ECTRIMS eLearning

Disease course and grey matter volume predict success of home-based cognitive rehabilitation in multiple sclerosis
Author(s): ,
T. Fuchs
Affiliations:
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; Neurology, University at Buffalo, Buffalo, NY, United States
,
S. Ziccardi
Affiliations:
Neurology, University at Buffalo, Buffalo, NY, United States; Verona University, Verona, Italy
,
R. Benedict
Affiliations:
Neurology, University at Buffalo, Buffalo, NY, United States
,
L. Charvet
Affiliations:
New York University Langone Medical Center, Multiple Sclerosis Comprehensive Care Center, New York, NY, United States
,
M. Shaw
Affiliations:
New York University Langone Medical Center, Multiple Sclerosis Comprehensive Care Center, New York, NY, United States
,
A. Bartnik
Affiliations:
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; Neurology, University at Buffalo, Buffalo, NY, United States
,
D. Oship
Affiliations:
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; Neurology, University at Buffalo, Buffalo, NY, United States
,
R. Campbell
Affiliations:
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; Neurology, University at Buffalo, Buffalo, NY, United States
,
J. Escobar
Affiliations:
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; Neurology, University at Buffalo, Buffalo, NY, United States
,
F. Yasin
Affiliations:
Neurology, University at Buffalo, Buffalo, NY, United States
,
J. Pol
Affiliations:
Neurology, University at Buffalo, Buffalo, NY, United States
,
C. Wojcik
Affiliations:
Neurology, University at Buffalo, Buffalo, NY, United States
,
R. Zivadinov
Affiliations:
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; Neurology, University at Buffalo, Buffalo, NY, United States
M. Dwyer
Affiliations:
Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; Neurology, University at Buffalo, Buffalo, NY, United States
ECTRIMS Learn. Fuchs T. 10/11/18; 228793; P950
Tom Fuchs
Tom Fuchs
Contributions
Abstract

Abstract: P950

Type: Poster Sessions

Abstract Category: Therapy - Symptomatic treatment

Background: Adaptable cognitive training interventions are accessible online from home for people with multiple sclerosis (PwMS), including for those with limited mobility, and have been shown to significantly improve cognition relative to control treatments. However, individual responsiveness to treatment is highly variable. Baseline clinical and MRI factors may contribute to this variability.
Objective: To determine whether specific baseline clinical and neuropathological MRI factors predict the success of online cognitive training in PwMS.
Methods: 46 PwMS (30 RRMS, 16 PMS) were recruited for a 12-week home-based cognitive rehabilitation program. Subjects were recruited from a cohort of individuals with MRI previously collected (~2.3 years prior) for a larger study (Zivadinov, et al., 2017). Baseline and follow-up neuropsychological assessment included standard tests of cognition (SDMT, BVMTR, CVLT-II) and executive function (DKEFS), as well as clinical questionnaires. Participants were asked to complete 5 training sessions per week for approximately 50 minutes per session. Forward stepwise selection was applied using baseline clinical measures, including age, sex, EDSS, fatigue, depression, personality, disease course, and education, to predict longitudinal change in SDMT performance following rehabilitation from brain MRI measures. A separate, analogous regression analysis was applied to investigate MRI predictors of SDMT performance improvement, and included lateral ventricular volume (LVV), gray matter volume (GMV), and T2 lesion volume (T2LV).
Results: Disease course (RRMS vs PMS) was a statistically significant clinical predictor of improvement on SDMT performance following rehabilitation (β=-0.336, p=0.026). The RRMS subgroup showed a 4.34 +/- 5.74 point improvement (p< 0.0001), while there was no significant change in the PMS group (0.25 +/- 4.73 points, p=0.835). Among MRI measures, baseline GMV was significantly related to improvement on SDMT performance (β=0.367, p=0.014).
Conclusion: Remote cognitive rehabilitation therapy is more effective for individuals with RRMS, rather than those with PMS. Furthermore, increased baseline GMV is also predictive of greater cognitive improvement following rehabilitation.
Disclosure: Tom Fuchs, Stefano Ziccardi, Leigh Charvet, Michael T. Shaw, Alex Bartnik, Devon Oship, Rebecca Campbell, Jose Escobar, Faizan Yasin, Jeta Pol, and Curtis Wojcik have nothing to declare.
Ralph H. B. Benedict has received research support from Accorda, Novartis, Genzyme, Biogen Idec, and Mallinkrodt, and is on the speakers' bureau for EMD Serono, and consults for Biogen Idec, Genentech, Roche, Sanofi/Genzyme, Takeda, NeuroCog Trials, and Novartis. Dr. Benedict also receives royalties for Psychological Assessment Resources.
Bianca Weinstock-Guttman received honoraria as a speaker and as a consultant for Biogen Idec, Teva Pharmaceuticals, EMD Serono, Genzyme, Sanofi, Novartis and Acorda. Dr Weinstock-Guttman received research funds from Biogen Idec, Teva Pharmaceuticals, EMD Serono,Genzyme, Sanofi, Novartis, Acorda.
R Zivadinov received personal compensation from EMD Serono, Genzyme-Sanofi, Novartis, Claret-Medical, Celgene for speaking and consultant fees. He received financial support for research activities from Claret Medical, Genzyme-Sanofi, QuintilesIMS Health, Intekrin-Coherus, Novartis and Intekrin-Coherus.
Michael G. Dwyer has received consultant fees from Claret Medical and EMD Serono and research grant support from Novartis.

