Clinical features, MRI markers predict cognition deterioration over 10 years in MS

Base age, disability, whole brain volume (WBV), and T2 lesion volume were significant predictors of long-term deterioration in information processing speed (IPS) in patients with multiple sclerosis (MS), translational and clinical.

This study included 76 Norwegian patients who were diagnosed with MS from 1998 to 2000. All participants underwent a neurological examination, 1.5T magnetic resonance imaging (MRI) of the brain, and clinical assessments at baseline. These evaluations were carried out again after 5 and 10 years. The study researchers rated the physical disability at each visit using the Extended Disability Status Scale (EDSS). In addition, they calculated global and tissue-specific volumes with each visit. Changes in the IPS were measured using the Symbol Digit Modalities Test (SDMT).

Approximately 49% (n = 37) of the patients were classified as cognitively impaired at the start of the study. Among the participants available for assessment, rates of cognitive impairment fluctuated at 47% and 37%, respectively, at 5 and 10 years.

At the 5-year follow-up, factors predicting SDMT worsening in the multivariable analysis include baseline age (β, -1.8; -4.5-0.9; P = 0.20), EDSS ( β, -1.8; 95% CI, -3.9) -0.3; P = 0.084), SDMT (β, -0.20; 95% CI, -0.40 to -0.01; P = 0.043), WBV (β, 0.042; 95% CI, 0.009-0.076; P = 0.015 ) and T2 lesion volume (β, -0.35; 95% CI, -0.55 to -0.16; P = 0.001). The study researchers found that these predictive variables accounted for 30.2% of the variance in SDMT.

Base predictors for the change in SDMT during the 10 years examined were age (β, -3.0; 95% CI, -6.4-0.4; P = 0.083), EDSS (β, 1.7; 95% CI , -0.7-4.0; P. = 0.16), gray matter volume (β, 0.08; 95% CI, 0.02-0.13; P = 0.007), and T1 lesion volume ( β, -1.1; 95% CI, -1.5 to -0.7; P <). 001), which explained 39.4% of the variance in change in SDMT.

The limitations of this study included the relatively small size of the cohort and the high drop-out rate over a period of 10 years.

Using these identified predictors, the researchers concluded that “identifying patients at greater risk for developing cognitive difficulties could help clinicians initiate appropriate follow-up care” and aid treatment decisions.

Disclosure: This clinical study was supported by Novartis. Several authors on the study stated links to the pharmaceutical industry. For a full list of the authors’ information, see the original reference.


Jacobsen C., Zivadinov R., Myhr KM, et al. Brain atrophy and clinical features predicting SDMT performance in multiple sclerosis: a 10-year follow-up study. Mult Scler J Exp Transl Clin. Published online February 8, 2021. doi: 10.1177 / 2055217321992394

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