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Including random centre effects in design, analysis and presentation of multi-centre trials
BACKGROUND: In large multicentre trials in diverse settings, there is uncertainty about the need to adjust for centre variation in design and analysis. A key distinction is the difference between variation in outcome (independent of treatment) and variation in treatment effect. Through re-analysis o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140487/ https://www.ncbi.nlm.nih.gov/pubmed/34022937 http://dx.doi.org/10.1186/s13063-021-05266-w |
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author | Edgar, Kate Roberts, Ian Sharples, Linda |
author_facet | Edgar, Kate Roberts, Ian Sharples, Linda |
author_sort | Edgar, Kate |
collection | PubMed |
description | BACKGROUND: In large multicentre trials in diverse settings, there is uncertainty about the need to adjust for centre variation in design and analysis. A key distinction is the difference between variation in outcome (independent of treatment) and variation in treatment effect. Through re-analysis of the CRASH-2 trial (2010), this study clarifies when and how to use multi-level models for multicentre studies with binary outcomes. METHODS: CRASH-2 randomised 20,127 trauma patients across 271 centres and 40 countries to either single-dose tranexamic acid or identical placebo, with all-cause death at 4 weeks the primary outcome. The trial data had a hierarchical structure, with patients nested in hospitals which in turn are nested within countries. Reanalysis of CRASH-2 trial data assessed treatment effect and both patient and centre level baseline covariates as fixed effects in logistic regression models. Random effects were included to assess where there was variation between countries, and between centres within countries, both in underlying risk of death and in treatment effect. RESULTS: In CRASH-2, there was significant variation between countries and between centres in death at 4 weeks, but absolutely no differences between countries or centres in the effect of treatment. Average treatment effect was not altered after accounting for centre and country variation in this study. CONCLUSIONS: It is important to distinguish between underlying variation in outcomes and variation in treatment effects; the former is common but the latter is not. Stratifying randomisation by centre overcomes many statistical problems and including random intercepts in analysis may increase power and decrease bias in mean and standard error estimates. TRIAL REGISTRATION: Current Controlled Trials ISRCTN86750102, ClinicalTrials.gov NCT00375258, and South African Clinical Trial Register DOH-27-0607-1919 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-021-05266-w. |
format | Online Article Text |
id | pubmed-8140487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81404872021-05-25 Including random centre effects in design, analysis and presentation of multi-centre trials Edgar, Kate Roberts, Ian Sharples, Linda Trials Methodology BACKGROUND: In large multicentre trials in diverse settings, there is uncertainty about the need to adjust for centre variation in design and analysis. A key distinction is the difference between variation in outcome (independent of treatment) and variation in treatment effect. Through re-analysis of the CRASH-2 trial (2010), this study clarifies when and how to use multi-level models for multicentre studies with binary outcomes. METHODS: CRASH-2 randomised 20,127 trauma patients across 271 centres and 40 countries to either single-dose tranexamic acid or identical placebo, with all-cause death at 4 weeks the primary outcome. The trial data had a hierarchical structure, with patients nested in hospitals which in turn are nested within countries. Reanalysis of CRASH-2 trial data assessed treatment effect and both patient and centre level baseline covariates as fixed effects in logistic regression models. Random effects were included to assess where there was variation between countries, and between centres within countries, both in underlying risk of death and in treatment effect. RESULTS: In CRASH-2, there was significant variation between countries and between centres in death at 4 weeks, but absolutely no differences between countries or centres in the effect of treatment. Average treatment effect was not altered after accounting for centre and country variation in this study. CONCLUSIONS: It is important to distinguish between underlying variation in outcomes and variation in treatment effects; the former is common but the latter is not. Stratifying randomisation by centre overcomes many statistical problems and including random intercepts in analysis may increase power and decrease bias in mean and standard error estimates. TRIAL REGISTRATION: Current Controlled Trials ISRCTN86750102, ClinicalTrials.gov NCT00375258, and South African Clinical Trial Register DOH-27-0607-1919 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-021-05266-w. BioMed Central 2021-05-22 /pmc/articles/PMC8140487/ /pubmed/34022937 http://dx.doi.org/10.1186/s13063-021-05266-w Text en © The Author(s) 2021 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 | Methodology Edgar, Kate Roberts, Ian Sharples, Linda Including random centre effects in design, analysis and presentation of multi-centre trials |
title | Including random centre effects in design, analysis and presentation of multi-centre trials |
title_full | Including random centre effects in design, analysis and presentation of multi-centre trials |
title_fullStr | Including random centre effects in design, analysis and presentation of multi-centre trials |
title_full_unstemmed | Including random centre effects in design, analysis and presentation of multi-centre trials |
title_short | Including random centre effects in design, analysis and presentation of multi-centre trials |
title_sort | including random centre effects in design, analysis and presentation of multi-centre trials |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140487/ https://www.ncbi.nlm.nih.gov/pubmed/34022937 http://dx.doi.org/10.1186/s13063-021-05266-w |
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