Family Practice Health Centre, Women's College Hospital, 76 Grenville Street, Toronto, ON, M5S1B2, Canada.
Trials. 2012 Aug 1;13:120. doi: 10.1186/1745-6215-13-120.
Reviews have repeatedly noted important methodological issues in the conduct and reporting of cluster randomized controlled trials (C-RCTs). These reviews usually focus on whether the intracluster correlation was explicitly considered in the design and analysis of the C-RCT. However, another important aspect requiring special attention in C-RCTs is the risk for imbalance of covariates at baseline. Imbalance of important covariates at baseline decreases statistical power and precision of the results. Imbalance also reduces face validity and credibility of the trial results. The risk of imbalance is elevated in C-RCTs compared to trials randomizing individuals because of the difficulties in recruiting clusters and the nested nature of correlated patient-level data. A variety of restricted randomization methods have been proposed as way to minimize risk of imbalance. However, there is little guidance regarding how to best restrict randomization for any given C-RCT. The advantages and limitations of different allocation techniques, including stratification, matching, minimization, and covariate-constrained randomization are reviewed as they pertain to C-RCTs to provide investigators with guidance for choosing the best allocation technique for their trial.
综述反复指出了群组随机对照试验（C-RCT）实施和报告中重要的方法学问题。这些综述通常集中于在 C-RCT 的设计和分析中是否明确考虑了组内相关性。然而，在 C-RCT 中需要特别注意的另一个重要方面是基线时协变量不均衡的风险。基线时重要协变量的不均衡会降低结果的统计效力和精度。不均衡还会降低试验结果的表面有效性和可信度。与个体随机化试验相比，由于招募群组的困难和相关患者水平数据的嵌套性质，C-RCT 中不均衡的风险更高。已经提出了各种限制随机化方法来最小化不均衡的风险。然而，对于任何给定的 C-RCT，如何最好地限制随机化，几乎没有指导。本文综述了不同分配技术的优缺点，包括分层、匹配、最小化和协变量约束随机化，因为它们与 C-RCT 相关，为研究者在选择适合其试验的最佳分配技术时提供指导。
