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Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology

INTRODUCTION: Clinical trial designs based on the assumption of independent observations are well established. Clustered clinical trial designs, where all observational units belong to a cluster and outcomes within clusters are expected to be correlated, have also received considerable attention. Ho...

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Autores principales: Lange, Kylie M, Kasza, Jessica, Sullivan, Thomas R, Yelland, Lisa N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021130/
https://www.ncbi.nlm.nih.gov/pubmed/36628406
http://dx.doi.org/10.1177/17407745221146987
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author Lange, Kylie M
Kasza, Jessica
Sullivan, Thomas R
Yelland, Lisa N
author_facet Lange, Kylie M
Kasza, Jessica
Sullivan, Thomas R
Yelland, Lisa N
author_sort Lange, Kylie M
collection PubMed
description INTRODUCTION: Clinical trial designs based on the assumption of independent observations are well established. Clustered clinical trial designs, where all observational units belong to a cluster and outcomes within clusters are expected to be correlated, have also received considerable attention. However, many clinical trials involve partially clustered data, where only some observational units belong to a cluster. Examples of such trials occur in neonatology, where participants include infants from both singleton and multiple births, and ophthalmology, where one or two eyes per participant may need treatment. Partial clustering can also arise in trials of group-based treatments (e.g. group education or counselling sessions) or treatments administered individually by a discrete number of health care professionals (e.g. surgeons or physical therapists), when this is compared to an unclustered control arm. Trials involving partially clustered data have received limited attention in the literature and the current lack of standardised terminology may be hampering the development and dissemination of methods for designing and analysing these trials. METHODS AND EXAMPLES: In this article, we present an overarching definition of partially clustered trials, bringing together several existing trial designs including those for group-based treatments, clustering due to facilitator effects and the re-randomisation design. We define and describe four types of partially clustered trial designs, characterised by whether the clustering occurs pre-randomisation or post-randomisation and, in the case of pre-randomisation clustering, by the method of randomisation that is used for the clustered observations (individual randomisation, cluster randomisation or balanced randomisation within clusters). Real life examples are provided to highlight the occurrence of partially clustered trials across a variety of fields. To assess how partially clustered trials are currently reported, we review published reports of partially clustered trials. DISCUSSION: Our findings demonstrate that the description of these trials is often incomplete and the terminology used to describe the trial designs is inconsistent, restricting the ability to identify these trials in the literature. By adopting the definitions and terminology presented in this article, the reporting of partially clustered trials can be substantially improved, and we present several recommendations for reporting these trial designs in practice. Greater awareness of partially clustered trials will facilitate more methodological research into their design and analysis, ultimately improving the quality of these trials.
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spelling pubmed-100211302023-03-18 Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology Lange, Kylie M Kasza, Jessica Sullivan, Thomas R Yelland, Lisa N Clin Trials Articles INTRODUCTION: Clinical trial designs based on the assumption of independent observations are well established. Clustered clinical trial designs, where all observational units belong to a cluster and outcomes within clusters are expected to be correlated, have also received considerable attention. However, many clinical trials involve partially clustered data, where only some observational units belong to a cluster. Examples of such trials occur in neonatology, where participants include infants from both singleton and multiple births, and ophthalmology, where one or two eyes per participant may need treatment. Partial clustering can also arise in trials of group-based treatments (e.g. group education or counselling sessions) or treatments administered individually by a discrete number of health care professionals (e.g. surgeons or physical therapists), when this is compared to an unclustered control arm. Trials involving partially clustered data have received limited attention in the literature and the current lack of standardised terminology may be hampering the development and dissemination of methods for designing and analysing these trials. METHODS AND EXAMPLES: In this article, we present an overarching definition of partially clustered trials, bringing together several existing trial designs including those for group-based treatments, clustering due to facilitator effects and the re-randomisation design. We define and describe four types of partially clustered trial designs, characterised by whether the clustering occurs pre-randomisation or post-randomisation and, in the case of pre-randomisation clustering, by the method of randomisation that is used for the clustered observations (individual randomisation, cluster randomisation or balanced randomisation within clusters). Real life examples are provided to highlight the occurrence of partially clustered trials across a variety of fields. To assess how partially clustered trials are currently reported, we review published reports of partially clustered trials. DISCUSSION: Our findings demonstrate that the description of these trials is often incomplete and the terminology used to describe the trial designs is inconsistent, restricting the ability to identify these trials in the literature. By adopting the definitions and terminology presented in this article, the reporting of partially clustered trials can be substantially improved, and we present several recommendations for reporting these trial designs in practice. Greater awareness of partially clustered trials will facilitate more methodological research into their design and analysis, ultimately improving the quality of these trials. SAGE Publications 2023-01-10 2023-04 /pmc/articles/PMC10021130/ /pubmed/36628406 http://dx.doi.org/10.1177/17407745221146987 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Articles
Lange, Kylie M
Kasza, Jessica
Sullivan, Thomas R
Yelland, Lisa N
Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology
title Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology
title_full Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology
title_fullStr Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology
title_full_unstemmed Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology
title_short Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology
title_sort partially clustered designs for clinical trials: unifying existing designs using consistent terminology
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021130/
https://www.ncbi.nlm.nih.gov/pubmed/36628406
http://dx.doi.org/10.1177/17407745221146987
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