MRI-based clinical trials in relapsing–remitting MS: new sample size calculations based on a longitudinal model

Abstract

Background:

Sample sizes for magnetic resonance imaging (MRI)-based clinical trials in multiple sclerosis (MS) generally assume that lesion counts are reasonably described by the negative binomial (NB) model.

Objective:

This study aimed to assess the appropriateness of the NB model for lesion count data and to provide sample sizes for placebo-controlled, MRI-based clinical trials in relapsing–remitting MS using a more realistic model.

Methods:

The fit of the NB model in each arm of five MS clinical trials was assessed using Pearson’s chi-squared statistic. Required sample sizes associated with various tests of treatment effect were estimated by simulating data from a new, longitudinal model for repeated lesion count data on individual patients.

Results:

Evidence (p < 0.05) against the NB model was found in at least one arm of four of the five trials. If a trial is designed using this model but the resulting clinical data do not follow its assumptions then this trial can be seriously under-powered for assessing differences in mean lesion counts.

Conclusion:

Sample sizes based on the longitudinal model are more realistic and often smaller than those previously reported using the NB model.