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Predicting clinical progression in multiple sclerosis after 6 and 12 years.

I Dekker1,2, A J C Eijlers3, V Popescu1

  • 1Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

European Journal of Neurology
|January 11, 2019
PubMed
Summary

Early clinical and imaging markers can predict long-term disability and cognitive decline in multiple sclerosis (MS). Progressive disease onset and early neurodegeneration indicate higher risk for disability and cognitive dysfunction in MS patients.

Keywords:
atrophycognitiondisabilitymultiple sclerosisprediction

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Area of Science:

  • Neurology
  • Neuroimaging
  • Clinical Prediction

Background:

  • Multiple sclerosis (MS) is a chronic neurological disease characterized by progressive disability and cognitive impairment.
  • Predicting the long-term course of MS is crucial for patient management and therapeutic development.

Purpose of the Study:

  • To identify early clinical and imaging predictors of disability and cognitive function in multiple sclerosis (MS) patients.
  • To assess the predictive value of baseline and 2-year measures for outcomes at 6 and 12 years.

Main Methods:

  • A cohort of 115 MS patients was followed for up to 12 years.
  • Disability was assessed using the Expanded Disability Status Scale (EDSS); cognition was evaluated via neuropsychological testing.
  • Predictors included EDSS scores, brain/lesion volumes, and demographic factors.

Main Results:

  • Early EDSS scores and whole-brain volume changes predicted 6-year disability (R²=0.56).
  • Primary progressive MS, lower education, male sex, and early brain atrophy predicted 6-year cognition (R²=0.26).
  • Higher T1-hypointense lesion volumes predicted 12-year disability and cognition.

Conclusions:

  • Early neurodegeneration and progressive onset are associated with increased disability and cognitive decline in MS.
  • Male sex and lower education specifically impact cognitive dysfunction, suggesting a need for advanced imaging in prediction.
  • Early identification of at-risk patients can guide personalized MS management strategies.