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Conversion of clinically isolated syndrome to multiple sclerosis: a prospective study
Jan Kolčava1, Jan Kočica1, Monika Hulová1
1Faculty of Medicine, Masaryk University, Brno, Czech Republic; Department of Neurology, University Hospital Brno, Czech Republic.
Multiple Sclerosis and Related Disorders
|June 23, 2020
Summary
Subclinical evoked potential abnormalities, along with MRI T2 lesions and OCB positivity, are strong predictors for clinically isolated syndrome (CIS) conversion to multiple sclerosis (MS). Early identification aids in timely treatment decisions for MS.
Area of Science:
- Neurology
- Neuroimmunology
- Clinical Neuroscience
Background:
- Multiple sclerosis (MS) often initiates with a clinically isolated syndrome (CIS), a single neurological attack.
- Predicting conversion from CIS to MS is crucial for timely therapeutic intervention.
- Existing studies show variable conversion rates, highlighting the need for precise predictive factors.
Purpose of the Study:
- To identify independent predictors for the conversion of CIS to MS.
- To evaluate demographic, clinical, MRI, CSF, and electrophysiological parameters.
- To utilize the 2010 McDonald MS diagnostic criteria for assessing conversion.
Main Methods:
- Prospective longitudinal study of 64 CIS patients over at least 24 months.
- Assessment of conversion to MS based on clinical relapse or new MRI lesions.
- Analysis of baseline MRI T2 lesions, oligoclonal bands (OCB), and multimodal evoked potentials (EP).
Main Results:
- 70.3% of CIS patients converted to MS within the follow-up period.
- Predictors for conversion included: >10 baseline MRI T2 lesions (OR 3.107), OCB positivity (OR 5.958), and subclinical EP abnormality (OR 14.400).
- Multivariate models confirmed these as independent predictors with 84% sensitivity and 63% specificity.
Conclusions:
- Baseline MRI T2 lesion load and OCB positivity are established predictors for CIS to MS conversion.
- Subclinical abnormalities in multimodal evoked potentials (EP) demonstrate significant predictive value.
- These findings enhance the ability to identify patients at high risk of MS progression.

