Allocation techniques for balance at baseline in cluster randomized trials: a methodological review

Noah M Ivers, Ilana J Halperin, Jan Barnsley, Jeremy M Grimshaw, Baiju R Shah, Karen Tu, Ross Upshur, Merrick Zwarenstein, Noah M Ivers, Ilana J Halperin, Jan Barnsley, Jeremy M Grimshaw, Baiju R Shah, Karen Tu, Ross Upshur, Merrick Zwarenstein

Abstract

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.

Figures

Figure 1
Figure 1
Questions to ask and potential answers when trialists and statisticians work together to consider allocation techniques for balancing covariates in cluster-trials.aOne would expect that in most trials access to some relevant data would become accessible immediately after recruitment and prior to allocation. bOnly use matching if confident in ability to achieve a good match

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