Reaching an evidence-based prognosis for personalized treatment of multiple sclerosis

Dalia Rotstein, Xavier Montalban*

*Corresponding author for this work

Research output: Contribution to journalReview articleResearchpeer-review

106 Citations (Scopus)


Personalized treatment is ideal for multiple sclerosis (MS) owing to the heterogeneity of clinical features, but current knowledge gaps, including validation of biomarkers and treatment algorithms, limit practical implementation. The contemporary approach to personalized MS therapy depends on evidence-based prognostication, an initial treatment choice and evaluation of early treatment responses to identify the need to switch therapy. Prognostication is directed by baseline clinical, environmental and demographic factors, MRI measures and biomarkers that correlate with long-term disability measures. The initial treatment choice should be a shared decision between the patient and physician. In addition to prognosis, this choice must account for patient-related factors, including comorbidities, pregnancy planning, preferences of the patients and their comfort with risk, and drug-related factors, including safety, cost and implications for treatment sequencing. Treatment response has traditionally been assessed on the basis of relapse rate, MRI lesions and disability progression. Larger longitudinal data sets have enabled development of composite outcome measures and more stringent standards for disease control. Biomarkers, including neurofilament light chain, have potential as early surrogate markers of prognosis and treatment response but require further validation. Overall, attainment of personalized treatment for MS is complex but will be refined as new data become available.

Original languageEnglish
Pages (from-to)287-300
Number of pages14
JournalNature Reviews Neurology
Issue number5
Early online date2 Apr 2019
Publication statusPublished - 1 May 2019


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