Format

Send to

Choose Destination
Neurology. 2009 Aug 18;73(7):498-503. doi: 10.1212/WNL.0b013e3181b351fd. Epub 2009 Jul 29.

Neuropsychological and MRI measures predict short-term evolution in benign multiple sclerosis.

Author information

1
Department of Neurology, University of Florence, Italy.

Abstract

OBJECTIVE:

To assess whether neuropsychological tests and MRI measures could be used as predictors of short-term disease evolution in a population of patients with benign multiple sclerosis (B-MS).

BACKGROUND:

The definition of B-MS is controversial. Recent data suggest that neuropsychological tests and MRI measures can provide valuable information for a more correct definition and interpretation of B-MS.

METHODS:

Sixty-three patients with B-MS (Expanded Disability Status Scale [EDSS] < or =3.0 and disease duration > or =15 years) underwent neuropsychological assessment using the Rao's Brief Repeatable Neuropsychological Battery and the Stroop Test. At that time, conventional brain MRI and magnetization transfer (MT) imaging was performed. White matter lesion load, global and regional brain volumes, and MT ratio in lesions and normal-appearing brain were measured. After a mean follow-up of 5 years, patients still having an EDSS score < or =3.5 were classified as still benign, whereas patients who had developed a secondary progressive course or who had an EDSS score > or =4.0 were defined as no longer benign (NLB).

RESULTS:

At end of follow-up, 29% of patients were classified as NLB. Male gender (hazard ratio [HR] = 2.9; 95% confidence interval [CI] 1.2-7.5; p = 0.02), number of neuropsychological tests failed (HR = 1.4; 95% CI 1.1-1.7; p = 0.003), and T1-weighted lesions (HR = 1.3; 95% CI 1.1-1.5; p = 0.002) were related to NLB status. In a model including these 3 variables, the NLB status was predicted with an accuracy of 82%.

CONCLUSIONS:

Cognitive assessment and MRI metrics can predict short-term disease evolution in benign multiple sclerosis (B-MS). This information can be useful to correctly identify patients with B-MS.

PMID:
19641173
DOI:
10.1212/WNL.0b013e3181b351fd
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center