Early prediction of the long term evolution of multiple sclerosis: the Bayesian Risk Estimate for Multiple Sclerosis (BREMS) score.
OBJECTIVE
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<0.0001). The BREMS value was related to SP risk in the whole cohort (p<0.0001) and in the subgroup of 535 patients who had never been treated with immune therapies, thus reasonably representing the natural history of the disease (p<0.000001).


CONCLUSIONS
The BREMS score may be useful both to identify patients who are candidates for early or for more aggressive therapies and to improve the design and analysis of clinical therapeutic trials and of observational studies.
Bergamaschi
Roberto
R
Multiple Sclerosis Centre, Department of Clinical Neurology, Neurological Institute C Mondino, Via Mondino 2, 27100 Pavia, Italy. roberto.bergamaschi@mondino.it
Quaglini
Silvana
S
Trojano
Maria
M
Amato
Maria Pia
MP
Tavazzi
Eleonora
E
Paolicelli
Damiano
D
Zipoli
Valentina
V
Romani
Alfredo
A
Fuiani
Aurora
A
Portaccio
Emilio
E
Berzuini
Carlo
C
Montomoli
Cristina
C
Bastianello
Stefano
S
Cosi
Vittorio
V
D000328:Adult; D001499:Bayes Theorem; D015331:Cohort Studies; D018450:Disease Progression; D005260:Female; D006801:Humans; D008297:Male; D009103:Multiple Sclerosis / Q000473:pathology*; D011379:Prognosis; D012720:Severity of Illness Index