Conversion from clinically isolated syndrome to multiple sclerosis: A large multicentre study
Research output: Contribution to journal › Journal article › Research › peer-review
BACKGROUND AND OBJECTIVE: We explored which clinical and biochemical variables predict conversion from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) in a large international cohort.
METHODS: Thirty-three centres provided serum samples from 1047 CIS cases with at least two years' follow-up. Age, sex, clinical presentation, T2-hyperintense lesions, cerebrospinal fluid (CSF) oligoclonal bands (OCBs), CSF IgG index, CSF cell count, serum 25-hydroxyvitamin D3 (25-OH-D), cotinine and IgG titres against Epstein-Barr nuclear antigen 1 (EBNA-1) and cytomegalovirus were tested for association with risk of CDMS.
RESULTS: At median follow-up of 4.31 years, 623 CIS cases converted to CDMS. Predictors of conversion in multivariable analyses were OCB (HR = 2.18, 95% CI = 1.71-2.77, p < 0.001), number of T2 lesions (two to nine lesions vs 0/1 lesions: HR = 1.97, 95% CI = 1.52-2.55, p < 0.001; >9 lesions vs 0/1 lesions: HR = 2.74, 95% CI = 2.04-3.68, p < 0.001) and age at CIS (HR per year inversely increase = 0.98, 95% CI = 0.98-0.99, p < 0.001). Lower 25-OH-D levels were associated with CDMS in univariable analysis, but this was attenuated in the multivariable model. OCB positivity was associated with higher EBNA-1 IgG titres.
CONCLUSIONS: We validated MRI lesion load, OCB and age at CIS as the strongest independent predictors of conversion to CDMS in this multicentre setting. A role for vitamin D is suggested but requires further investigation.
Original language | English |
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Journal | Multiple Sclerosis Journal |
Volume | 21 |
Issue number | 8 |
Pages (from-to) | 1013-24 |
Number of pages | 12 |
ISSN | 1352-4585 |
DOIs | |
Publication status | Published - Jul 2015 |
- Adult, Cohort Studies, Disease Progression, Female, Follow-Up Studies, Humans, Immunoglobulin G, Magnetic Resonance Imaging, Male, Multiple Sclerosis, Nuclear Proteins, Oligoclonal Bands, Predictive Value of Tests, Prognosis, Risk Assessment, Survival Analysis, Vitamin D
Research areas
ID: 162194907