ArticleAnnals of surgical oncology2025
Risk-Prediction Models for Clinical Decision-Making in Sarcoma Care: An International Survey Among Soft-Tissue Sarcoma Clinicians.
Article in Annals of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- ASO Author Reflections: Enhancing Shared Decision-Making with Risk Prediction Models in Sarcoma Care.Annals of surgical oncology · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
introductionRisk prediction models (RPMs) are statistical tools that predict outcomes on the basis of clinical characteristics and can thereby support (shared) decision-making. With the shift toward personalized medicine, the number of RPMs has increased exponentially, including in multimodal sarcoma care. However, their integration into routine soft-tissue sarcoma (STS) care remains largely unknown. Therefore, we inventoried RPM use in sarcoma care during tumor board discussions and patient consultations as well as the attitudes toward the use of RPMs to support (shared) decision-making among STS clinicians. MATERIALS AND
methodsA 29-item survey was disseminated online to members of international sarcoma societies.
resultsThis study enrolled 278 respondents. Respectively, 68% and 65% of the clinicians reported using RPMs during tumor board discussions and/or patient consultations. During tumor board discussions, RPMs were used primarily to assess the potential benefits of (neo)adjuvant chemotherapy. During patient consultations, RPMs were used to predict patient prognosis upon request and to assist in decision-making regarding (neo)adjuvant therapies. The reliability of patient risk predicted by RPMs and the absence of guidelines regarding the use of RPMs were identified as barriers. Additionally, some clinicians questioned the applicability of estimates from RPMs to individual patients and expressed concerns about causing unnecessary anxiety when discussing prognostic outcomes.
conclusionsResponding STS clinicians frequently use RPMs to support decision-making about (neo)adjuvant therapies. However, they expressed concerns about the applicability of RPM estimates to individual patients and reported challenges in communicating prognostic outcomes with patients. These findings highlight the difficulties clinicians face when integrating RPMs into patient consultations.
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