Reports from Post-ECTRIMS – reflections on multiple sclerosis phenotypes

In current clinical practice, we use the classification of multiple sclerosis proposed by prof. Fred Lublin in 1996, which was subsequently revised in 2013. During the recent ECTRIMS conference (European Committee for Treatment and Research in Multiple Sclerosis), potential new phenotypes of this disease were discussed. New data suggest that multiple sclerosis is a condition with a broad spectrum of symptoms, and factors influencing its course can occur at any stage of the disease, with varying severity. Progression plays a key role in the course of the disease and may begin even before the diagnosis is made. New classifications might include clinical, radiological, neuropsychological factors, and biomarkers, enabling more accurate disease course predictions and optimal timing of treatment implementation.

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Publication Details

Journal
MS Report
Published
2024-09-30
DOI
https://doi.org/10.24292/01.ms.133300924.2
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00
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article

Reports from Post-ECTRIMS – reflections on multiple sclerosis phenotypes

Marek Hałas
MS Report
Gene expression and cancer classification
article

Reports from Post-ECTRIMS – reflections on multiple sclerosis phenotypes

Marek Hałas
article en

Abstract

In current clinical practice, we use the classification of multiple sclerosis proposed by prof. Fred Lublin in 1996, which was subsequently revised in 2013. During the recent ECTRIMS conference (European Committee for Treatment and Research in Multiple Sclerosis), potential new phenotypes of this disease were discussed. New data suggest that multiple sclerosis is a condition with a broad spectrum of symptoms, and factors influencing its course can occur at any stage of the disease, with varying severity. Progression plays a key role in the course of the disease and may begin even before the diagnosis is made. New classifications might include clinical, radiological, neuropsychological factors, and biomarkers, enabling more accurate disease course predictions and optimal timing of treatment implementation.

MS ReportVol. 13(3(48))
University Clinical Centre (PL)
Openalex Percentile: Top 78%
Gene expression and cancer classification
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