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Analysis and reporting of stratified cluster randomized trials—a systematic survey
BACKGROUND: In order to correctly assess the effect of intervention from stratified cluster randomized trials (CRTs), it is necessary to adjust for both clustering and stratification, as failure to do so leads to misleading conclusions about the intervention effect. We have conducted a systematic su...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672868/ https://www.ncbi.nlm.nih.gov/pubmed/33203468 http://dx.doi.org/10.1186/s13063-020-04850-w |
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author | Borhan, Sayem Papaioannou, Alexandra Ma, Jinhui Adachi, Jonathan Thabane, Lehana |
author_facet | Borhan, Sayem Papaioannou, Alexandra Ma, Jinhui Adachi, Jonathan Thabane, Lehana |
author_sort | Borhan, Sayem |
collection | PubMed |
description | BACKGROUND: In order to correctly assess the effect of intervention from stratified cluster randomized trials (CRTs), it is necessary to adjust for both clustering and stratification, as failure to do so leads to misleading conclusions about the intervention effect. We have conducted a systematic survey to examine the current practices about analysis and reporting of stratified CRTs. METHOD: We used the search terms to identify the stratified CRTs from MEDLINE since the inception to July 2019. In phase 1, we screened the title and abstract for English-only studies and selected, including the main results paper of the identified protocols, for the next phase. In phase 2, we screened the full text and selected studies for data abstraction. The data abstraction form was piloted and developed using the REDCap. We abstracted data on multiple design and methodological aspects of the study including whether the primary method adjusted for both clustering and stratification, reporting of sample size, randomization, and results. RESULTS: We screened 2686 studies in the phase 1 and selected 286 studies for phase 2—among them 185 studies were selected for data abstraction. Most of the selected studies were two-arm 140/185 (76%) and parallel-group 165/185 (89%) trials. Among these 185 studies, 27 (15%) of them did not provide any sample size or power calculation, while 105 (57%) studies did not mention any method used for randomization within each stratum. Further, 43 (23%) and 150 (81%) of 185 studies did not provide the definition of all the strata, while more than 60% of the studies did not include all the stratification variable(s) in the flow chart or baseline characteristics table. More than half 114/185 (62%) of the studies did not adjust the primary method for both clustering and stratification. CONCLUSION: Stratification helps to achieve the balance among intervention groups. However, to correctly assess the intervention effect from stratified CRTs, it is important to adjust the primary analysis for both stratification and clustering. There are significant deficiencies in the reporting of methodological aspects of stratified CRTs, which require substantial improvements in several areas including definition of strata, inclusion of stratification variable(s) in the flow chart or baseline characteristics table, and reporting the stratum-specific number of clusters and individuals in the intervention groups. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s13063-020-04850-w. |
format | Online Article Text |
id | pubmed-7672868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76728682020-11-19 Analysis and reporting of stratified cluster randomized trials—a systematic survey Borhan, Sayem Papaioannou, Alexandra Ma, Jinhui Adachi, Jonathan Thabane, Lehana Trials Review BACKGROUND: In order to correctly assess the effect of intervention from stratified cluster randomized trials (CRTs), it is necessary to adjust for both clustering and stratification, as failure to do so leads to misleading conclusions about the intervention effect. We have conducted a systematic survey to examine the current practices about analysis and reporting of stratified CRTs. METHOD: We used the search terms to identify the stratified CRTs from MEDLINE since the inception to July 2019. In phase 1, we screened the title and abstract for English-only studies and selected, including the main results paper of the identified protocols, for the next phase. In phase 2, we screened the full text and selected studies for data abstraction. The data abstraction form was piloted and developed using the REDCap. We abstracted data on multiple design and methodological aspects of the study including whether the primary method adjusted for both clustering and stratification, reporting of sample size, randomization, and results. RESULTS: We screened 2686 studies in the phase 1 and selected 286 studies for phase 2—among them 185 studies were selected for data abstraction. Most of the selected studies were two-arm 140/185 (76%) and parallel-group 165/185 (89%) trials. Among these 185 studies, 27 (15%) of them did not provide any sample size or power calculation, while 105 (57%) studies did not mention any method used for randomization within each stratum. Further, 43 (23%) and 150 (81%) of 185 studies did not provide the definition of all the strata, while more than 60% of the studies did not include all the stratification variable(s) in the flow chart or baseline characteristics table. More than half 114/185 (62%) of the studies did not adjust the primary method for both clustering and stratification. CONCLUSION: Stratification helps to achieve the balance among intervention groups. However, to correctly assess the intervention effect from stratified CRTs, it is important to adjust the primary analysis for both stratification and clustering. There are significant deficiencies in the reporting of methodological aspects of stratified CRTs, which require substantial improvements in several areas including definition of strata, inclusion of stratification variable(s) in the flow chart or baseline characteristics table, and reporting the stratum-specific number of clusters and individuals in the intervention groups. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s13063-020-04850-w. BioMed Central 2020-11-17 /pmc/articles/PMC7672868/ /pubmed/33203468 http://dx.doi.org/10.1186/s13063-020-04850-w Text en © The Author(s) 2020 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/. 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 in a credit line to the data. |
spellingShingle | Review Borhan, Sayem Papaioannou, Alexandra Ma, Jinhui Adachi, Jonathan Thabane, Lehana Analysis and reporting of stratified cluster randomized trials—a systematic survey |
title | Analysis and reporting of stratified cluster randomized trials—a systematic survey |
title_full | Analysis and reporting of stratified cluster randomized trials—a systematic survey |
title_fullStr | Analysis and reporting of stratified cluster randomized trials—a systematic survey |
title_full_unstemmed | Analysis and reporting of stratified cluster randomized trials—a systematic survey |
title_short | Analysis and reporting of stratified cluster randomized trials—a systematic survey |
title_sort | analysis and reporting of stratified cluster randomized trials—a systematic survey |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672868/ https://www.ncbi.nlm.nih.gov/pubmed/33203468 http://dx.doi.org/10.1186/s13063-020-04850-w |
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