Konduri Praneeta R, Marquering Henk A, van Bavel Ed E, Hoekstra Alfons, Majoie Charles B L M
Biomedical Engineering and Physics, Amsterdam University Medical Centers, Amsterdam, Netherlands.
Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands.
Front Neurol. 2020 Sep 16;11:558125. doi: 10.3389/fneur.2020.558125. eCollection 2020.
Despite improved treatment, a large portion of patients with acute ischemic stroke due to a large vessel occlusion have poor functional outcome. Further research exploring novel treatments and better patient selection has therefore been initiated. The feasibility of new treatments and optimized patient selection are commonly tested in extensive and expensive randomized clinical trials. trials, computer-based simulation of randomized clinical trials, have been proposed to aid clinical trials. In this white paper, we present our vision and approach to set up trials focusing on treatment and selection of patients with an acute ischemic stroke. The INSIST project ( trials for treatment of acute Ischemic STroke, www.insist-h2020.eu) is a collaboration of multiple experts in computational science, cardiovascular biology, biophysics, biomedical engineering, epidemiology, radiology, and neurology. INSIST will generate virtual populations of acute ischemic stroke patients based on anonymized data from the recent stroke trials and registry, and build on the existing and emerging models for acute ischemic stroke, its treatment (thrombolysis and thrombectomy) and the resulting perfusion changes. These models will be used to design a platform for trials that will be validated with existing data and be used to provide a proof of concept of the potential efficacy of this emerging technology. The platform will be used for preliminary evaluation of the potential suitability and safety of medication, new thrombectomy device configurations and methods to select patient subpopulations for better treatment outcome. This could allow generating, exploring and refining relavant hypotheses on potential causal pathways (which may follow from the evidence obtained from clinical trials) and improving clinical trial design. Importantly, the findings of the trials will require validation under the controlled settings of randomized clinical trials.
尽管治疗方法有所改进,但很大一部分因大血管闭塞导致急性缺血性中风的患者功能预后仍较差。因此,已启动了进一步探索新治疗方法和优化患者选择的研究。新治疗方法的可行性和优化的患者选择通常在广泛且昂贵的随机临床试验中进行测试。有人提出基于计算机的随机临床试验模拟来辅助临床试验。在本白皮书中,我们阐述了开展聚焦于急性缺血性中风患者治疗与选择的虚拟临床试验的愿景和方法。INSIST项目(急性缺血性中风治疗虚拟临床试验,www.insist-h2020.eu)是计算科学、心血管生物学、生物物理学、生物医学工程、流行病学、放射学和神经学等多个领域专家的合作项目。INSIST将基于近期中风试验和登记处的匿名数据生成急性缺血性中风患者的虚拟群体,并以现有的和新出现的急性缺血性中风、其治疗方法(溶栓和取栓)以及由此产生的灌注变化的模型为基础。这些模型将用于设计一个虚拟临床试验平台,该平台将用现有数据进行验证,并用于为这项新兴技术的潜在疗效提供概念验证。该平台将用于对药物、新的取栓装置配置以及选择患者亚群以获得更好治疗结果的方法的潜在适用性和安全性进行初步评估。这可以生成、探索和完善关于潜在因果途径的相关假设(这些假设可能来自临床试验获得的证据),并改进临床试验设计。重要的是,虚拟临床试验的结果需要在随机临床试验的受控环境下进行验证。