Altman R M, Petkau A J, Vrecko D, Smith A
Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC, Canada.
Mult Scler. 2012 Nov;18(11):1600-8. doi: 10.1177/1352458512444326. Epub 2012 Apr 11.
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.
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.
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.
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.
Sample sizes based on the longitudinal model are more realistic and often smaller than those previously reported using the NB model.
在多发性硬化症（MS）中，基于磁共振成像（MRI）的临床试验样本量通常假定病灶计数可以通过负二项分布（NB）模型合理描述。
本研究旨在评估NB模型对病灶计数数据的适用性，并使用更现实的模型为复发缓解型MS的安慰剂对照MRI临床试验提供样本量。
使用Pearson卡方统计量评估NB模型在五项MS临床试验各臂中的拟合情况。通过模拟来自一个新的纵向模型的数据来估计与各种治疗效果测试相关的所需样本量，该纵向模型用于个体患者的重复病灶计数数据。
在五项试验中的四项试验的至少一个臂中发现了反对NB模型的证据（p < 0.05）。如果使用该模型设计试验，但所得临床数据不符合其假设，那么该试验在评估平均病灶计数差异时可能严重缺乏效力。
基于纵向模型的样本量更现实，且通常比之前使用NB模型报告的样本量小。
