Literature DB >> 22888087

Dealing with excess of zeros in the statistical analysis of magnetic resonance imaging lesion count in multiple sclerosis.

Mercier Francois1, Chin Peter, Francis Gordon.   

Abstract

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.

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Year:  2012        PMID: 22888087     DOI: 10.1002/pst.1529

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  3 in total

1.  Statistical Methods for Unusual Count Data: Examples From Studies of Microchimerism.

Authors:  Katherine A Guthrie; Hilary S Gammill; Mads Kamper-Jørgensen; Anne Tjønneland; Vijayakrishna K Gadi; J Lee Nelson; Wendy Leisenring
Journal:  Am J Epidemiol       Date:  2016-11-15       Impact factor: 4.897

2.  Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials.

Authors:  Leonard H Verhey; Alessio Signori; Douglas L Arnold; Amit Bar-Or; A Dessa Sadovnick; Ruth Ann Marrie; Brenda Banwell; Maria Pia Sormani
Journal:  Neurology       Date:  2013-08-21       Impact factor: 9.910

3.  Marginalized zero-inflated negative binomial regression with application to dental caries.

Authors:  John S Preisser; Kalyan Das; D Leann Long; Kimon Divaris
Journal:  Stat Med       Date:  2015-11-15       Impact factor: 2.373

  3 in total

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