Predictors of progression from a first demyelinating event to clinically definite multiple sclerosis

Understanding the predictors of progression from a first to a second demyelinating event (and formerly, a diagnosis of clinically definite multiple sclerosis) is important clinically. Previous studies have focused on predictors within a single domain, e.g. radiological, lacking prospective data across multiple domains. We tested a comprehensive set of personal, environmental, neurological, MRI and genetic characteristics, considered together, as predictors of progression from a first demyelinating event to clinically definite multiple sclerosis. Participants were aged 18–59 years and had a first demyelinating event during the study recruitment period (1 November 2003–31 December 2006) for the Ausimmune Study (n = 216) and had follow-up data to 2–3 years post-initial interview. Detailed baseline data were available on a broad range of demographic and environmental factors, MRI, and genetic and viral studies. Follow-up data included confirmation of clinically definite multiple sclerosis (or not) and changes in environmental exposures during the follow-up period. We used multivariable logistic regression and Cox proportional hazards regression modelling to test predictors of, and time to, conversion to clinically definite multiple sclerosis. On review, one participant had an undiagnosed event prior to study recruitment and was excluded (n = 215). Data on progression to clinically definite multiple sclerosis were available for 91.2% (n = 196); 77% were diagnosed as clinically definite multiple sclerosis at follow-up. Mean (standard deviation) duration of follow-up was 2.7 (0.7) years. The set of predictors retained in the best predictive model for progression from a first demyelinating event to clinically definite multiple sclerosis were as follows: younger age at first demyelinating event [adjusted odds ratio (aOR) = 0.92, 95% confidence interval (CI) = 0.87–0.97, per additional year of age); being a smoker at baseline (versus not) (aOR = 2.55, 95% CI 0.85–7.69); lower sun exposure at age 6–18 years (aOR = 0.86, 95% CI 0.74–1.00, per 100 kJ/m(2) increment in ultraviolet radiation dose), presence (versus absence) of infratentorial lesions on baseline magnetic resonance imaging (aOR = 7.41, 95% CI 2.08–26.41); and single nucleotide polymorphisms in human leukocyte antigen (HLA)-B (rs2523393, aOR = 0.25, 95% CI 0.09–0.68, for any G versus A:A), TNFRSF1A (rs1800693, aOR = 5.82, 95% CI 2.10–16.12, for any C versus T:T), and a vitamin D-binding protein gene (rs7041, aOR = 3.76, 95% CI 1.41–9.99, for any A versus C:C). The final model explained 36% of the variance. Predictors of more rapid progression to clinically definite multiple sclerosis (Cox proportional hazards regression) were similar. Genetic and magnetic resonance imaging characteristics as well as demographic and environmental factors predicted progression, and more rapid progression, from a first demyelinating event to a second event and clinically definite multiple sclerosis.