Document Detail

Relapsing multiple sclerosis patients treated with disease modifying therapy exhibit highly variable disease progression: A predictive model.
MedLine Citation:
PMID:  25459249     Owner:  NLM     Status:  In-Data-Review    
OBJECTIVE: To describe a "new natural history" of multiple sclerosis (MS), characterizing three patterns of progression in Relapsing MS (RMS) patients during the "treatment era," using newly developed definitions. By utilizing our simple model we intend to predict which patients are most likely to reach an EDSS of 6.0.
METHODS: We stratified MS progression into three distinct patterns: aggressive MS (AMS), intermediate MS (IMS) and mild MS (MMS), based on Expanded Disability Status Scale (EDSS) score rate of change. These groups were compared for progression of EDSS before and after reaching these definitions.
RESULTS: The three groups remained significantly different in terms of disability throughout their disease courses p≤0.001; 98% of the patients used disease modifying treatments (DMTs). AMS patients represent a significantly more disabling and aggressive form of MS than the IMS group.
CONCLUSIONS: Transition from relatively mild MS to aggressive course may begin at any time in the first 15 years, despite DMTs. Our definition for AMS is unique and identifies a group of patients who become permanently disabled within two years after a variable amount of time in a benign phase, despite treatment with modern DMTs.
Thomas F Scott; Christopher T Hackett; Matthew R Quigley; Carol J Schramke
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Publication Detail:
Type:  Journal Article     Date:  2014-10-02
Journal Detail:
Title:  Clinical neurology and neurosurgery     Volume:  127     ISSN:  1872-6968     ISO Abbreviation:  Clin Neurol Neurosurg     Publication Date:  2014 Dec 
Date Detail:
Created Date:  2014-12-03     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7502039     Medline TA:  Clin Neurol Neurosurg     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  86-92     Citation Subset:  IM    
Copyright Information:
Copyright © 2014 Elsevier B.V. All rights reserved.
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