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Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes

BACKGROUND: In an individually randomised controlled trial where the treatment is delivered by a health professional it seems likely that the effectiveness of the treatment, independent of any treatment effect, could depend on the skill, training or even enthusiasm of the health professional deliver...

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Autores principales: Flight, Laura, Allison, Annabel, Dimairo, Munyaradzi, Lee, Ellen, Mandefield, Laura, Walters, Stephen J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5129671/
https://www.ncbi.nlm.nih.gov/pubmed/27899073
http://dx.doi.org/10.1186/s12874-016-0249-5
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author Flight, Laura
Allison, Annabel
Dimairo, Munyaradzi
Lee, Ellen
Mandefield, Laura
Walters, Stephen J.
author_facet Flight, Laura
Allison, Annabel
Dimairo, Munyaradzi
Lee, Ellen
Mandefield, Laura
Walters, Stephen J.
author_sort Flight, Laura
collection PubMed
description BACKGROUND: In an individually randomised controlled trial where the treatment is delivered by a health professional it seems likely that the effectiveness of the treatment, independent of any treatment effect, could depend on the skill, training or even enthusiasm of the health professional delivering it. This may then lead to a potential clustering of the outcomes for patients treated by the same health professional, but similar clustering may not occur in the control arm. Using four case studies, we aim to provide practical guidance and recommendations for the analysis of trials with some element of clustering in one arm. METHODS: Five approaches to the analysis of outcomes from an individually randomised controlled trial with clustering in one arm are identified in the literature. Some of these methods are applied to four case studies of completed randomised controlled trials with clustering in one arm with sample sizes ranging from 56 to 539. Results are obtained using the statistical packages R and Stata and summarised using a forest plot. RESULTS: The intra-cluster correlation coefficient (ICC) for each of the case studies was small (<0.05) indicating little dependence on the outcomes related to cluster allocations. All models fitted produced similar results, including the simplest approach of ignoring clustering for the case studies considered. CONCLUSIONS: A partially clustered approach, modelling the clustering in just one arm, most accurately represents the trial design and provides valid results. Modelling homogeneous variances between the clustered and unclustered arm is adequate in scenarios similar to the case studies considered. We recommend treating each participant in the unclustered arm as a single cluster. This approach is simple to implement in R and Stata and is recommended for the analysis of trials with clustering in one arm only. However, the case studies considered had small ICC values, limiting the generalisability of these results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-016-0249-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-51296712016-12-12 Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes Flight, Laura Allison, Annabel Dimairo, Munyaradzi Lee, Ellen Mandefield, Laura Walters, Stephen J. BMC Med Res Methodol Research Article BACKGROUND: In an individually randomised controlled trial where the treatment is delivered by a health professional it seems likely that the effectiveness of the treatment, independent of any treatment effect, could depend on the skill, training or even enthusiasm of the health professional delivering it. This may then lead to a potential clustering of the outcomes for patients treated by the same health professional, but similar clustering may not occur in the control arm. Using four case studies, we aim to provide practical guidance and recommendations for the analysis of trials with some element of clustering in one arm. METHODS: Five approaches to the analysis of outcomes from an individually randomised controlled trial with clustering in one arm are identified in the literature. Some of these methods are applied to four case studies of completed randomised controlled trials with clustering in one arm with sample sizes ranging from 56 to 539. Results are obtained using the statistical packages R and Stata and summarised using a forest plot. RESULTS: The intra-cluster correlation coefficient (ICC) for each of the case studies was small (<0.05) indicating little dependence on the outcomes related to cluster allocations. All models fitted produced similar results, including the simplest approach of ignoring clustering for the case studies considered. CONCLUSIONS: A partially clustered approach, modelling the clustering in just one arm, most accurately represents the trial design and provides valid results. Modelling homogeneous variances between the clustered and unclustered arm is adequate in scenarios similar to the case studies considered. We recommend treating each participant in the unclustered arm as a single cluster. This approach is simple to implement in R and Stata and is recommended for the analysis of trials with clustering in one arm only. However, the case studies considered had small ICC values, limiting the generalisability of these results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-016-0249-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-11-29 /pmc/articles/PMC5129671/ /pubmed/27899073 http://dx.doi.org/10.1186/s12874-016-0249-5 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Flight, Laura
Allison, Annabel
Dimairo, Munyaradzi
Lee, Ellen
Mandefield, Laura
Walters, Stephen J.
Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes
title Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes
title_full Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes
title_fullStr Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes
title_full_unstemmed Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes
title_short Recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes
title_sort recommendations for the analysis of individually randomised controlled trials with clustering in one arm – a case of continuous outcomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5129671/
https://www.ncbi.nlm.nih.gov/pubmed/27899073
http://dx.doi.org/10.1186/s12874-016-0249-5
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