Using Biomarkers To Predict Clinical Outcomes In Multiple Sclerosis
June 26, 2019
Castle D, Wynford-Thomas R, Loveless S, Bentley E, Howell OW and Tallantyre EC
Pract Neurol. 2019 Jun 26. pii: practneurol-2018-002000. doi: 10.1136/practneurol-2018-002000.
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.