Taljaard Monica, Teerenstra Steven, Ivers Noah M, Fergusson Dean A
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, ON, Canada
Section Biostatistics, Department for Health Evidence, Radboud Institute for Health Science, Radboud University Medical Center, Nijmegen, The Netherlands.
Clin Trials. 2016 Aug;13(4):459-63. doi: 10.1177/1740774516634316. Epub 2016 Mar 3.
Given the growing attention to quality improvement, comparative effectiveness research, and pragmatic trials embedded within learning health systems, the use of the cluster randomization design is bound to increase. The number of clusters available for randomization is often limited in such trials. Designs that incorporate pre-intervention measurements (e.g. cluster cross-over, repeated parallel arm, and stepped wedge designs) can substantially reduce the required numbers of clusters by decreasing between-cluster sources of variation. However, there are substantial risks associated with few clusters, including increased probability of chance imbalances and type I and type II error, limited perceived or actual generalizability, and fewer options for statistical analysis. Furthermore, current sample size methods for the stepped wedge design make a strong underlying assumption with respect to the correlation structure-in particular, that the intracluster and inter-period correlations are equal. This is in contrast with methods for the cluster cross-over design that explicitly allow for a smaller inter-period correlation. Failing to similarly allow for the inter-period correlation in the design of a stepped wedge trial may yield perilously low sample sizes. Further methodological and empirical work is required to inform sample size methods and guidance for the stepped wedge trial and to provide minimum thresholds for this design.
鉴于对质量改进、比较效果研究以及学习型卫生系统中嵌入的务实试验的关注度不断提高，整群随机化设计的使用必然会增加。在这类试验中，可供随机化的群组数量往往有限。纳入干预前测量的设计（如群组交叉、重复平行组和阶梯楔形设计）可以通过减少群组间变异来源，大幅减少所需的群组数量。然而，群组数量较少会带来重大风险，包括机会失衡以及I型和II型错误的概率增加、可感知的或实际的可推广性有限，以及统计分析的选项较少。此外，当前阶梯楔形设计的样本量方法对相关结构做出了一个很强的潜在假设，特别是群组内和周期间的相关性相等。这与群组交叉设计的方法形成对比，后者明确允许周期间相关性较小。在阶梯楔形试验设计中未能同样考虑周期间相关性可能会导致样本量低得危险。需要进一步开展方法学和实证研究，为阶梯楔形试验的样本量方法和指导提供依据，并为该设计提供最低阈值。
