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Assessing potential sources of clustering in individually randomised trials

BACKGROUND: Recent reviews have shown that while clustering is extremely common in individually randomised trials (for example, clustering within centre, therapist, or surgeon), it is rarely accounted for in the trial analysis. Our aim is to develop a general framework for assessing whether potentia...

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Autores principales: Kahan, Brennan C, Morris, Tim P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3643875/
https://www.ncbi.nlm.nih.gov/pubmed/23590245
http://dx.doi.org/10.1186/1471-2288-13-58
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author Kahan, Brennan C
Morris, Tim P
author_facet Kahan, Brennan C
Morris, Tim P
author_sort Kahan, Brennan C
collection PubMed
description BACKGROUND: Recent reviews have shown that while clustering is extremely common in individually randomised trials (for example, clustering within centre, therapist, or surgeon), it is rarely accounted for in the trial analysis. Our aim is to develop a general framework for assessing whether potential sources of clustering must be accounted for in the trial analysis to obtain valid type I error rates (non-ignorable clustering), with a particular focus on individually randomised trials. METHODS: A general framework for assessing clustering is developed based on theoretical results and a case study of a recently published trial is used to illustrate the concepts. A simulation study is used to explore the impact of not accounting for non-ignorable clustering in practice. RESULTS: Clustering is non-ignorable when there is both correlation between patient outcomes within clusters, and correlation between treatment assignments within clusters. This occurs when the intraclass correlation coefficient is non-zero, and when the cluster has been used in the randomisation process (e.g. stratified blocks within centre) or when patients are assigned to clusters after randomisation with different probabilities (e.g. a surgery trial in which surgeons treat patients in only one arm). A case study of an individually randomised trial found multiple sources of clustering, including centre of recruitment, attending surgeon, and site of rehabilitation class. Simulations show that failure to account for non-ignorable clustering in trial analyses can lead to type I error rates over 20% in certain cases; conversely, adjusting for the clustering in the trial analysis gave correct type I error rates. CONCLUSIONS: Clustering is common in individually randomised trials. Trialists should assess potential sources of clustering during the planning stages of a trial, and account for any sources of non-ignorable clustering in the trial analysis.
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spelling pubmed-36438752013-05-09 Assessing potential sources of clustering in individually randomised trials Kahan, Brennan C Morris, Tim P BMC Med Res Methodol Research Article BACKGROUND: Recent reviews have shown that while clustering is extremely common in individually randomised trials (for example, clustering within centre, therapist, or surgeon), it is rarely accounted for in the trial analysis. Our aim is to develop a general framework for assessing whether potential sources of clustering must be accounted for in the trial analysis to obtain valid type I error rates (non-ignorable clustering), with a particular focus on individually randomised trials. METHODS: A general framework for assessing clustering is developed based on theoretical results and a case study of a recently published trial is used to illustrate the concepts. A simulation study is used to explore the impact of not accounting for non-ignorable clustering in practice. RESULTS: Clustering is non-ignorable when there is both correlation between patient outcomes within clusters, and correlation between treatment assignments within clusters. This occurs when the intraclass correlation coefficient is non-zero, and when the cluster has been used in the randomisation process (e.g. stratified blocks within centre) or when patients are assigned to clusters after randomisation with different probabilities (e.g. a surgery trial in which surgeons treat patients in only one arm). A case study of an individually randomised trial found multiple sources of clustering, including centre of recruitment, attending surgeon, and site of rehabilitation class. Simulations show that failure to account for non-ignorable clustering in trial analyses can lead to type I error rates over 20% in certain cases; conversely, adjusting for the clustering in the trial analysis gave correct type I error rates. CONCLUSIONS: Clustering is common in individually randomised trials. Trialists should assess potential sources of clustering during the planning stages of a trial, and account for any sources of non-ignorable clustering in the trial analysis. BioMed Central 2013-04-16 /pmc/articles/PMC3643875/ /pubmed/23590245 http://dx.doi.org/10.1186/1471-2288-13-58 Text en Copyright © 2013 Kahan and Morris; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Kahan, Brennan C
Morris, Tim P
Assessing potential sources of clustering in individually randomised trials
title Assessing potential sources of clustering in individually randomised trials
title_full Assessing potential sources of clustering in individually randomised trials
title_fullStr Assessing potential sources of clustering in individually randomised trials
title_full_unstemmed Assessing potential sources of clustering in individually randomised trials
title_short Assessing potential sources of clustering in individually randomised trials
title_sort assessing potential sources of clustering in individually randomised trials
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3643875/
https://www.ncbi.nlm.nih.gov/pubmed/23590245
http://dx.doi.org/10.1186/1471-2288-13-58
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