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Dealing with excess of zeros in the statistical analysis of magnetic resonance imaging lesion count in multiple sclerosis
Author(s) -
Francois Mercier,
Peter Chin,
Gordon Francis
Publication year - 2012
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1529
Subject(s) - count data , negative binomial distribution , poisson distribution , poisson regression , multiple sclerosis , magnetic resonance imaging , context (archaeology) , fingolimod , medicine , clinical trial , statistics , mathematics , radiology , pathology , population , paleontology , environmental health , psychiatry , biology
Lesion count observed on brain magnetic resonance imaging scan is a common end point in phase 2 clinical trials evaluating therapeutic treatment in relapsing remitting multiple sclerosis (MS). This paper compares the performances of Poisson, zero‐inflated poisson (ZIP), negative binomial (NB), and zero‐inflated NB (ZINB) mixed‐effects regression models in fitting lesion count data in a clinical trial evaluating the efficacy and safety of fingolimod in comparison with placebo, in MS. The NB and ZINB models prove to be superior to the Poisson and ZIP models. We discuss the advantages and limitations of zero‐inflated models in the context of MS treatment. Copyright © 2012 John Wiley & Sons, Ltd.