Risk-Prediction Models for Clinical Decision-Making in Sarcoma Care: An International Survey Among Soft-Tissue Sarcoma Clinicians.

IF 3.4 2区 医学 Q2 ONCOLOGY
Annals of Surgical Oncology Pub Date : 2025-04-01 Epub Date: 2025-02-01 DOI:10.1245/s10434-024-16849-7
Anouk A Kruiswijk, Lisa A E Vlug, Ibtissam Acem, Ellen G Engelhardt, Alessandro Gronchi, Dario Callegaro, Rick L Haas, Robert J P van de Wal, Michiel A J van de Sande, Leti van Bodegom-Vos
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Abstract

Introduction: Risk 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 methods: A 29-item survey was disseminated online to members of international sarcoma societies.

Results: This 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.

Conclusions: Responding 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.

用于肉瘤治疗临床决策的风险预测模型:一项针对软组织肉瘤临床医生的国际调查。
风险预测模型(rpm)是基于临床特征预测结果的统计工具,因此可以支持(共享)决策。随着向个性化医疗的转变,rpm的数量呈指数增长,包括在多模式肉瘤治疗中。然而,它们与常规软组织肉瘤(STS)治疗的结合在很大程度上仍然未知。因此,我们盘点了肿瘤委员会讨论和患者咨询期间RPM在肉瘤治疗中的使用情况,以及STS临床医生对使用RPM支持(共享)决策的态度。材料和方法:一项29项的调查在网上分发给国际肉瘤学会的成员。结果:本研究纳入278名受访者。分别有68%和65%的临床医生报告在肿瘤委员会讨论和/或患者咨询期间使用rpm。在肿瘤委员会的讨论中,rpm主要用于评估(新)辅助化疗的潜在益处。在患者会诊期间,rpm被用于根据要求预测患者预后,并协助制定有关(新)辅助治疗的决策。rpm预测患者风险的可靠性和缺乏关于rpm使用的指南被认为是障碍。此外,一些临床医生质疑rpm估计对个体患者的适用性,并表达了在讨论预后结果时引起不必要焦虑的担忧。结论:有反应的STS临床医生经常使用rpm来支持(新)辅助治疗的决策。然而,他们对RPM估计对个体患者的适用性表示担忧,并报告了与患者沟通预后结果的挑战。这些发现突出了临床医生在将rpm纳入患者咨询时所面临的困难。
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来源期刊
CiteScore
5.90
自引率
10.80%
发文量
1698
审稿时长
2.8 months
期刊介绍: The Annals of Surgical Oncology is the official journal of The Society of Surgical Oncology and is published for the Society by Springer. The Annals publishes original and educational manuscripts about oncology for surgeons from all specialities in academic and community settings.
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