Abstract
In cluster randomised trials, randomisation increases internal study validity. If enough clusters are randomised, an unadjusted analysis should be unbiased. If a smaller number of clusters are included, stratified or matched randomisation can increase comparability between trial arms. In addition, an adjusted analysis may be required; nevertheless, randomisation removes the possibility for systematically biased allocation and increases transparency. In stepped wedge trials, clusters are randomised to receive an intervention at different start times (‘steps’), and all clusters eventually receive it. In a recent study protocol for a ‘modified stepped wedge trial’, the investigators considered randomisation of the clusters (hospital wards), but decided against it for ethical and logistical reasons, and under the assumption that it would not add much to the rigour of the evaluation. We show that the benefits of randomisation for cluster randomised trials also apply to stepped wedge trials. The biggest additional issue for stepped wedge trials in relation to parallel cluster randomised trials is the need to control for secular trends in the outcome. Analysis of stepped wedge trials can in theory be based on ‘horizontal’ or ‘vertical’ comparisons. Horizontal comparisons are based on measurements taken before and after the intervention is introduced in each cluster, and are unbiased if there are no secular trends. Vertical comparisons are based on outcome measurements from clusters that have switched to the intervention condition and those from clusters that have yet to switch, and are unbiased under randomisation since at any time point, which clusters are in intervention and control conditions will have been determined at random. Secular outcome trends are a possibility in many settings. Many stepped wedge trials are analysed with a mixed model, including a random effect for cluster and fixed effects for time period to account for secular trends, thereby combining both vertical and horizontal comparisons of intervention and control clusters. The importance of randomisation in a stepped wedge trial is that the effects of time can be estimated from the data, and bias from secular trends that would otherwise arise can be controlled for, provided the trends are correctly specified in the model.
Highlights
Why is randomisation useful in stepped wedge trials? Randomisation brings several important benefits to cluster randomised controlled trials
The biggest additional issue for stepped wedge trials in relation to parallel cluster randomised trials is the need to control for secular trends in the outcome of interest
The authors obviously have excellent knowledge of the trial setting, but it seems plausible that the systematic allocation order of wards may prevent the unbiased estimation of any secular trends affecting all wards in the proposed analysis, and the intervention effect may be biased
Summary
Clusters are randomised to receive an intervention at different start times (‘steps’), and all clusters eventually receive it. The popularity of the design is increasing and debate about their use, design and analysis is ongoing [1,2,3]. This issue of Trials features a protocol for a study described as a ‘modified stepped wedge’ [4]. DiDiodato et al investigate whether an antimicrobial stewardship intervention involving prospective chart audit and feedback could reduce the length of stay in hospital for patients admitted with community-acquired pneumonia [4]. They plan to introduce the intervention in four hospital wards
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