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Predicting the severity of relapsing-remitting MS: The contribution of cross-sectional and short-term follow-up MRI data.
MedLine Citation:
PMID:  21228028     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Background and objective: Predicting the long-term clinical course of multiple sclerosis (MS) is difficult on clinical grounds. Recent studies have suggested magnetic resonance imaging (MRI) metrics to be helpful. We wanted to confirm this. Methods: Contactable individuals (N = 84) from an initial 99 patients with relapsing-remitting MS (RRMS) who had undergone careful baseline and 2-year follow-up examinations including MRI were reassessed after a mean of 10.8 ± 2.7 years. We investigated using multivariate linear regression analyses if clinical and MRI data obtained at the prior time-points and the rates of change in morphologic variables over a mean observational period of 2.5 years could have served to predict a patient's MS severity score (MSSS) 11 years later. Conversion to secondary progressive MS (SPMS) was a further outcome variable. Results: In univariate analyses, the 'black hole ratio' (BHR) at baseline (p = 0.017, beta = 0.148) and at first follow-up (p = 0.007, beta = -0.154) was the only MRI parameter showing a significant correlation with the MSSS. In a multiple regression model, the independent predictive value of imaging variables became statistically non-significant and the latest MSSS was predicted primarily by the baseline EDSS (r (2 )= 0.28; p < 0.001). The BHR at baseline explained 9.4% of variance of conversion to SPMS (p = 0.033). Over the observational period the MSSS remained stable in patients remaining RRMS, but increased in converters to SPMS from 4.0 to 6.4. Conclusions: We failed to confirm a clear independent contribution of cross-sectional and short-term follow-up MRI data for the prediction of the long-term clinical course of MS. The MSSS is not a stable indicator of disease severity but may increase in converters to SPMS.
Authors:
C Enzinger; S Fuchs; A Pichler; M Wallner-Blazek; M Khalil; C Langkammer; S Ropele; F Fazekas
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-1-12
Journal Detail:
Title:  Multiple sclerosis (Houndmills, Basingstoke, England)     Volume:  -     ISSN:  1477-0970     ISO Abbreviation:  -     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2011-1-13     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9509185     Medline TA:  Mult Scler     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Neurology, Medical University of Graz/ Division of Neuroradiology, Department of Radiology, Medical University of Graz, Graz, Austria.
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