Consort 2010 statement: extension to cluster randomised trials

Consort 2010 statement: extension to cluster randomised trials

Published 4 September 2012 | Marion K Campbell director1, Gilda Piaggio honorary professor2, Diana R Elbourne professor of healthcare evaluation2, Douglas G Altman director3, for the CONSORT Group
The paper discusses the extension of the Consolidated Standards of Reporting Trials (CONSORT) statement to cluster randomized trials, focusing on the 2010 revision of the CONSORT statement and the 2008 extension for abstracts. Cluster randomized trials involve randomizing groups of people (clusters) rather than individuals, which can be more feasible and reduce contamination risks. The updated CONSORT statement includes a 25-item checklist, simplified and clarified to better reflect the complexity of cluster trials. Key changes include explicit guidance on defining clusters, accounting for intraclass correlations, and detailing the randomization process. The paper also highlights the importance of reporting the rationale for using a cluster design, the level of inference, and the methods used to minimize selection bias. Examples and explanations are provided to illustrate the application of these guidelines in various contexts, emphasizing the need for detailed and transparent reporting to ensure valid analysis and interpretation of cluster randomized trials.The paper discusses the extension of the Consolidated Standards of Reporting Trials (CONSORT) statement to cluster randomized trials, focusing on the 2010 revision of the CONSORT statement and the 2008 extension for abstracts. Cluster randomized trials involve randomizing groups of people (clusters) rather than individuals, which can be more feasible and reduce contamination risks. The updated CONSORT statement includes a 25-item checklist, simplified and clarified to better reflect the complexity of cluster trials. Key changes include explicit guidance on defining clusters, accounting for intraclass correlations, and detailing the randomization process. The paper also highlights the importance of reporting the rationale for using a cluster design, the level of inference, and the methods used to minimize selection bias. Examples and explanations are provided to illustrate the application of these guidelines in various contexts, emphasizing the need for detailed and transparent reporting to ensure valid analysis and interpretation of cluster randomized trials.
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