Department of Psychiatry, University of Rostock, Rostock, Germany.
World J Biol Psychiatry. 2011 Sep;12 Suppl 1:109-13. doi: 10.3109/15622975.2011.603222.
Structural MRI markers may serve as surrogate endpoints in clinical trials on disease modification in Alzheimer's disease (AD). Here, we used a longitudinal MRI data set of total brain and cortical grey matter volumes from 66 patients with AD recruited across seven centres of the German Dementia Competence Network. We compared effect size estimates for the detection of a 25% reduction of atrophy progression between a priori segmentation of brain tissue, implementing an anatomical model of brain tissue distribution, and a posteriori segmentation that was not informed by an anatomical model. Additionally, we compared effect size estimates between fixed effects analysis and a mixed effects model, implementing a random effects term to account for variable spacing of observation times. A priori segmentation reduced the required sample size by 50%. Introducing a random effects term for time led to an additional 50% reduction of required samples sizes compared to fixed effects analysis. In summary, using a priori segmentation with mixed effects analysis reduced the sample size to detect clinically relevant treatment effects more than fourfold. The implementation of mixed effects models will enhance the power to detect treatment effects also with other classes of biological endpoints including molecular biomarkers of disease.
结构 MRI 标志物可用作阿尔茨海默病（AD）疾病修饰临床试验中的替代终点。在这里，我们使用了来自德国痴呆症网络七个中心的 66 名 AD 患者的纵向 MRI 数据集，包括总脑和皮质灰质体积。我们比较了在预先分割脑组织、实施脑组织分布解剖模型和不依赖解剖模型的事后分割之间检测萎缩进展减少 25%的效果大小估计值。此外，我们还比较了固定效应分析和混合效应模型之间的效果大小估计值，通过引入随机效应项来解释观察时间间隔的变化。预先分割将所需样本量减少了 50%。与固定效应分析相比，引入用于时间的随机效应项将所需样本量进一步减少了 50%。总之，使用具有混合效应分析的预先分割将检测临床相关治疗效果的样本量减少了四倍以上。混合效应模型的实施将提高检测治疗效果的能力，包括疾病的其他类别的生物学终点，如分子生物标志物。
