Clinical Trials

❘❙❚■ Chapter 15 | Cluster Randomized TrialsIt has been argued that the results of CRTs are more subjective to imbalanceat baseline than simple randomized trials, as it can be impossible to know theclusters well enough to be able to assure an adequate balance of clusters to eachtreatment arm. For example, one cluster might have a heavy bias toward ethnicminority individuals or older patients. Therefore, proper randomization schemesshould be implemented in order to minimize the possible confounding effect onthe outcome variables.ExampleThe PROMIS (Prospective Registry of Outcomes and Management in AcuteIschaemic Syndromes)-UK study illustrates the use of CRT design in an ongoingstudy [10]. In this trial, the strategy under investigation is a guideline adherenceeducational program on enhancing the use of evidence-based treatments (aspirin,heparin, beta-blockers, clopidogrel, and statins) to improve the outcomes of patientsadmitted with acute coronary syndromes. Individual centers are either randomizedto the education program or not.The primary outcome is defined as a composite score of all five treatments beingprescribed during the in-hospital phase (1 point for each treatment on a patient,with a range from 0 to 5). In this CRT, the primary objective is to compare thecomposite score for the five evidence-based treatments between the educationgroup and the control group.Since it is likely that many of the same health professionals will look after differentpatients within a hospital entering the study, the patients cannot be treated ashaving independent outcomes on an individual basis – hence, the choice ofa CRT design is justified. To control for possible confounding, the investigatorshave employed a stratified randomization scheme. This aims to achieve abalanced distribution of hospitals between two treatment groups with regard togeographic distribution, teaching hospital status, and whether a hospital has thefacilities to perform invasive therapies for an acute coronary syndrome, since suchhospitals are more likely to also use more drug interventions.Impact of clustering on sample sizeIn CRTs, statistical power is greatly reduced in comparison with a similarly sizedindividually randomized trial due to randomizing by cluster – therefore, thesample size calculations need to be inflated, using a cluster inflation factor toaccommodate for the clustering.144