title: Modeling MR imaging enhancing-lesion volumes in multiple sclerosis: application in clinical trials.
abstract: OBJECTIVE
  Although the number of enhancing lesions is the typical outcome measure of choice in clinical trials in MS, a potentially more sensitive and statistically more powerful outcome measure is the volume of enhancing lesions. In this study, we assessed the distribution and statistical power of the volume of enhancing brain lesions as an outcome measure by means of their required sample size, and we compared the results with the number of enhancing lesions.
  
  
  METHODS
  First, a literature search was performed to compare the effects of treatment on the number and volume of enhancing lesions. Then, a statistical model was proposed to describe the distribution of the volume of enhancing lesions in 2 datasets of patients with RRMS, and sample sizes for enhancing-lesion volume as primary outcome measure were calculated.
  
  
  RESULTS
  A mixture of the binomial and Weibull distribution was determined to model enhancing-lesion volumes in patients. Sample size calculations for enhancing-lesion volumes showed that approximately 94 patients per arm would be required to detect a combination of 20% decrease in lesion volume and 20% increase in patients without enhancing lesions, whereas calculations for enhancing-lesion counts showed that approximately 129 patients would be required to detect a 50% decrease.
  
  
  CONCLUSIONS
  The mixture of the binomial and Weibull distribution is a suitable approach in modeling new enhancing-lesion volumes in MS and yielded feasible sample size estimates for clinical trials, showing lesion volumes to be an advantageous outcome measure compared with lesion counts in terms of statistical power.
authors: Department of Radiology, VU University Medical Center, Amsterdam, theNetherlands. i.vandenelskamp@vumc.nl
authors: I J
authors: IJ
authors: van den Elskamp
authors: D L
authors: DL
authors: Knol
authors: B M J
authors: BM
authors: Uitdehaag
authors: F
authors: F
authors: Barkhof
mesh_terms: D000328:Adult; D001921:Brain / Q000473:pathology; D002986:Clinical Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data*; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D009103:Multiple Sclerosis / Q000453:epidemiology / Q000473:pathology* / Q000628:therapy*; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016896:Treatment Outcome