Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study. Issue 1 (February 2021)

• Record Type: Journal Article
• Authors: Jacobsen, Cecilie; Zivadinov, Robert; Myhr, Kjell-Morten; Dalaker, Turi O; Dalen, Ingvild; Benedict, Ralph HB; Bergsland, Niels; Farbu, Elisabeth
• Is Part Of: Multiple sclerosis journal, experimental, translational and clinical. Volume 7:Issue 1(2021)
• Publication Date: 2021-02
• Subjects: Atrophy -- biomarkers -- cognition -- longitudinal -- MRI -- multiple sclerosis; Multiple sclerosis -- Periodicals; 616.834
• DOI: 10.1177/2055217321992394
• Languages: English
• ISSNs: 2055-2173

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.