Early imaging predictors of long-term outcomes in relapse-onset multiple sclerosis.


Journal

Brain : a journal of neurology
ISSN: 1460-2156
Titre abrégé: Brain
Pays: England
ID NLM: 0372537

Informations de publication

Date de publication:
01 08 2019
Historique:
received: 28 11 2018
revised: 13 03 2019
accepted: 16 04 2019
pubmed: 26 7 2019
medline: 27 5 2020
entrez: 26 7 2019
Statut: ppublish

Résumé

The clinical course of relapse-onset multiple sclerosis is highly variable. Demographic factors, clinical features and global brain T2 lesion load have limited value in counselling individual patients. We investigated early MRI predictors of key long-term outcomes including secondary progressive multiple sclerosis, physical disability and cognitive performance, 15 years after a clinically isolated syndrome. A cohort of patients with clinically isolated syndrome (n = 178) was prospectively recruited within 3 months of clinical disease onset and studied with MRI scans of the brain and spinal cord at study entry (baseline) and after 1 and 3 years. MRI measures at each time point included: supratentorial, infratentorial, spinal cord and gadolinium-enhancing lesion number, brain and spinal cord volumetric measures. The patients were followed-up clinically after ∼15 years to determine disease course, and disability was assessed using the Expanded Disability Status Scale, Paced Auditory Serial Addition Test and Symbol Digit Modalities Test. Multivariable logistic regression and multivariable linear regression models identified independent MRI predictors of secondary progressive multiple sclerosis and Expanded Disability Status Scale, Paced Auditory Serial Addition Test and Symbol Digit Modalities Test, respectively. After 15 years, 166 (93%) patients were assessed clinically: 119 (72%) had multiple sclerosis [94 (57%) relapsing-remitting, 25 (15%) secondary progressive], 45 (27%) remained clinically isolated syndrome and two (1%) developed other disorders. Physical disability was overall low in the multiple sclerosis patients (median Expanded Disability Status Scale 2, range 0-10); 71% were untreated. Baseline gadolinium-enhancing (odds ratio 3.16, P < 0.01) and spinal cord lesions (odds ratio 4.71, P < 0.01) were independently associated with secondary progressive multiple sclerosis at 15 years. When considering 1- and 3-year MRI variables, baseline gadolinium-enhancing lesions remained significant and new spinal cord lesions over time were associated with secondary progressive multiple sclerosis. Baseline gadolinium-enhancing (β = 1.32, P < 0.01) and spinal cord lesions (β = 1.53, P < 0.01) showed a consistent association with Expanded Disability Status Scale at 15 years. Baseline gadolinium-enhancing lesions was also associated with performance on the Paced Auditory Serial Addition Test (β = - 0.79, P < 0.01) and Symbol Digit Modalities Test (β = -0.70, P = 0.02) at 15 years. Our findings suggest that early focal inflammatory disease activity and spinal cord lesions are predictors of very long-term disease outcomes in relapse-onset multiple sclerosis. Established MRI measures, available in routine clinical practice, may be useful in counselling patients with early multiple sclerosis about long-term prognosis, and personalizing treatment plans.

Identifiants

pubmed: 31342055
pii: 5537631
doi: 10.1093/brain/awz156
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2276-2287

Commentaires et corrections

Type : CommentIn

Informations de copyright

© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Auteurs

Wallace J Brownlee (WJ)

NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK.

Dan R Altmann (DR)

Medical Statistics Department, London School of Hygiene and Tropical Medicine, London, UK.

Ferran Prados (F)

NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK.
Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
Universitat Oberta de Catalunya, Barcelona, Spain.

Katherine A Miszkiel (KA)

Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK.

Arman Eshaghi (A)

NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK.

Claudia A M Gandini Wheeler-Kingshott (CAM)

NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK.
Brain Connectivity Center, C. Mondino National Neurological Institute, Pavia, Italy.
Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.

Frederik Barkhof (F)

NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK.
Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands.
National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre, UK.

Olga Ciccarelli (O)

NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK.
National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre, UK.

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