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Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies
BACKGROUND: To summarize the up-to-date empirical evidence on trial-level characteristics of randomized controlled trials associated with treatment effect estimates. METHODS: A systematic review searched three databases up to August 2020. Meta-epidemiological (ME) studies of randomized controlled tr...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202161/ https://www.ncbi.nlm.nih.gov/pubmed/35705904 http://dx.doi.org/10.1186/s12874-022-01650-5 |
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author | Wang, Huan Song, Jinlu Lin, Yali Dai, Wenjie Gao, Yinyan Qin, Lang Chen, Yancong Tam, Wilson Wu, Irene XY Chung, Vincent CH |
author_facet | Wang, Huan Song, Jinlu Lin, Yali Dai, Wenjie Gao, Yinyan Qin, Lang Chen, Yancong Tam, Wilson Wu, Irene XY Chung, Vincent CH |
author_sort | Wang, Huan |
collection | PubMed |
description | BACKGROUND: To summarize the up-to-date empirical evidence on trial-level characteristics of randomized controlled trials associated with treatment effect estimates. METHODS: A systematic review searched three databases up to August 2020. Meta-epidemiological (ME) studies of randomized controlled trials on intervention effect were eligible. We assessed the methodological quality of ME studies using a self-developed criterion. Associations between treatment effect estimates and trial-level characteristics were presented using forest plots. RESULTS: Eighty ME studies were included, with 25/80 (31%) being published after 2015. Less than one-third ME studies critically appraised the included studies (26/80, 33%), published a protocol (23/80, 29%), and provided a list of excluded studies with justifications (12/80, 15%). Trials with high or unclear (versus low) risk of bias on sequence generation (3/14 for binary outcome and 1/6 for continuous outcome), allocation concealment (11/18 and 1/6), double blinding (5/15 and 2/4) and smaller sample size (4/5 and 2/2) significantly associated with larger treatment effect estimates. Associations between high or unclear risk of bias on allocation concealment (5/6 for binary outcome and 1/3 for continuous outcome), double blinding (4/5 and 1/3) and larger treatment effect estimates were more frequently observed for subjective outcomes. The associations between treatment effect estimates and non-blinding of outcome assessors were removed in trials using multiple observers to reach consensus for both binary and continuous outcomes. Some trial characteristics in the Cochrane risk-of-bias (RoB2) tool have not been covered by the included ME studies, including using validated method for outcome measures and selection of the reported results from multiple outcome measures or multiple analysis based on results (e.g., significance of the results). CONCLUSIONS: Consistently significant associations between larger treatment effect estimates and high or unclear risk of bias on sequence generation, allocation concealment, double blinding and smaller sample size were found. The impact of allocation concealment and double blinding were more consistent for subjective outcomes. The methodological and reporting quality of included ME studies were dissatisfactory. Future ME studies should follow the corresponding reporting guideline. Specific guidelines for conducting and critically appraising ME studies are needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01650-5. |
format | Online Article Text |
id | pubmed-9202161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92021612022-06-17 Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies Wang, Huan Song, Jinlu Lin, Yali Dai, Wenjie Gao, Yinyan Qin, Lang Chen, Yancong Tam, Wilson Wu, Irene XY Chung, Vincent CH BMC Med Res Methodol Research BACKGROUND: To summarize the up-to-date empirical evidence on trial-level characteristics of randomized controlled trials associated with treatment effect estimates. METHODS: A systematic review searched three databases up to August 2020. Meta-epidemiological (ME) studies of randomized controlled trials on intervention effect were eligible. We assessed the methodological quality of ME studies using a self-developed criterion. Associations between treatment effect estimates and trial-level characteristics were presented using forest plots. RESULTS: Eighty ME studies were included, with 25/80 (31%) being published after 2015. Less than one-third ME studies critically appraised the included studies (26/80, 33%), published a protocol (23/80, 29%), and provided a list of excluded studies with justifications (12/80, 15%). Trials with high or unclear (versus low) risk of bias on sequence generation (3/14 for binary outcome and 1/6 for continuous outcome), allocation concealment (11/18 and 1/6), double blinding (5/15 and 2/4) and smaller sample size (4/5 and 2/2) significantly associated with larger treatment effect estimates. Associations between high or unclear risk of bias on allocation concealment (5/6 for binary outcome and 1/3 for continuous outcome), double blinding (4/5 and 1/3) and larger treatment effect estimates were more frequently observed for subjective outcomes. The associations between treatment effect estimates and non-blinding of outcome assessors were removed in trials using multiple observers to reach consensus for both binary and continuous outcomes. Some trial characteristics in the Cochrane risk-of-bias (RoB2) tool have not been covered by the included ME studies, including using validated method for outcome measures and selection of the reported results from multiple outcome measures or multiple analysis based on results (e.g., significance of the results). CONCLUSIONS: Consistently significant associations between larger treatment effect estimates and high or unclear risk of bias on sequence generation, allocation concealment, double blinding and smaller sample size were found. The impact of allocation concealment and double blinding were more consistent for subjective outcomes. The methodological and reporting quality of included ME studies were dissatisfactory. Future ME studies should follow the corresponding reporting guideline. Specific guidelines for conducting and critically appraising ME studies are needed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01650-5. BioMed Central 2022-06-15 /pmc/articles/PMC9202161/ /pubmed/35705904 http://dx.doi.org/10.1186/s12874-022-01650-5 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 Wang, Huan Song, Jinlu Lin, Yali Dai, Wenjie Gao, Yinyan Qin, Lang Chen, Yancong Tam, Wilson Wu, Irene XY Chung, Vincent CH Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies |
title | Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies |
title_full | Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies |
title_fullStr | Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies |
title_full_unstemmed | Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies |
title_short | Trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies |
title_sort | trial-level characteristics associate with treatment effect estimates: a systematic review of meta-epidemiological studies |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202161/ https://www.ncbi.nlm.nih.gov/pubmed/35705904 http://dx.doi.org/10.1186/s12874-022-01650-5 |
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