4.6 Article

Onset of secondary progressive phase and long-term evolution of multiple sclerosis

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BMJ PUBLISHING GROUP
DOI: 10.1136/jnnp-2012-304333

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  1. Italian Multiple Sclerosis Foundation (FISM) [2008/R/16]
  2. Medical Research Council [G0800679]
  3. MS Society of Canada
  4. UK MS Society
  5. German Ministry for Education and Research (BMBF) [01GI0904, 01GI0920]
  6. MRC [G0800679] Funding Source: UKRI

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Objectives To assess factors affecting the rate of conversion to secondary progressive (SP) multiple sclerosis (MS) and its subsequent evolution. Methods Among 806 patients with relapsing remitting (RR) onset MS from the London Ontario database, we used Kaplan-Meier, Cox regression and multiple logistic regression analyses to investigate the effect of baseline clinical and demographic features on (1) the probability of, and the time to, SP disease, (2) the time to bedbound status (Disability Status Scale (DSS 8)) from onset of progression. Results The risk of entering the SP phase increased proportionally with disease duration (OR=1.07 for each additional year; p<0.001). Shorter latency to SP was associated with shorter times to severe disability. The same association was found even when patients were grouped by number of total relapses before progression. However, the evolution of the SP phase was not influenced by the duration of the RR phase. Male sex (HR=1.41; p<0.001), older age at onset (age <= 20 and 21-30 vs >30 HR=0.52 (p<0.001), 0.65 (p<0.001), respectively) and high early relapse frequency (1-2 attacks vs >= 3 HR=0.63 (p<0.001), 0.75 (p=0.04), respectively) predicted significantly higher risk of SP MS and shorter latency to progression. Times to DSS 8 from onset of progression were significantly shorter among those with high early relapse frequency (>= 3 attacks), and among those presenting with cerebellar and brainstem symptoms. Conclusions The onset of SP MS is the dominant determinant of long-term prognosis, and its prevention is the most important target measure for treatment. Baseline clinical features of early relapse frequency and age at onset can be used to select groups at higher risk of developing severe disability based on the probability of their disease becoming progressive within a defined time period.

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