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Modelling MRI enhancing lesion counts in multiple sclerosis using a negative binomial model: implications for clinical trials

Sormani, MP; Bruzzi, P; Miller, DH; Gasperini, C; Barkhof, F; Filippi, L; (1999) Modelling MRI enhancing lesion counts in multiple sclerosis using a negative binomial model: implications for clinical trials. J NEUROL SCI , 163 (1) 74 - 80.

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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, no statistical 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.

Type: Article
Title: Modelling MRI enhancing lesion counts in multiple sclerosis using a negative binomial model: implications for clinical trials
Keywords: multiple sclerosis, magnetic resonance imaging, negative binomial distribution, DISEASE-ACTIVITY, PARALLEL-GROUPS, GUIDELINES, POISSON, RATES
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: http://discovery.ucl.ac.uk/id/eprint/146174
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