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 journalArticle

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 pages3
JournalJournal of Neurology, Neurosurgery and Psychiatry
Volume78
Issue number7
DOIs
Publication statusPublished - Jul 2007

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Neuroscience(all)
  • Psychiatry and Mental health

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    Bergamaschi, R., Quaglini, S., Trojano, M., Amato, M. P., Tavazzi, E., Paolicelli, D., Zipoli, V., Romani, A., Fuiani, A., Portaccio, E., Berzuini, C., Montomoli, C., Bastianello, S., & Cosi, V. (2007). Early prediction of the long term evolution of multiple sclerosis: The Bayesian Risk Estimate for Multiple Sclerosis (BREMS) score. Journal of Neurology, Neurosurgery and Psychiatry, 78(7), 757-759. https://doi.org/10.1136/jnnp.2006.107052