Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/103184
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DC Field | Value | Language |
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dc.contributor.author | Bernhardt, Alexander | - |
dc.contributor.author | Tiedt, Steffen | - |
dc.contributor.author | Teupser, Daniel | - |
dc.contributor.author | Dichgans, Martin | - |
dc.contributor.author | Meyer, Bernhard | - |
dc.contributor.author | Gempt, Jens | - |
dc.contributor.author | Kuhn, Peer-Hendrik | - |
dc.contributor.author | Simons, Mikael | - |
dc.contributor.author | Palleis, Carla Teresa | - |
dc.contributor.author | Weidinger, Endy | - |
dc.contributor.author | Nübling, Georg | - |
dc.contributor.author | Holdt, Lesca Miriam | - |
dc.contributor.author | Hönikl, Lisa | - |
dc.contributor.author | Gasperi, Christiane | - |
dc.contributor.author | Giesbertz, Pieter | - |
dc.contributor.author | Müller, Stephan Andreas | - |
dc.contributor.author | Breimann, Stephan | - |
dc.contributor.author | Lichtenthaler, Stefan | - |
dc.contributor.author | Kuster, Bernhard | - |
dc.contributor.author | Mann, Matthias | - |
dc.contributor.author | Imhof, Axel | - |
dc.contributor.author | Barth, Teresa | - |
dc.contributor.author | Hauck, Stefanie M. | - |
dc.contributor.author | Zetterberg, Henrik | - |
dc.contributor.author | Otto, Markus | - |
dc.contributor.author | Weichert, Wilko | - |
dc.contributor.author | Hemmer, Bernhard | - |
dc.contributor.author | Levin, Johannes Martin | - |
dc.date.accessioned | 2023-05-08T07:03:01Z | - |
dc.date.available | 2023-05-08T07:03:01Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | https://opendata.uni-halle.de//handle/1981185920/105136 | - |
dc.identifier.uri | http://dx.doi.org/10.25673/103184 | - |
dc.description.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. | eng |
dc.language.iso | eng | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject.ddc | 610 | - |
dc.title | A unified classification approach rating clinical utility of protein biomarkers across neurologic diseases | eng |
dc.type | Article | - |
local.versionType | publishedVersion | - |
local.bibliographicCitation.journaltitle | EBioMedicine | - |
local.bibliographicCitation.volume | 89 | - |
local.bibliographicCitation.publishername | Elsevier | - |
local.bibliographicCitation.publisherplace | Amsterdam [u.a.] | - |
local.bibliographicCitation.doi | 10.1016/j.ebiom.2023.104456 | - |
local.subject.keywords | Biomarker; Neurology; Proteomics; Protein; Clinical utility; Analytical validity | - |
local.openaccess | true | - |
dc.identifier.ppn | 184474843X | - |
local.bibliographicCitation.year | 2023 | - |
cbs.sru.importDate | 2023-05-08T07:02:36Z | - |
local.bibliographicCitation | Enthalten in EBioMedicine - Amsterdam [u.a.] : Elsevier, 2014 | - |
local.accessrights.dnb | free | - |
Appears in Collections: | Open Access Publikationen der MLU |
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1-s2.0-S235239642300021X-main.pdf | 1.36 MB | Adobe PDF | ![]() View/Open |