Specific power calculations for magnetic resonance imaging (MRI) in monitoring active relapsing-remitting multiple sclerosis (MS): implications for phase II therapeutic trials

Mult Scler. 1997 Jan;2(6):283-90. doi: 10.1177/135245859700200604.

Abstract

Inhomogeneous patient samples have been used in previous studies to determine the power of magnetic resonance imaging (MRI) for trial monitoring in multiple sclerosis (MS). These power-calculations might not be applicable to the active relapsing-remitting patient who is preferably included in trials. In order to reevaluate the power-calculations for MRI in the monitoring of treatment in strictly relapsing-remitting MS and to compare the power of different trial designs we studied 12 relapsing-remitting MS patients prospectively for a median period of 12 months using monthly clinical assessments and gadolinium-enhanced MRI. A median number of two clinical relapses/patient occurred of which a median of one was treated with steroids. A median of 1.59 new lesions/scan/patient was detected (range 0-8). The total number of new active lesions correlated significantly with study period relapses (SRCC = 0.72, P = 0.023). Computer simulations using the bootstrap technique yielded mostly lower power values for a parallel groups design than in previous studies except for short follow-periods in larger samples. In this-sample the open cross-over design was found to be between 20 and 40% more powerful. Results of power-calculations are clearly sample dependent implying that for treatment trial monitoring using MRI in relapsing-remitting MS conservative sample size estimates are to be used. In an active patient group open cross-over trial designs could be a very powerful alternative to parallel groups design.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Clinical Trials, Phase II as Topic
  • Female
  • Humans
  • Magnetic Resonance Imaging*
  • Male
  • Middle Aged
  • Multiple Sclerosis / diagnosis*
  • Multiple Sclerosis / physiopathology*
  • Recurrence
  • Research Design