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Updated: May 2, 2026
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Validating predictors of disease progression in a large cohort of primary-progressive multiple sclerosis based on a
Jan-Patrick Stellmann1, Anneke Neuhaus2, Christian Lederer3
1Institute for Neuroimmunology and Clinical MS Research (inims), University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Background:
New agents with neuroprotective or neuroregenerative potential might be explored in primary-progressive Multiple Sclerosis (PPMS)--the MS disease course with leading neurodegenerative pathology. Identification of patients with a high short-term risk for progression may minimize study duration and sample size. Cohort studies reported several variables as predictors of EDSS disability progression but findings were partially contradictory.
Objective:
To analyse the impact of published predictors on EDSS disease progression in a large cohort of PPMS patients.
Methods:
A systematic literature research was performed to identify predictors for disease progression in PPMS. Individual case data from the Sylvia Lawry Centre (SLC) and the Hamburg MS patient database (HAPIMS) was pooled for a retrospective validation of these predictors on the annualized EDSS change.
Results:
The systematic literature analysis revealed heterogeneous data from 3 prospective and 5 retrospective natural history cohort studies. Age at onset, gender, type of first symptoms and early EDSS changes were available for validation. Our pooled cohort of 597 PPMS patients (54% female) had a mean follow-up of 4.4 years and mean change of EDSS of 0.35 per year based on 2503 EDSS assessments. There was no significant association between the investigated variables and the EDSS-change.
Conclusion:
None of the analysed variables were predictive for the disease progression measured by the annualized EDSS change. Whether PPMS is still unpredictable or our results may be due to limitations of cohort assessments or selection of predictors cannot be answered. Large systematic prospective studies with new endpoints are needed.
