Castle, Daniel, Wynford-Thomas, Ray, Loveless, Sam ORCID: https://orcid.org/0000-0002-5124-4115, Bentley, Emily, Howell, Owain W and Tallantyre, Emma C ORCID: https://orcid.org/0000-0002-3760-6634 2019. Using biomarkers to predict clinical outcomes in multiple sclerosis. Practical Neurology 19 (4) , pp. 342-349. 10.1136/practneurol-2018-002000 |
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Abstract
Long-term outcomes in multiple sclerosis (MS) are highly varied and treatment with disease-modifying therapies carries significant risks. Finding tissue biomarkers that can predict clinical outcomes would be valuable in individualising treatment decisions for people with MS. Several candidate biomarkers—reflecting inflammation, neurodegeneration and glial pathophysiology—show promise for predicting outcomes. However, many candidates still require validation in cohorts with long-term follow-up and evaluation for their independent contribution in predicting outcome when models are adjusted for known demographic, clinical and radiological predictors. Given the complexity of MS pathophysiology, heterogeneous panels comprising a combination of biomarkers that encompass the various aspects of neurodegenerative, glial and immune pathology seen in MS, may enhance future predictions of outcome.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Medicine MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) |
Publisher: | BMJ Publishing Group / Blackwell Publishing |
ISSN: | 1474-7758 |
Date of First Compliant Deposit: | 12 July 2019 |
Date of Acceptance: | 25 March 2019 |
Last Modified: | 20 Nov 2024 09:15 |
URI: | https://orca.cardiff.ac.uk/id/eprint/124194 |
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