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Titolo:
Modelling new enhancing MRI lesion counts in multiple sclerosis
Autore:
Sormani, MP; Bruzzi, P; Rovaris, M; Barkhof, F; Comi, G; Miller, DH; Cutter, GR; Filippi, M;
Indirizzi:
Natl Inst Canc Res, Unit Clin Epidemiol & Trials, Genoa, Italy Natl Inst Canc Res Genoa Italy it Clin Epidemiol & Trials, Genoa, Italy Sci Inst Osped, Dept Neurosci, Neuroimaging Res Unit, Milan, Italy Sci Inst Osped Milan Italy eurosci, Neuroimaging Res Unit, Milan, Italy Univ San Raffael, Milan, Italy Univ San Raffael Milan ItalyUniv San Raffael, Milan, Italy Sci Inst Osped, Dept Neurosci, Clin Trials Unit, Milan, Italy Sci Inst Osped Milan Italy ept Neurosci, Clin Trials Unit, Milan, Italy Free Univ Amsterdam Hosp, Dutch MS MR Ctr, NL-1081 HV Amsterdam, Netherlands Free Univ Amsterdam Hosp Amsterdam Netherlands NL-1081 HV m, Netherlands Inst Neurol, NMR Res Unit, London WC1N 3BG, England Inst Neurol London England WC1N 3BG R Res Unit, London WC1N 3BG, England AMC Canc Res Ctr, Ctr Res Methods & Biometr, Lakewood, CO USA AMC Canc ResCtr Lakewood CO USA Res Methods & Biometr, Lakewood, CO USA
Titolo Testata:
MULTIPLE SCLEROSIS
fascicolo: 5, volume: 7, anno: 2001,
pagine: 298 - 304
SICI:
1352-4585(200110)7:5<298:MNEMLC>2.0.ZU;2-B
Fonte:
ISI
Lingua:
ENG
Soggetto:
MAGNETIC-RESONANCE TECHNIQUES; DISEASE-ACTIVITY; STATISTICAL POWER; PARALLEL-GROUPS; POISSON; TRIALS; MS; REGRESSION; GUIDELINES; OUTCOMES;
Keywords:
multiple sclerosis; magnetic resonance imaging; mixed poisson distributions;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Life Sciences
Citazioni:
28
Recensione:
Indirizzi per estratti:
Indirizzo: Filippi, M San Raffaele Sci Inst, Dept Neurosci, Neuroimaging Res Unit, Via Olgettino60, I-20132 Milan, Italy San Raffaele Sci Inst Via Olgettino 60 Milan Italy I-20132 aly
Citazione:
M.P. Sormani et al., "Modelling new enhancing MRI lesion counts in multiple sclerosis", MULT SCLER, 7(5), 2001, pp. 298-304

Abstract

Magnetic resonance imaging (MRI) has been established as the most relevantparaclinical toot for diagnosing and monitoring multiple sclerosis (MS). In this context counting the number of new enhancing lesions on monthly MRI scans is widely used as a surrogate marker of MS activity when evaluating the effect of treatments. In this study, we investigated whether parametric models based on mixed Poisson distributions (the Negative Binomial (NB) andthe Poisson-Inverse Gaussian (P-IG) distributions) were able to provide adequate fitting of new enhancing lesion counts in MS. We found that the NB model gave good approximations in relapsing-remitting and secondary progressive MS patients not selected for baseline MRI activity, whereas the P-IG distribution modelled better new enhancing lesion counts in relapsing-remitting MS patients selected for baseline activity. This study shows that parametric modelling for MS new enhancing lesion counts is feasible. This approach should provide more targeted tools for the design and the analysis of MRImonitored clinical trials in MS.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 28/03/20 alle ore 13:11:21