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.

Keywords

multiple sclerosis magnetic resonance imaging clinical trials as topic sample size longitudinal studies statistical models research design

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