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Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance

BACKGROUND: The complexities associated with delivering randomised surgical trials, such as clustering effects, by centre or surgeon, and surgical learning, are well known. Despite this, approaches used to manage these complexities, and opinions on these, vary. Guidance documents have been developed...

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Autores principales: Conroy, Elizabeth J., Blazeby, Jane M., Burnside, Girvan, Cook, Jonathan A., Gamble, Carrol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552436/
https://www.ncbi.nlm.nih.gov/pubmed/36221107
http://dx.doi.org/10.1186/s13063-022-06743-6
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author Conroy, Elizabeth J.
Blazeby, Jane M.
Burnside, Girvan
Cook, Jonathan A.
Gamble, Carrol
author_facet Conroy, Elizabeth J.
Blazeby, Jane M.
Burnside, Girvan
Cook, Jonathan A.
Gamble, Carrol
author_sort Conroy, Elizabeth J.
collection PubMed
description BACKGROUND: The complexities associated with delivering randomised surgical trials, such as clustering effects, by centre or surgeon, and surgical learning, are well known. Despite this, approaches used to manage these complexities, and opinions on these, vary. Guidance documents have been developed to support clinical trial design and reporting. This work aimed to identify and examine existing guidance and consider its relevance to clustering effects and learning curves within surgical trials. METHODS: A review of existing guidelines, developed to inform the design and analysis of randomised controlled trials, is undertaken. Guidelines were identified using an electronic search, within the Equator Network, and by a targeted search of those endorsed by leading UK funding bodies, regulators, and medical journals. Eligible documents were compared against pre-specified key criteria to identify gaps or inconsistencies in recommendations. RESULTS: Twenty-eight documents were eligible (12 Equator Network; 16 targeted search). Twice the number of guidance documents targeted design (n/N=20/28, 71%) than analysis (n/N=10/28, 36%). Managing clustering by centre through design was well documented. Clustering by surgeon had less coverage and contained some inconsistencies. Managing the surgical learning curve, or changes in delivery over time, through design was contained within several documents (n/N=8/28, 29%), of which one provided guidance on reporting this and restricted to early phase studies only. Methods to analyse clustering effects and learning were provided in five and four documents respectively (N=28). CONCLUSIONS: To our knowledge, this is the first review as to the extent to which existing guidance for designing and analysing randomised surgical trials covers the management of clustering, by centre or surgeon, and the surgical learning curve. Twice the number of identified documents targeted design aspects than analysis. Most notably, no single document exists for use when designing these studies, which may lead to inconsistencies in practice. The development of a single document, with agreed principles to guide trial design and analysis across a range of realistic clinical scenarios, is needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-022-06743-6.
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spelling pubmed-95524362022-10-12 Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance Conroy, Elizabeth J. Blazeby, Jane M. Burnside, Girvan Cook, Jonathan A. Gamble, Carrol Trials Research BACKGROUND: The complexities associated with delivering randomised surgical trials, such as clustering effects, by centre or surgeon, and surgical learning, are well known. Despite this, approaches used to manage these complexities, and opinions on these, vary. Guidance documents have been developed to support clinical trial design and reporting. This work aimed to identify and examine existing guidance and consider its relevance to clustering effects and learning curves within surgical trials. METHODS: A review of existing guidelines, developed to inform the design and analysis of randomised controlled trials, is undertaken. Guidelines were identified using an electronic search, within the Equator Network, and by a targeted search of those endorsed by leading UK funding bodies, regulators, and medical journals. Eligible documents were compared against pre-specified key criteria to identify gaps or inconsistencies in recommendations. RESULTS: Twenty-eight documents were eligible (12 Equator Network; 16 targeted search). Twice the number of guidance documents targeted design (n/N=20/28, 71%) than analysis (n/N=10/28, 36%). Managing clustering by centre through design was well documented. Clustering by surgeon had less coverage and contained some inconsistencies. Managing the surgical learning curve, or changes in delivery over time, through design was contained within several documents (n/N=8/28, 29%), of which one provided guidance on reporting this and restricted to early phase studies only. Methods to analyse clustering effects and learning were provided in five and four documents respectively (N=28). CONCLUSIONS: To our knowledge, this is the first review as to the extent to which existing guidance for designing and analysing randomised surgical trials covers the management of clustering, by centre or surgeon, and the surgical learning curve. Twice the number of identified documents targeted design aspects than analysis. Most notably, no single document exists for use when designing these studies, which may lead to inconsistencies in practice. The development of a single document, with agreed principles to guide trial design and analysis across a range of realistic clinical scenarios, is needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-022-06743-6. BioMed Central 2022-10-11 /pmc/articles/PMC9552436/ /pubmed/36221107 http://dx.doi.org/10.1186/s13063-022-06743-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Conroy, Elizabeth J.
Blazeby, Jane M.
Burnside, Girvan
Cook, Jonathan A.
Gamble, Carrol
Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance
title Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance
title_full Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance
title_fullStr Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance
title_full_unstemmed Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance
title_short Managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance
title_sort managing clustering effects and learning effects in the design and analysis of randomised surgical trials: a review of existing guidance
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552436/
https://www.ncbi.nlm.nih.gov/pubmed/36221107
http://dx.doi.org/10.1186/s13063-022-06743-6
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