Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany; German Center for Neurodegenerative Diseases, Site Munich, Germany.
Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany.
EBioMedicine. 2023 Mar;89:104456. doi: 10.1016/j.ebiom.2023.104456. Epub 2023 Feb 4.
A major evolution from purely clinical diagnoses to biomarker supported clinical diagnosing has been occurring over the past years in neurology. High-throughput methods, such as next-generation sequencing and mass spectrometry-based proteomics along with improved neuroimaging methods, are accelerating this development. This calls for a consensus framework that is broadly applicable and provides a spot-on overview of the clinical validity of novel biomarkers. We propose a harmonized terminology and a uniform concept that stratifies biomarkers according to clinical context of use and evidence levels, adapted from existing frameworks in oncology with a strong focus on (epi)genetic markers and treatment context. We demonstrate that this framework allows for a consistent assessment of clinical validity across disease entities and that sufficient evidence for many clinical applications of protein biomarkers is lacking. Our framework may help to identify promising biomarker candidates and classify their applications by clinical context, aiming for routine clinical use of (protein) biomarkers in neurology.
在过去几年中,神经病学领域已经从纯粹的临床诊断向基于生物标志物的临床诊断发生了重大演变。高通量方法,如下一代测序和基于质谱的蛋白质组学以及改进的神经影像学方法,正在加速这一发展。这需要一个广泛适用的共识框架,为新型生物标志物的临床有效性提供准确的概述。我们提出了一个协调的术语和一个统一的概念,根据临床使用情况和证据水平对生物标志物进行分层,该概念改编自肿瘤学中现有的框架,并特别关注(表观)遗传学标志物和治疗背景。我们证明,该框架允许在疾病实体之间对临床有效性进行一致评估,并且缺乏许多蛋白质生物标志物临床应用的充分证据。我们的框架可以帮助识别有前途的生物标志物候选者,并根据临床背景对其应用进行分类,旨在使(蛋白质)生物标志物在神经病学中常规临床应用。