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Prediction of long-term disability in multiple sclerosis

Schlaeger, R. and D'Souza, M. and Schindler, C. and Grize, L. and Dellas, S. and Radue, E. and Kappos, L. and Fuhr, P.. (2012) Prediction of long-term disability in multiple sclerosis. Multiple Sclerosis Journal, 18 (1). pp. 31-38.

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Official URL: http://edoc.unibas.ch/dok/A6094320

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Abstract

Background: Little is known about the predictive value of neurophysiological measures for the long-term course of multiple sclerosis (MS). Objective: To prospectively investigate whether combined visual (VEP) and motor evoked potentials (MEP) allow prediction of disability over 14 years. Methods: A total of 30 patients with relapsing-remitting and secondary progressive MS were prospectively investigated with VEPs, MEPs and the Expanded Disability Status Scale (EDSS) at entry (T0) and after 6, 12 and 24 months, and with cranial MRI scans at entry (T2-weighted and gadolinium-enhanced T1-weighted images). EDSS was again assessed at year 14 (T4). The association between evoked potential (EP), magnetic resonance (MR) data and EDSS was measured using Spearman's rank correlation. Multivariable linear regression was performed to predict EDSS(T4) as a function of z-transformed EP-latencies(T0). The model was validated using a jack-knife procedure and the potential for improving it by inclusion of additional baseline variables was examined. Results: EDSS values(T4) correlated with the sum of z-transformed EP-latencies(T0) (rho = 0.68, p > 0.0001), but not with MR-parameters(T0). EDSS(T4) as predicted by the formula EDSS(T4) = 4.194 + 0.088 * z-score P100(T0) + 0.071 * z-score CMCT(UE, T0) correlated with the observed values (rho = 0.69, p > 0.0001). Conclusion: Combined EPs allow prediction of long-term disability in small groups of patients with MS. This may have implications for the choice of monitoring methods in clinical trials and for daily practice decisions
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Biostatistics
UniBasel Contributors:Schindler, Christian and Grize, Leticia
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:SAGE
ISSN:1352-4585
e-ISSN:1477-0970
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:02 Nov 2017 13:28
Deposited On:16 Aug 2013 07:28

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