The Influence of Personalised Sarcoma Care (PERSARC) Prediction Modelling on Clinical Decision Making in a Multidisciplinary Setting.

Q2 Medicine Sarcoma Pub Date : 2021-10-21 eCollection Date: 2021-01-01 DOI:10.1155/2021/8851354

H S Femke Hagenmaier, Annelies G K van Beeck, Rick L Haas, Veroniek M van Praag, Leti van Bodegom-Vos, Jos A van der Hage, Stijn Krol, Frank M Speetjens, Arjen H G Cleven, Ana Navas, Herman M Kroon, Rieneke G Moeri-Schimmel, Nicolette A C Leyerzapf, Michiel A J van de Sande

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引用次数: 4

Abstract

Background: With soft-tissue sarcoma of the extremity (ESTS) representing a heterogenous group of tumors, management decisions are often made in multidisciplinary team (MDT) meetings. To optimize outcome, nomograms are more commonly used to guide individualized treatment decision making.

Purpose: To evaluate the influence of Personalised Sarcoma Care (PERSARC) on treatment decisions for patients with high-grade ESTS and the ability of the MDT to accurately predict overall survival (OS) and local recurrence (LR) rates.

Methods: Two consecutive meetings were organised. During the first meeting, 36 cases were presented to the MDT. OS and LR rates without the use of PERSARC were estimated by consensus and preferred treatment was recorded for each case. During the second meeting, OS/LR rates calculated with PERSARC were presented to the MDT. Differences between estimated OS/LR rates and PERSARC OS/LR rates were calculated. Variations in preferred treatment protocols were noted.

Results: The MDT underestimated OS when compared to PERSARC in 48.4% of cases. LR rates were overestimated in 41.9% of cases. With the use of PERSARC, the proposed treatment changed for 24 cases.

Conclusion: PERSARC aids the MDT to optimize individualized predicted OS and LR rates, hereby guiding patient-centered care and shared decision making.

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个性化肉瘤护理(PERSARC)预测模型对多学科环境下临床决策的影响

背景:由于四肢软组织肉瘤(ESTS)是一组异质性肿瘤，治疗决策通常在多学科团队(MDT)会议上做出。为了优化结果，nomographic更常用来指导个体化治疗决策。目的:评估个性化肉瘤护理(PERSARC)对高级别est患者治疗决策的影响，以及MDT准确预测总生存期(OS)和局部复发率(LR)的能力。方法:连续组织两次会议。在第一次会议期间，向MDT提交了36个病例。在不使用PERSARC的情况下，通过共识估计OS和LR率，并记录每个病例的首选治疗方法。在第二次会议期间，将使用PERSARC计算的OS/LR率提交给MDT。计算了估计OS/LR率与PERSARC OS/LR率之间的差异。注意到首选治疗方案的变化。结果:与PERSARC相比，MDT低估了48.4%的OS。41.9%的病例LR率被高估。随着PERSARC的使用，24例患者的治疗方案发生了变化。结论:PERSARC有助于MDT优化个性化的OS和LR预测率，从而指导以患者为中心的护理和共同决策。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Sarcoma Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

5.00

自引率

0.00%

发文量

审稿时长

14 weeks

期刊介绍： Sarcoma is dedicated to publishing papers covering all aspects of connective tissue oncology research. It brings together work from scientists and clinicians carrying out a broad range of research in this field, including the basic sciences, molecular biology and pathology and the clinical sciences of epidemiology, surgery, radiotherapy and chemotherapy. High-quality papers concerning the entire range of bone and soft tissue sarcomas in both adults and children, including Kaposi"s sarcoma, are published as well as preclinical and animal studies. This journal provides a central forum for the description of advances in diagnosis, assessment and treatment of this rarely seen, but often mismanaged, group of patients.