| Autor: |
Yonca Steubing, Nilofar Ahmadi, Flemming Puscz, Alexander Wolff, Jannik Hinzmann, Felix Reinkemeier, Sonja Verena Schmidt, Alexander Sogorski, Maxi Von Glinski, Mustafa Becerikli, Maria Füth, Jessica Zuchowski, Hannah Brüggenhorst, Tom Huyghebaert, Ingo Stricker, Marcus Lehnhardt, Christoph Wallner |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Life, Vol 14, Iss 5, p 569 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2075-1729 |
| DOI: |
10.3390/life14050569 |
| Popis: |
Background: Sarculator and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms are freely available risk prediction scores for surgically treated patients with primary sarcomas. Due to the rarity of angiosarcomas, these scores have only been tested on small cohorts of angiosarcoma patients. In neither the original patient cohort upon which the Sarculator is based nor in subsequent studies was a distinction made between primary and secondary angiosarcomas, as the app is intended to be applied to primary sarcomas. Therefore, the objective of our investigation was to assess whether the Sarculator reveals a difference in prognosis and whether such differentiation aligns with actual clinical data. Patients and Methods: Thirty-one patients with primary or secondary soft tissue angiosarcoma, treated at our Sarcoma Center from 2001 to 2023, were included in the study. Actual survival rates were compared with nomogram-derived data for predicted 5-year survival (Sarculator), as well as 4-, 8- and 12-year sarcoma-specific death probabilities (MSKCC). Harrell’s c-index was utilized to assess predictive validity. Results: In total, 31 patients were analyzed. The actual overall 5-year survival was 22.57% with a predicted 5-year survival rate of 25.97%, and the concordance index was 0.726 for the entire cohort. The concordance index results from MSKCC for angiosarcoma patients were below 0.7 indicating limited predictive accuracy in this cohort, particularly when compared to Sarculator. Summary: Nomogram-based predictive models are valuable tools in clinical practice for rapidly assessing prognosis. They can streamline the decision-making process for adjuvant treatments and improve patient counselling especially in the treatment of rare and complicated tumor entities such as angiosarcomas. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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