Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/103184
Title: | A unified classification approach rating clinical utility of protein biomarkers across neurologic diseases |
Author(s): | Bernhardt, Alexander Tiedt, Steffen Teupser, Daniel Dichgans, Martin Meyer, Bernhard Gempt, Jens Kuhn, Peer-Hendrik Simons, Mikael Palleis, Carla Teresa Weidinger, Endy Nübling, Georg Holdt, Lesca Miriam Hönikl, Lisa Gasperi, Christiane Giesbertz, Pieter Müller, Stephan Andreas Breimann, Stephan Lichtenthaler, Stefan Kuster, Bernhard Mann, Matthias Imhof, Axel Barth, Teresa Hauck, Stefanie M. Zetterberg, Henrik Otto, Markus Weichert, Wilko Hemmer, Bernhard Levin, Johannes Martin |
Issue Date: | 2023 |
Type: | Article |
Language: | English |
Abstract: | 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. |
URI: | https://opendata.uni-halle.de//handle/1981185920/105136 http://dx.doi.org/10.25673/103184 |
Open Access: | Open access publication |
License: | (CC BY 4.0) Creative Commons Attribution 4.0 |
Journal Title: | EBioMedicine |
Publisher: | Elsevier |
Publisher Place: | Amsterdam [u.a.] |
Volume: | 89 |
Original Publication: | 10.1016/j.ebiom.2023.104456 |
Appears in Collections: | Open Access Publikationen der MLU |
Files in This Item:
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1-s2.0-S235239642300021X-main.pdf | 1.36 MB | Adobe PDF | View/Open |