soft tissue angiosarcoma. Kaplan–Meier survival analysis demonstrated 5-year overall survival of 28%. Competing risk analysis demonstrated cumulative incidence of local recurrence of 30% and metastasis of 43%. Multivariable Cox models among 154 included patients demonstrated age above 60 years and metastasis to be independently associated with worse overall survival. Cutaneous tumors, surgery, and negative resection margin were independently associated with improved overall survival. Adjuvant oncological treatment did not improve overall survival, risk of metastasis, or recurrence. Negative margin was not associated with lower risk of recurrence and metastasis. We conclude that, despite demonstrated improved survival after surgery with wide resection, overall survival remains poor.

Background: Soft-tissue sarcomas (STSs) are rare and challenging to diagnose due to their heterogeneous presentation. In 2009, Denmark introduced the Cancer Patient Pathways for sarcomas (CPPs) to improve sarcoma treatment by streamlining diagnostic and therapeutic processes. The primary objective of this study is to evaluate the impact of the CPPs on the overall survival of patients with deep-seated, high-grade STSs, comparing outcomes from before and after CPP implementation. Methods: A retrospective cohort study was conducted using data from 712 patients diagnosed with high-grade STSs in the extremities or trunk wall between 2000 and 2018. Patients were grouped into pre-CPP (2000–2008) and post-CPP (2010–2018) cohorts. Overall survival was analyzed using Kaplan–Meier estimates. Results: The five-year overall survival improved from 43% in the pre-CPP cohort to 52% post-CPP (p = 0.05). Time-to-treatment was significantly reduced in the post-CPP cohort, with a median decrease of 3 days (18 vs. 15 days, p < 0.001). We found only a very weak tendency toward larger tumor sizes in the pre-CPP cohort and no difference regarding the percentage of patients that had distant metastases at diagnosis between cohorts. In the post-CPP cohort, the percentage of whoops operations decreased and the use of oncological services increased. Conclusions: After the introduction of the CPPs for the sarcoma patients, overall survival improved and time to treatment was reduced. This study highlights the importance of efficient referral pathways in improving cancer outcomes but cannot exclude that other factors could also have contributed.

Two national sarcoma centers have had different approaches for selecting patients with grade 2–3 deep-seated soft tissue sarcomas (STS) for postoperative radiotherapy (RT). We evaluated potential differences in local recurrence in patients treated at the two centers. At Sarcoma Center 1 (SC1), RT was the standard treatment for all tumors except certain small tumors excised with a margin wider than 1 cm. Sarcoma Center 2 (SC2) avoided RT for tumors regardless of tumor size if removed with a margin wider than 1 cm and/or a solid barrier. We included 386 patients (SC1/SC2 = 196/190) over 18 years of age diagnosed with a non-metastatic grade 2–3, deep-seated STS of the extremities or trunk wall, who underwent primary surgical treatment (only tumors excised with a negative margin) from 1 January 2000, to 31 December 2016. Kaplan–Meier survival analysis, competing risk analysis, and cause-specific Cox regression were applied. A total of 284 patients received primary RT, 163 (83%) at SC1 and 121 (64%) at SC2 (p < 0.001). The cumulative incidence of local recurrence at five years was 15% (95% CI: 10–19%) at SC1 and 14% (95% CI: 9–19%) at SC2. Multivariate analysis showed no significant differences in local recurrence between the centers. We concluded that when entering all available patients into the analysis using an intention-to-treat principle, a more selective approach to postoperative RT in patients with grade 2–3 deep-seated STS did not lead to a higher local recurrence rate. However, with this study design, we cannot rule out if the local recurrence rate could have been lower if RT was administered to all tumors removed with a margin wider than 1 cm and/or a solid barrier.

Background and purpose: Soft tissue sarcomas are a heterogeneous group of malignant tumors with a high risk of metastasis, primarily to the lungs, making accurate survival prediction an essential part of long-term planning. No machine learning (ML) survival prediction models have been developed using a modern, population-based dataset from Scandinavia. We aimed to develop and compare ML models with logistic regression in predicting 5-year survival in soft tissue sarcoma patients and identify key predictive variables.Methods: This retrospective cohort study included patients diagnosed with deep-seated, high-grade soft tissue sarcomas of the extremities and trunk wall in Denmark from 2000 to 2016. Logistic regression was compared with 4 developed ML models, including random forest. Performance was assessed using the area under the curve (AUC), sensitivity, specificity, and calibration metrics, with a 70:30 training–test split and 5-fold cross-validation to evaluate the models.Results: 516 patients were included, of whom 226 (44%) died within 5 years following surgery. Random forest demonstrated the best ML performance on the training set and was compared with logistic regression on the test set. Logistic regression achieved an AUC of 0.74 (95% confidence interval [CI] 0.66–0.82), outperforming random forest‘s AUC of 0.65 (CI 0.56–0.74). Logistic regression also had higher sensitivity (0.65 vs 0.59) and specificity (0.72 vs 0.69), while random forest had a lower Brier score (0.38 vs 0.41).Conclusion: Although the developed random forest ML model performed well during training, logistic regression outperformed it after internal validation. Soft tissue sarcomas located in the trunk, grade 3 tumors, and chemotherapy within 3 months of surgery demonstrated the highest negative effect on survival, consistent with current treatment protocols in which patients with high-risk disease are managed with more aggressive multimodal therapy. Further external validation and assessment of clinical utility are required before potential clinical implementation.