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Titolo:
Modelling MRI enhancing lesion counts in multiple sclerosis using a negative binomial model: implications for clinical trials
Autore:
Sormani, MP; Bruzzi, P; Miller, DH; Gasperini, C; Barkhof, F; Filippi, L;
Indirizzi:
Natl Inst Canc Res, Unit Clin Epidemiol & Trials, I-16132 Genoa, Italy Natl Inst Canc Res Genoa Italy I-16132 ol & Trials, I-16132 Genoa, Italy Univit,lan, Osped San Raffaele, Inst Sci, Dept Neurosci,Neuroimaging Res Un Univ Milan Milan Italy I-20127 st Sci, Dept Neurosci,Neuroimaging Res Un Inst Neurol, NMR Res Unit, London WC1N 3BG, England Inst Neurol London England WC1N 3BG R Res Unit, London WC1N 3BG, England Univ Rome, S Camillo Hosp, Dept Neurol, Rome, Italy Univ Rome Rome Italy niv Rome, S Camillo Hosp, Dept Neurol, Rome, Italy Free Univ Amsterdam Hosp, Dutch MS MR Ctr, Amsterdam, Netherlands Free Univ Amsterdam Hosp Amsterdam Netherlands , Amsterdam, Netherlands
Titolo Testata:
JOURNAL OF THE NEUROLOGICAL SCIENCES
fascicolo: 1, volume: 163, anno: 1999,
pagine: 74 - 80
SICI:
0022-510X(19990201)163:1<74:MMELCI>2.0.ZU;2-O
Fonte:
ISI
Lingua:
ENG
Soggetto:
DISEASE-ACTIVITY; PARALLEL-GROUPS; GUIDELINES; POISSON; RATES;
Keywords:
multiple sclerosis; magnetic resonance imaging; negative binomial distribution;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
17
Recensione:
Indirizzi per estratti:
Indirizzo: Sormani, MP Natl-16132Canc Res, Unit Clin Epidemiol & Trials, Largo Rosanna Benzi 10, I Natl Inst Canc Res Largo Rosanna Benzi 10 Genoa Italy I-16132
Citazione:
M.P. Sormani et al., "Modelling MRI enhancing lesion counts in multiple sclerosis using a negative binomial model: implications for clinical trials", J NEUR SCI, 163(1), 1999, pp. 74-80

Abstract

In multiple sclerosis (MS) the number of new enhancing lesions seen on monthly magnetic resonance imaging (MRT) scans is the most widely used response variable in MRI-monitored studies of experimental treatments. However, nostatistical model has been proposed to describe the distribution of the number of such lesions across MS patients. This article briefly summarizes the statistical models for counted data. The negative binomial (NB) model is proposed to fit the number of new enhancing lesions counted in a set of 56 untreated MS patients followed for 9 months, It is shown that the large variability present in this data set is better addressed by the NE model (residual deviance=66.6, 54 degrees of freedom):than by the Poisson model (residual deviance=1830.1, 55 degrees of freedom). Applications of the parametrization of lesion counts are discussed, and an example related to computer simulations for the sample size estimation is presented. (C) 1999 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 10/07/20 alle ore 08:38:11