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Mult Scler. 2011 Jun;17(6):695-701. doi: 10.1177/1352458510394454. Epub 2011 Jan 12.

Predicting the severity of relapsing-remitting MS: the contribution of cross-sectional and short-term follow-up MRI data.

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1
Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, Graz, Austria.

Abstract

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.

PMID:
21228028
DOI:
10.1177/1352458510394454
[Indexed for MEDLINE]
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