Clinical Trials

Clinical Trials: A Practical Guide ■❚❙❘Table 1. Why use cluster randomization?• To evaluate health care interventions in practices, hospitals, regions, or communities• Patients in one cluster are more likely to have similar outcomes• To eliminate contamination of the intervention effects between patients within a clusterTable 2. Potential units of randomization in cluster randomized trials.• Groups of individuals chosen by a specific link (eg, geographic location)• Primary care practices• Hospitals• CommunitiesNote: Intervention is usually applied at the cluster level.It is important to ensure that enough similar hospitals exist to enable balance whenrandomized as a cluster; the size of each cluster must also be similar (eg, 20 patientsrecruited at each hospital). Randomizing by cluster must now be accounted for inthe design, analysis, and reporting of a trial, since the lack of independencebetween patients in a CRT has important statistical implications [4].Selection biasIn conventional trials, selection bias can be minimized by the randomizedallocation of individual subjects [5]. However, trials in cluster settings are proneto contamination effects due to correlations among individuals within clusters inthe trial – eg, patients attending an affluent hospital are more likely to becompliant and to report side-effects.This bias can be partially offset by using each cluster as a unit of randomization(rather than the individual subject), providing enough similar clusters can beidentified. However, CRTs are less efficient than conventional trials since thenumber of clusters randomized is smaller than when randomizing at the individualpatient level. This can generate a trade-off between an individual randomized trialand a CRT [6]. For example, in studies at the primary care level that randomizephysicians of a practice as the unit of clustering – rather than as individualphysicians – the sample size, interpretation, and analysis can all be affected [7–9].ConfoundingAs in a simple randomized trial, the effect of a treatment in CRTs can beinfluenced by the presence of possible confounding factors due to imbalances inthe baseline characteristics of patients (or covariates) between treatment groups(see Chapter 25).143