Abstract: P950

Type: Poster Sessions

Abstract Category: Therapy - Symptomatic treatment

Background: Adaptable cognitive training interventions are accessible online from home for people with multiple sclerosis (PwMS), including for those with limited mobility, and have been shown to significantly improve cognition relative to control treatments. However, individual responsiveness to treatment is highly variable. Baseline clinical and MRI factors may contribute to this variability.
Objective: To determine whether specific baseline clinical and neuropathological MRI factors predict the success of online cognitive training in PwMS.
Methods: 46 PwMS (30 RRMS, 16 PMS) were recruited for a 12-week home-based cognitive rehabilitation program. Subjects were recruited from a cohort of individuals with MRI previously collected (~2.3 years prior) for a larger study (Zivadinov, et al., 2017). Baseline and follow-up neuropsychological assessment included standard tests of cognition (SDMT, BVMTR, CVLT-II) and executive function (DKEFS), as well as clinical questionnaires. Participants were asked to complete 5 training sessions per week for approximately 50 minutes per session. Forward stepwise selection was applied using baseline clinical measures, including age, sex, EDSS, fatigue, depression, personality, disease course, and education, to predict longitudinal change in SDMT performance following rehabilitation from brain MRI measures. A separate, analogous regression analysis was applied to investigate MRI predictors of SDMT performance improvement, and included lateral ventricular volume (LVV), gray matter volume (GMV), and T2 lesion volume (T2LV).
Results: Disease course (RRMS vs PMS) was a statistically significant clinical predictor of improvement on SDMT performance following rehabilitation (β=-0.336, p=0.026). The RRMS subgroup showed a 4.34 +/- 5.74 point improvement (p< 0.0001), while there was no significant change in the PMS group (0.25 +/- 4.73 points, p=0.835). Among MRI measures, baseline GMV was significantly related to improvement on SDMT performance (β=0.367, p=0.014).
Conclusion: Remote cognitive rehabilitation therapy is more effective for individuals with RRMS, rather than those with PMS. Furthermore, increased baseline GMV is also predictive of greater cognitive improvement following rehabilitation.
Disclosure: Tom Fuchs, Stefano Ziccardi, Leigh Charvet, Michael T. Shaw, Alex Bartnik, Devon Oship, Rebecca Campbell, Jose Escobar, Faizan Yasin, Jeta Pol, and Curtis Wojcik have nothing to declare.
Ralph H. B. Benedict has received research support from Accorda, Novartis, Genzyme, Biogen Idec, and Mallinkrodt, and is on the speakers' bureau for EMD Serono, and consults for Biogen Idec, Genentech, Roche, Sanofi/Genzyme, Takeda, NeuroCog Trials, and Novartis. Dr. Benedict also receives royalties for Psychological Assessment Resources.
Bianca Weinstock-Guttman received honoraria as a speaker and as a consultant for Biogen Idec, Teva Pharmaceuticals, EMD Serono, Genzyme, Sanofi, Novartis and Acorda. Dr Weinstock-Guttman received research funds from Biogen Idec, Teva Pharmaceuticals, EMD Serono,Genzyme, Sanofi, Novartis, Acorda.
R Zivadinov received personal compensation from EMD Serono, Genzyme-Sanofi, Novartis, Claret-Medical, Celgene for speaking and consultant fees. He received financial support for research activities from Claret Medical, Genzyme-Sanofi, QuintilesIMS Health, Intekrin-Coherus, Novartis and Intekrin-Coherus.
Michael G. Dwyer has received consultant fees from Claret Medical and EMD Serono and research grant support from Novartis.

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