|Title||MRI-based clinical trials in relapsing-remitting multiple sclerosis: new sample size calculations based on a longitudinal model|
|Publication Type||Journal Article|
|Year of Publication||2012|
|Authors||Altman, RM, Petkau, AJ, Vrecko, D, Smith, A|
|Journal||Multiple Sclerosis Journal|
|Keywords||Brain, Chi-Square Distribution, Computer Simulation, Controlled Clinical Trials as Topic, Endpoint Determination, Humans, Longitudinal Studies, magnetic resonance imaging, Models, multiple sclerosis, Predictive Value of Tests, Relapsing-Remitting, Sample Size, Statistical, Time Factors, Treatment Outcome|
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.