Medical University of Vienna, Department of Radiation Oncology, Vienna, Austria.
Medical University of Vienna, Department of Radiation Oncology, Vienna, Austria.
Radiother Oncol. 2023 Sep;186:109748. doi: 10.1016/j.radonc.2023.109748. Epub 2023 Jun 16.
To develop a novel decision-support system for radiation oncology that incorporates clinical, treatment and outcome data, as well as outcome models from a large clinical trial on magnetic resonance image-guided adaptive brachytherapy (MR-IGABT) for locally advanced cervical cancer (LACC).
A system, called EviGUIDE, was developed that combines dosimetric information from the treatment planning system, patient and treatment characteristics, and established tumor control probability (TCP), and normal tissue complication probability (NTCP) models, to predict clinical outcome of radiotherapy treatment of LACC. Six Cox Proportional Hazards models based on data from 1341 patients of the EMBRACE-I study have been integrated. One TCP model for local tumor control, and five NTCP models for OAR morbidities.
EviGUIDE incorporates TCP-NTCP graphs to help users visualize the clinical impact of different treatment plans and provides feedback on achievable doses based on a large reference population. It enables holistic assessment of the interplay between multiple clinical endpoints and tumour and treatment variables. Retrospective analysis of 45 patients treated with MR-IGABT showed that there exists a sub-cohort of patients (20%) with increased risk factors, that could greatly benefit from the quantitative and visual feedback.
A novel digital concept was developed that can enhance clinical decision- making and facilitate personalized treatment. It serves as a proof of concept for a new generation of decision support systems in radiation oncology, which incorporate outcome models and high-quality reference data, and aids the dissemination of evidence-based knowledge about optimal treatment and serve as a blueprint for other sites in radiation oncology.
开发一种新的放射肿瘤学决策支持系统，该系统结合了临床、治疗和结果数据，以及一项大型关于磁共振图像引导自适应近距离放射治疗（MR-IGABT）治疗局部晚期宫颈癌（LACC）的临床试验的结果模型。
开发了一种名为 EviGUIDE 的系统，该系统结合了治疗计划系统的剂量学信息、患者和治疗特征以及已建立的肿瘤控制概率（TCP）和正常组织并发症概率（NTCP）模型，以预测 LACC 放射治疗的临床结果。整合了来自 EMBRACE-I 研究的 1341 名患者的 6 个基于 Cox 比例风险模型的数据。一个用于局部肿瘤控制的 TCP 模型，以及五个用于 OAR 并发症的 NTCP 模型。
EviGUIDE 结合了 TCP-NTCP 图，以帮助用户可视化不同治疗计划的临床影响，并根据大量参考人群提供关于可实现剂量的反馈。它能够全面评估多个临床终点与肿瘤和治疗变量之间的相互作用。对 45 例接受 MR-IGABT 治疗的患者进行的回顾性分析表明，存在一个具有较高危险因素的亚组患者（20%），他们可以从定量和可视化反馈中获益匪浅。
开发了一种新的数字概念，可以增强临床决策，并促进个性化治疗。它为放射肿瘤学新一代决策支持系统提供了概念验证，该系统结合了结果模型和高质量的参考数据，并有助于传播关于最佳治疗的循证知识，并为放射肿瘤学的其他部位提供蓝图。
