Changing cluster composition in cluster randomised controlled trials: design and analysis considerations.

Neil Corrigan,Karen L Smith,Laura J Gray,Michael J G Bankart

doi:10.1186/1745-6215-15-184

Neil Corrigan, Karen L Smith + Show 2 more

Open Access

https://doi.org/10.1186/1745-6215-15-184

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Abstract

BackgroundThere are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. To illustrate this, we focus on the issue of cluster merging, considering the impact on the design, analysis and interpretation of trial outcomes.MethodsWe explored the effects of merging clusters on study power using standard methods of power calculation. We assessed the potential impacts on study findings of both homogeneous cluster merges (involving clusters randomised to the same arm of a trial) and heterogeneous merges (involving clusters randomised to different arms of a trial) by simulation. To determine the impact on bias and precision of treatment effect estimates, we applied standard methods of analysis to different populations under analysis.ResultsCluster merging produced a systematic reduction in study power. This effect depended on the number of merges and was most pronounced when variability in cluster size was at its greatest. Simulations demonstrate that the impact on analysis was minimal when cluster merges were homogeneous, with impact on study power being balanced by a change in observed intracluster correlation coefficient (ICC). We found a decrease in study power when cluster merges were heterogeneous, and the estimate of treatment effect was attenuated.ConclusionsExamples of cluster merges found in previously published reports of cluster randomised trials were typically homogeneous rather than heterogeneous. Simulations demonstrated that trial findings in such cases would be unbiased. However, simulations also showed that any heterogeneous cluster merges would introduce bias that would be hard to quantify, as well as having negative impacts on the precision of estimates obtained. Further methodological development is warranted to better determine how to analyse such trials appropriately. Interim recommendations include avoidance of cluster merges where possible, discontinuation of clusters following heterogeneous merges, allowance for potential loss of clusters and additional variability in cluster size in the original sample size calculation, and use of appropriate ICC estimates that reflect cluster size.

Highlights

There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition
Using a MEDLINE search, we identified reports of completed cluster Randomised controlled trial (RCT) in primary care published between 2004 and June 2012, with the start date chosen because 2004 was the year of publication of the Consolidated Standards of Reporting Trials (CONSORT) extension for cluster RCTs [5], which require descriptions of the flow of participants and clusters
We have demonstrated, through established approaches to power calculation, that cluster merges have an adverse impact on study power, assuming that the intracluster correlation coefficient (ICC) is unaffected by the change in average cluster size and variability in cluster size

Summary

Introduction

There are many methodological challenges in the conduct and analysis of cluster randomised controlled trials, but one that has received little attention is that of post-randomisation changes to cluster composition. The cluster design is often used when an intervention can be administered only to a group, such as a service-wide change or a public health campaign; when there is a risk that an intervention will affect participants in the nonintervention arm; or for reasons of cost or convenience. Such RCTs have a number of methodological challenges in their design, conduct and analysis, discussions of which can be found in a number of texts [1,2]. There was a 9% decrease in the number of GP practices between 1997 and 2007 [3], and organisational changes to meet the challenges of patient care have been actively encouraged [4]

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