Background: Growing evidence supports the efficacy of restorative cognitive training in people with multiple sclerosis (PwMS), but the effects vary across individuals. Differences in treatment efficacy may be related to baseline individual differences. We investigated clinical characteristics and MRI variables to predict response to a previously validated approach to home-based restorative cognitive training.
Methods: In a single-arm repeated measures study, 51 PwMS completed a 12-week at-home restorative cognitive training program called BrainHQ, shown to be effective in a placebo-controlled clinical trial. Baseline demographic, clinical, neuropsychological, and brain MRI factors were captured and the effects of treatment were quantified with Symbol Digit Modalities Test (SDMT). Also measured were indices of treatment compliance. Regression modeling was employed to identify the factors associated with greatest SDMT improvement.
Results: As a group, patients improved significantly after training: mean SDMT improving from 49.6 ± 14.7 to 52.6 ± 15.6 (t = 3.91, p<0.001). Greater SDMT improvement correlated positively with treatment exposure (r = 0.38, p = 0.007). Increased post-rehabilitation improvement on SDMT was predicted by baseline relapsing-remitting course (β=-0.34, p = 0.017), higher trait Conscientiousness-Orderliness (β=0.29, p = 0.040), and higher baseline gray matter volume (GMV; β=0.31, p = 0.030).
Conclusion: The study was designed to explore the variables that predict favorable outcome in a home-based application of a validated restorative cognitive training program. We find good outcomes are most likely in patients with higher trait Conscientiousness-Orderliness, and relapsing-remitting course. The same was found for individuals with higher GMV. Future work in larger cohorts is needed to support these findings and to investigate the unique needs of individuals according to baseline factors.
Keywords: Cognition; Multiple sclerosis; Neurological rehabilitation; Quality of life; Telemedicine; Therapeutics.
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