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.
- multiple sclerosis (ms)
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DC and RW-T contributed equally.
Contributors DC, RW-T, SL, EB, OWH and ECT all contributed to the drafting of the manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Commissioned. Externally peer reviewed by Martin Duddy, Newcastle-upon-Tyne, UK, and Alasdair Coles, Cambridge, UK.
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