Cargando…

Ideal vs. real: a systematic review on handling covariates in randomized controlled trials

BACKGROUND: In theory, efficient design of randomized controlled trials (RCTs) involves randomization algorithms that control baseline variable imbalance efficiently, and corresponding analysis involves pre-specified adjustment for baseline covariates. This review sought to explore techniques for ha...

Descripción completa

Detalles Bibliográficos
Autores principales: Ciolino, Jody D., Palac, Hannah L., Yang, Amy, Vaca, Mireya, Belli, Hayley M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610785/
https://www.ncbi.nlm.nih.gov/pubmed/31269898
http://dx.doi.org/10.1186/s12874-019-0787-8
_version_ 1783432565253734400
author Ciolino, Jody D.
Palac, Hannah L.
Yang, Amy
Vaca, Mireya
Belli, Hayley M.
author_facet Ciolino, Jody D.
Palac, Hannah L.
Yang, Amy
Vaca, Mireya
Belli, Hayley M.
author_sort Ciolino, Jody D.
collection PubMed
description BACKGROUND: In theory, efficient design of randomized controlled trials (RCTs) involves randomization algorithms that control baseline variable imbalance efficiently, and corresponding analysis involves pre-specified adjustment for baseline covariates. This review sought to explore techniques for handling potentially influential baseline variables in both the design and analysis phase of RCTs. METHODS: We searched PubMed for articles indexed “randomized controlled trial”, published in the NEJM, JAMA, BMJ, or Lancet for two time periods: 2009 and 2014 (before and after updated CONSORT guidelines). Upon screening (343), 298 articles underwent full review and data abstraction. RESULTS: Typical articles reported on superiority (86%), multicenter (92%), two-armed (79%) trials; 81% of trials involved covariates in the allocation and 84% presented adjusted analysis results. The majority reported a stratified block method (69%) of allocation, and of the trials reporting adjusted analyses, 91% were pre-specified. Trials published in 2014 were more likely to report adjusted analyses (87% vs. 79%, p = 0.0100) and more likely to pre-specify adjustment in analyses (95% vs. 85%, p = 0.0045). Studies initiated in later years (2010 or later) were less likely to use an adaptive method of randomization (p = 0.0066; 7% of those beginning in 2010 or later vs. 31% of those starting before 2000) but more likely to report a pre-specified adjusted analysis (p = 0.0029; 97% for those initiated in 2010 or later vs. 69% of those started before 2000). CONCLUSION: While optimal reporting procedures and pre-specification of adjusted analyses for RCTs tend to be progressively more prevalent over time, we see the opposite effect on reported use of covariate-adaptive randomization methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0787-8) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6610785
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-66107852019-07-16 Ideal vs. real: a systematic review on handling covariates in randomized controlled trials Ciolino, Jody D. Palac, Hannah L. Yang, Amy Vaca, Mireya Belli, Hayley M. BMC Med Res Methodol Research Article BACKGROUND: In theory, efficient design of randomized controlled trials (RCTs) involves randomization algorithms that control baseline variable imbalance efficiently, and corresponding analysis involves pre-specified adjustment for baseline covariates. This review sought to explore techniques for handling potentially influential baseline variables in both the design and analysis phase of RCTs. METHODS: We searched PubMed for articles indexed “randomized controlled trial”, published in the NEJM, JAMA, BMJ, or Lancet for two time periods: 2009 and 2014 (before and after updated CONSORT guidelines). Upon screening (343), 298 articles underwent full review and data abstraction. RESULTS: Typical articles reported on superiority (86%), multicenter (92%), two-armed (79%) trials; 81% of trials involved covariates in the allocation and 84% presented adjusted analysis results. The majority reported a stratified block method (69%) of allocation, and of the trials reporting adjusted analyses, 91% were pre-specified. Trials published in 2014 were more likely to report adjusted analyses (87% vs. 79%, p = 0.0100) and more likely to pre-specify adjustment in analyses (95% vs. 85%, p = 0.0045). Studies initiated in later years (2010 or later) were less likely to use an adaptive method of randomization (p = 0.0066; 7% of those beginning in 2010 or later vs. 31% of those starting before 2000) but more likely to report a pre-specified adjusted analysis (p = 0.0029; 97% for those initiated in 2010 or later vs. 69% of those started before 2000). CONCLUSION: While optimal reporting procedures and pre-specification of adjusted analyses for RCTs tend to be progressively more prevalent over time, we see the opposite effect on reported use of covariate-adaptive randomization methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-019-0787-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-03 /pmc/articles/PMC6610785/ /pubmed/31269898 http://dx.doi.org/10.1186/s12874-019-0787-8 Text en © The Author(s). 2019 Open AccessThis 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
Ciolino, Jody D.
Palac, Hannah L.
Yang, Amy
Vaca, Mireya
Belli, Hayley M.
Ideal vs. real: a systematic review on handling covariates in randomized controlled trials
title Ideal vs. real: a systematic review on handling covariates in randomized controlled trials
title_full Ideal vs. real: a systematic review on handling covariates in randomized controlled trials
title_fullStr Ideal vs. real: a systematic review on handling covariates in randomized controlled trials
title_full_unstemmed Ideal vs. real: a systematic review on handling covariates in randomized controlled trials
title_short Ideal vs. real: a systematic review on handling covariates in randomized controlled trials
title_sort ideal vs. real: a systematic review on handling covariates in randomized controlled trials
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610785/
https://www.ncbi.nlm.nih.gov/pubmed/31269898
http://dx.doi.org/10.1186/s12874-019-0787-8
work_keys_str_mv AT ciolinojodyd idealvsrealasystematicreviewonhandlingcovariatesinrandomizedcontrolledtrials
AT palachannahl idealvsrealasystematicreviewonhandlingcovariatesinrandomizedcontrolledtrials
AT yangamy idealvsrealasystematicreviewonhandlingcovariatesinrandomizedcontrolledtrials
AT vacamireya idealvsrealasystematicreviewonhandlingcovariatesinrandomizedcontrolledtrials
AT bellihayleym idealvsrealasystematicreviewonhandlingcovariatesinrandomizedcontrolledtrials