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Updated: Jun 26, 2026
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Predicting clinical progression in patients with relapsing remitting multiple sclerosis retrospectively using a
Lis J M van den Boogaard1, Simone Monachino2, Gerhard S Drenthen3
1Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands; Mental Health and Neuroscience Research Institute, Maastricht University, Maastricht, the Netherlands; Academic MS Center Zuyd, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, the Netherlands.
Background:
Progression independent of relapse- and magnetic resonance imaging (MRI)-activity (PIRMA) in relapsing-remitting multiple sclerosis (RRMS) may result from subtle myelin pathology in normal-appearing white matter (NAWM) and perilesions.
Objective:
To evaluate whether short-term myelin changes, estimated with the MRI-based T1w/FLAIR ratio, are associatied with long-term clinical progression in patients with RRMS receiving natalizumab.
Methods:
For 29 patients with RRMS, short-term, six-month myelin changes were calculated for three areas, i.e. white matter hyperintensities (WMH), a perilesional area of 2 mm, and NAWM. Expanded disability status scale (EDSS) scores at baseline and after at least three years were used to define long-term clinical progression.
Results:
Logistic regression models demonstrated significant associations between long-term progression using short-term changes in myelin proxy in NAWM (β = -77.962; p = .039), but not in perilesional tissue (β = -3.999; p = .717) and WMH (β = -4.324; p = .752). ROC-curve of the logistic regression model of NAWM showed a good discriminative value (area under the curve (AUC) = 0.892, 95% CI [.755-1.000]) for clinical progression.
Conclusion:
By assessing short-term myelin changes outside lesions, using readily available clinical MRI scans, long-term clinical progression in patients with RRMS may be predicted.
