Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study

Cecilie Jacobsen, Robert Zivadinov, Kjell Morten Myhr, Turi O. Dalaker, Ingvild Dalen, Ralph H.B. Benedict, Niels Bergsland, Elisabeth Farbu

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: To identify Magnetic Resonance Imaging (MRI), clinical and demographic biomarkers predictive of worsening information processing speed (IPS) as measured by Symbol Digit Modalities Test (SDMT). Methods: Demographic, clinical data and 1.5 T MRI scans were collected in 76 patients at time of inclusion, and after 5 and 10 years. Global and tissue-specific volumes were calculated at each time point. For the primary outcome of analysis, SDMT was used. Results: Worsening SDMT at 5-year follow-up was predicted by baseline age, Expanded Disability Status Scale (EDSS), SDMT, whole brain volume (WBV) and T2 lesion volume (LV), explaining 30.2% of the variance of SDMT. At 10-year follow-up, age, EDSS, grey matter volume (GMV) and T1 LV explained 39.4% of the variance of SDMT change. Conclusion: This longitudinal study shows that baseline MRI-markers, demographic and clinical data can help predict worsening IPS. Identification of patients at risk of IPS decline is of importance as follow-up, treatment and rehabilitation can be optimized.

Original languageEnglish
JournalMultiple sclerosis journal - experimental, translational and clinical
Volume7
Issue number1
DOIs
Publication statusPublished - 2021

Keywords

  • Atrophy
  • biomarkers
  • cognition
  • longitudinal
  • MRI
  • multiple sclerosis

ASJC Scopus subject areas

  • Clinical Neurology
  • Cellular and Molecular Neuroscience

Fingerprint Dive into the research topics of 'Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study'. Together they form a unique fingerprint.

Cite this