Early prediction of the long term evolution of multiple sclerosis: The Bayesian Risk Estimate for Multiple Sclerosis (BREMS) score

Roberto Bergamaschi, Silvana Quaglini, Maria Trojano, Maria Pia Amato, Eleonora Tavazzi, Damiano Paolicelli, Valentino Zipoli, Alfredo Romani, Aurora Fuiani, Emilio Portaccio, Carlo Berzuini, Cristina Montomoli, Stefano Bastianello, Vittorio Cosi

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Aim: To propose a simple tool for early prediction of unfavourable long term evolution of multiple sclerosis (MS). Methods: A Bayesian model allowed us to calculate, within the first year of disease and for each patient, the Bayesian Risk Estimate for MS (BREMS) score that represents the risk of reaching secondary progression (SP). Results: The median BREMS scores were higher in 158 patients who reached SP within 10 years compared with 1087 progression free patients (0.69 vs 0.30; p
    Original languageEnglish
    Pages (from-to)757-759
    Number of pages2
    JournalJournal of Neurology, Neurosurgery and Psychiatry
    Volume78
    Issue number7
    DOIs
    Publication statusPublished - Jul 2007

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