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OS07.7 Patterns of diagnostic marker assessment in adult diffuse glioma - a survey of the European Confederation of Neuropathological Societies

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Introduction: The 2016 update of the WHO classification has introduced an integrated diagnostic approach that incorporates both tumor morphology and molecular information. This conceptual change has far reaching implications especially for neuropathologists who are in the forefront of translating molecular markers to routine diagnostic use. Adult diffuse glioma is a prototypic example for a group of tumors that underwent substantial regrouping, and it represents a major workload for surgical neuropathologists. METHODS: We conducted a survey among members of the European Confederation of Neuropathological Societies (Euro-CNS) in order to assess 1) the extent to which molecular markers have already been incorporated in glioma diagnoses, 2) which molecular techniques are in daily use, and 3) to set a baseline for future surveys in this field. Results: Based on 130 responses from participants across 40 nations neuropathologists uniformly rate molecular marker testing as highly relevant and already incorporate molecular information in their diagnostic assessments. At the same time however, the survey documents substantial differences in access to crucial biomarkers and molecular techniques across geographic regions and within individual countries. Concerns are raised concerning the validity of test assays with MGMT, 1p19q, and ATRX being perceived as most problematic. Conclusions: Together neuropathologists advocate the need for international harmonization of standards and consensus guidelines, and the majority is willing to actively engage in quality control.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
OS07.7 Patterns of diagnostic marker assessment in adult diffuse glioma - a survey of the European Confederation of Neuropathological Societies
Date Crossref
01/04/2017
Éditeur
Oxford University Press (OUP)
Type
journal-article

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Sujets associés

Radiomics and Machine Learning in Medical ImagingGlioma Diagnosis and Treatment

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