Response heterogeneity to home-based restorative cognitive rehabilitation in multiple sclerosis: An exploratory study

Tom A Fuchs; Stefano Ziccardi; Michael G Dwyer; Leigh E Charvet; Alexander Bartnik; Rebecca Campbell; Jose Escobar; David Hojnacki; Chana Kolb; Devon Oship; Jeta Pol; Michael T Shaw; Curtis Wojcik; Faizan Yasin; Bianca Weinstock-Guttman; Robert Zivadinov; Ralph H B Benedict

doi:10.1016/j.msard.2019.06.026

Response heterogeneity to home-based restorative cognitive rehabilitation in multiple sclerosis: An exploratory study

Mult Scler Relat Disord. 2019 Sep:34:103-111. doi: 10.1016/j.msard.2019.06.026. Epub 2019 Jun 22.

Authors

Tom A Fuchs¹, Stefano Ziccardi², Michael G Dwyer³, Leigh E Charvet⁴, Alexander Bartnik⁵, Rebecca Campbell⁵, Jose Escobar⁵, David Hojnacki⁶, Chana Kolb⁶, Devon Oship⁵, Jeta Pol⁶, Michael T Shaw⁴, Curtis Wojcik⁶, Faizan Yasin⁶, Bianca Weinstock-Guttman⁶, Robert Zivadinov⁷, Ralph H B Benedict⁸

Affiliations

¹ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA. Electronic address: tfuchs@bnac.net.
² Neurology Section, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Italy.
³ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA; Department of Biomedical Informatics, University at Buffalo, State University of New York, Buffalo, NY, USA.
⁴ Department of Neurology, NYU School of Medicine, New York, New York, USA.
⁵ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
⁶ Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
⁷ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA.
⁸ Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA. Electronic address: benedict@buffalo.edu.

PMID: 31254960
DOI: 10.1016/j.msard.2019.06.026

Abstract

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.

Publication types

Clinical Study

MeSH terms

Brain / diagnostic imaging
Brain / pathology
Cognitive Behavioral Therapy*
Cognitive Dysfunction / diagnostic imaging
Cognitive Dysfunction / rehabilitation
Female
Follow-Up Studies
Humans
Magnetic Resonance Imaging
Male
Middle Aged
Multiple Sclerosis / diagnostic imaging
Multiple Sclerosis / psychology*
Multiple Sclerosis / rehabilitation*
Neuropsychological Tests
Organ Size
Patient Compliance
Personality
Quality of Life
Self Care*
Treatment Outcome