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Prediction of disability increase in a real world multiple sclerosis cohort
Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience.
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

BACKGROUND Multiple sclerosis (MS) is an autoimmune disease characterized by demyelinating CNS-lesions and neurodegeneration. Brain atrophy measurements have been demonstrated to provide prognostic information. Assessment of brain atrophy via magnetic resonance imaging (MRI) using the Brain Parenchymal Fraction (BPF) was added to the clinical follow-up of individuals with MS at Umeå University Hospital in 2009/2010.  

OBJECTIVE To investigate whether an increase in disability, measured by a short to medium term increase in EDSS, can be predicted using clinically available variables.  To assess if the previously described association between brain atrophy and disability could be detected in the setting of the clinical care program at Umeå University Hospital.

METHODS All adult MS patients with simultaneous data on BPF, lesion count and EDSS at least at one occasion (n=278) were included. Individuals with two (n=163) and three (n=68) time points with complete data were used for testing the ability to predict Expanded Disability Status Scale (EDSS) score longitudinally.

 RESULTS The EDSS was found to correlate with BPF (p<0.001). Progressive disease course and early EDSS-worsening (SPMS), but no other clinical variables, could predict subsequent EDSS-worsening over follow-up times of approximately 1 to 4 years.

CONCLUSION BPF was associated with concurrent EDSS, as previously described. Progressive disease course predicted risk for EDSS-increase but it was otherwise very difficult to predict increased disability in this treated MS-cohort. We discuss possible reasons for the lack of predictive value from clinically used variables in a treated MS cohort. 

National Category
Neurology
Identifiers
URN: urn:nbn:se:umu:diva-128696OAI: oai:DiVA.org:umu-128696DiVA: diva2:1055540
Available from: 2016-12-12 Created: 2016-12-12 Last updated: 2016-12-14
In thesis
1. Brain parenchymal fraction in healthy individuals and in clinical follow-up of multiple sclerosis
Open this publication in new window or tab >>Brain parenchymal fraction in healthy individuals and in clinical follow-up of multiple sclerosis
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background Multiple sclerosis (MS) is an autoimmune disease characterised by inflammatory damage to the central nervous system (CNS). Accumulated CNS injury can be quantified as brain atrophy, definable as a reduction in brain parenchymal fraction (BPF). BPF correlate with disability in MS and is used routinely as an endpoint in clinical trials. In 2009/2010, a new MS clinical care program, that includes follow-up of BPF, was introduced at Umeå University Hospital (NUS). Levels of neurofilament light polypetide (NFL) and glial fibrillary acidic protein (GFAP) in cerebrospinal fluid (CSF) are markers of axonal and astrocytic injury, respectively, and also potential surrogate biomarkers for BPF decline. The goals of this thesis were to establish age-adjusted values of BPF in healthy individuals and to relate these to the BPF values from individuals with MS as well as to the levels of NFL and GFAP in CSF. Another goal was to investigate if expanded disability status scale (EDSS)-worsening could be predicted in a clinical MS cohort and if BPF measurements could contribute to such predictions. Methods A group of 111 healthy individuals volunteered to participate in the studies. A total of 106 of these underwent MRI with BPF measurements, 53 underwent lumbar puncture (LP) with measurement of NFL and GFAP and 48 underwent both MRI and LP. Three different automatic and one manual method were utilised to determine BPF. A literature search on BPF in healthy individuals was performed for the purpose of a systematic review. For studying disability progression in MS, all individuals with MS followed at NUS and included in the Swedish MS registry were included if they had matched data on BPF, EDSS and lesion load as part of clinical follow-up (n=278). Results BPF as well as NFL and GFAP levels in CSF were all associated with age. NFL was associated with BPF and GFAP, but only the association with GFAP was retained when adjusting for age. Significant differences were found between different methods for BPF determination. In the MS population, BPF was associated with EDSS. Only progressive disease course could predict EDSS worsening. Conclusion The data on BPF and levels of NFL and GFAP in CSF of healthy individuals can aid in the interpretation of these variables in the setting of MS. Knowledge on differences in BPF data from different methods for BPF determination can be useful in comparing data across studies, but also highlights the need for a commonly accepted gold standard. The correlation between GFAP and NFL levels in CSF may indicate an association between glial and axonal turnover that is independent of the aging effect on the brain. However, the low number of volunteers for LP precluded clear conclusions. An association between BPF and EDSS was seen in the MS group. The ability to predict EDSS worsening in the clinical MS cohort was limited.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2016. 80 p.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1867
Keyword
Brain parenchymal fraction, Neurofilament light, Glial fibrillary acidic protein, Brain atrophy, Multiple Sclerosis, Clinical follow-up
National Category
Neurology
Identifiers
urn:nbn:se:umu:diva-128697 (URN)978-91-7601-621-3 (ISBN)
Public defence
2017-01-20, Sal A, Tandläkarhögskolan 9 trappor, byggnad 1D, Umeå, 13:00 (Swedish)
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Supervisors
Available from: 2016-12-16 Created: 2016-12-12 Last updated: 2016-12-20Bibliographically approved

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Vågberg, MattiasGranåsen, GabrielSvenningsson, RasmusLindqvist, ThomasBirgander, RichardSvenningsson, Anders
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