title: Persistent T1 hypointensity as an MRI marker for treatment efficacy in multiple sclerosis.
abstract: BACKGROUND
  MRI is often used as primary outcome measure in phase II clinical trials in multiple sclerosis (MS). Since persistent T1 hypointense lesions are a surrogate parameter for axonal damage and demyelination, they may serve as a marker for monitoring the efficacy of neuroprotective drugs. At present, a power analysis using black hole (BH) evolution as primary outcome measure has not been performed.
  
  
  OBJECTIVE
  To assess the feasibility of using BH evolution on serial brain MR images as primary outcome measure in proof of concept studies in MS.
  
  
  METHODS
  MRI-data obtained from 169 active RRMS patients were analysed for BH evolution by determining the cumulative number of contrast enhancing lesions (CEL) evolving into a persistent black hole (PBH) after 3 months. With a parametric simulation procedure, based on a statistical distribution fitting the data, sample sizes were calculated.
  
  
  RESULTS
  21.2% of the total number of CELs observed during the study period evolved into a PBH. Ring enhancing lesions evolved most frequently into a PBH (59.4%), followed by lesions larger than 10 mm (57.4%) and periventricular CELs (30.6%). The simulation procedure, based on the statistical negative binomial (NB) model resulted in a sample sizes between 200 subjects and 30 subjects per arm, for treatment effects ranging from 50% to 90% reduction of the number of CELs evolving into a PBH, respectively.
  
  
  CONCLUSIONS
  To perform a MRI monitored phase II clinical trial with a feasible sample size, using the evolution of CELs into PBHs as primary outcome parameter, a potent drug is required to obtain sufficient power.
authors.affiliation: Department of Radiology, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. vandenelskamp@vume.nl
authors.forename: I J
authors.initials: IJ
authors.lastname: van den Elskamp
authors.forename: J
authors.initials: J
authors.lastname: Lembcke
authors.forename: V
authors.initials: V
authors.lastname: Dattola
authors.forename: K
authors.initials: K
authors.lastname: Beckmann
authors.forename: C
authors.initials: C
authors.lastname: Pohl
authors.forename: W
authors.initials: W
authors.lastname: Hong
authors.forename: R
authors.initials: R
authors.lastname: Sandbrink
authors.forename: K
authors.initials: K
authors.lastname: Wagner
authors.forename: D L
authors.initials: DL
authors.lastname: Knol
authors.forename: B
authors.initials: B
authors.lastname: Uitdehaag
authors.forename: F
authors.initials: F
authors.lastname: Barkhof
mesh_terms: D000276:Adjuvants, Immunologic / Q000008:administration & dosage*; D000284:Administration, Oral; D015415:Biomarkers; D003287:Contrast Media; D016903:Drug Monitoring / Q000379:methods*; D019786:Gadolinium DTPA; D006801:Humans; D000068556:Interferon beta-1a; D016899:Interferon-beta / Q000008:administration & dosage*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D020529:Multiple Sclerosis, Relapsing-Remitting / Q000188:drug therapy* / Q000473:pathology*; D016896:Treatment Outcome
chemical_list: D000276:Adjuvants, Immunologic; D015415:Biomarkers; D003287:Contrast Media; D016899:Interferon-beta; D019786:Gadolinium DTPA; D000068556:Interferon beta-1a