Related Experiment Video
Updated: May 10, 2026
The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Electrophysiological markers and predictors of the disease course in primary progressive multiple sclerosis
Regina Schlaeger1, Marcus D'Souza, Christian Schindler
1Department of Neurology, University Hospital Basel, Switzerland.
Background:
Currently no valid surrogate marker exists for primary progressive multiple sclerosis (PPMS).
Objective:
Our aim was to prospectively investigate multimodal evoked potentials (EPs) as markers and predictors of the disease course in PPMS.
Methods:
Twenty-two PPMS patients were prospectively examined with visual, somatosensory and motor EPs and Expanded Disability Status Scale (EDSS) assessments at baseline (T0) and at six-month intervals over three years. Spearman rank correlation was used to determine the relationship between EP measures and EDSS. The relationship between disease evolution and a numerical score derived from z-transformed EP-latencies (s-EP-Q) and baseline characteristics was further assessed using multivariable linear regression analysis.
Results:
s-EP-Q correlated with EDSS score at all points in time in cross-sectional comparison (0.53≤rs ≤0.68; 0.0007≤p≤0.0232) and also longitudinally by trend (rs=0.46, p=0.0740). The s-EP-QT0 correlated with the EDSS score at year 3 (T6) (r s=0.77, p<0.0001). The s-EP-Q changes became statistically significant six months before corresponding changes were seen in the EDSS score. EDSST6 as predicted by EDSST6 = -1.027+0.037* age+0.217* s-EP-QT0 + 0.695* EDSST0 correlated with the observed values (rs=0.92, p<0.0001).
Conclusions:
Multimodal EPs correlate well with disability in PPMS, and allow some prediction of the disease course over three years. These findings support a role of EPs as surrogate markers in clinical trials in PPMS.
