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Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design

BACKGROUND: There are currently no methodological studies on the performance of the statistical models for estimating intervention effects based on the time-to-recurrent-event (TTRE) in stepped wedge cluster randomised trial (SWCRT) using an open cohort design. This study aims to address this by eva...

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Autores principales: Oyamada, Shunsuke, Chiu, Shih-Wei, Yamaguchi, Takuhiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040235/
https://www.ncbi.nlm.nih.gov/pubmed/35473492
http://dx.doi.org/10.1186/s12874-022-01552-6
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author Oyamada, Shunsuke
Chiu, Shih-Wei
Yamaguchi, Takuhiro
author_facet Oyamada, Shunsuke
Chiu, Shih-Wei
Yamaguchi, Takuhiro
author_sort Oyamada, Shunsuke
collection PubMed
description BACKGROUND: There are currently no methodological studies on the performance of the statistical models for estimating intervention effects based on the time-to-recurrent-event (TTRE) in stepped wedge cluster randomised trial (SWCRT) using an open cohort design. This study aims to address this by evaluating the performance of these statistical models using an open cohort design with the Monte Carlo simulation in various settings and their application using an actual example. METHODS: Using Monte Carlo simulations, we evaluated the performance of the existing extended Cox proportional hazard models, i.e., the Andersen-Gill (AG), Prentice-Williams-Peterson Total-Time (PWP-TT), and Prentice-Williams-Peterson Gap-time (PWP-GT) models, using the settings of several event generation models and true intervention effects, with and without stratification by clusters. Unidirectional switching in SWCRT was represented using time-dependent covariates. RESULTS: Using Monte Carlo simulations with the various described settings, in situations where inter-individual variability do not exist, the PWP-GT model with stratification by clusters showed the best performance in most settings and reasonable performance in the others. The only situation in which the performance of the PWP-TT model with stratification by clusters was not inferior to that of the PWP-GT model with stratification by clusters was when there was a certain amount of follow-up period, and the timing of the trial entry was random within the trial period, including the follow-up period. In situations where inter-individual variability existed, the PWP-GT model consistently underperformed compared to the PWP-TT model. The AG model performed well only in a specific setting. By analysing actual examples, it was found that almost all the statistical models suggested that the risk of events during the intervention condition may be somewhat higher than in the control, although the difference was not statistically significant. CONCLUSIONS: When estimating the TTRE-based intervention effects of SWCRT in various settings using an open cohort design, the PWP-GT model with stratification by clusters performed most reasonably in situations where inter-individual variability was not present. However, if inter-individual variability was present, the PWP-TT model with stratification by clusters performed best. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01552-6.
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spelling pubmed-90402352022-04-27 Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design Oyamada, Shunsuke Chiu, Shih-Wei Yamaguchi, Takuhiro BMC Med Res Methodol Research BACKGROUND: There are currently no methodological studies on the performance of the statistical models for estimating intervention effects based on the time-to-recurrent-event (TTRE) in stepped wedge cluster randomised trial (SWCRT) using an open cohort design. This study aims to address this by evaluating the performance of these statistical models using an open cohort design with the Monte Carlo simulation in various settings and their application using an actual example. METHODS: Using Monte Carlo simulations, we evaluated the performance of the existing extended Cox proportional hazard models, i.e., the Andersen-Gill (AG), Prentice-Williams-Peterson Total-Time (PWP-TT), and Prentice-Williams-Peterson Gap-time (PWP-GT) models, using the settings of several event generation models and true intervention effects, with and without stratification by clusters. Unidirectional switching in SWCRT was represented using time-dependent covariates. RESULTS: Using Monte Carlo simulations with the various described settings, in situations where inter-individual variability do not exist, the PWP-GT model with stratification by clusters showed the best performance in most settings and reasonable performance in the others. The only situation in which the performance of the PWP-TT model with stratification by clusters was not inferior to that of the PWP-GT model with stratification by clusters was when there was a certain amount of follow-up period, and the timing of the trial entry was random within the trial period, including the follow-up period. In situations where inter-individual variability existed, the PWP-GT model consistently underperformed compared to the PWP-TT model. The AG model performed well only in a specific setting. By analysing actual examples, it was found that almost all the statistical models suggested that the risk of events during the intervention condition may be somewhat higher than in the control, although the difference was not statistically significant. CONCLUSIONS: When estimating the TTRE-based intervention effects of SWCRT in various settings using an open cohort design, the PWP-GT model with stratification by clusters performed most reasonably in situations where inter-individual variability was not present. However, if inter-individual variability was present, the PWP-TT model with stratification by clusters performed best. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01552-6. BioMed Central 2022-04-26 /pmc/articles/PMC9040235/ /pubmed/35473492 http://dx.doi.org/10.1186/s12874-022-01552-6 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
Oyamada, Shunsuke
Chiu, Shih-Wei
Yamaguchi, Takuhiro
Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design
title Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design
title_full Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design
title_fullStr Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design
title_full_unstemmed Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design
title_short Comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design
title_sort comparison of statistical models for estimating intervention effects based on time-to-recurrent-event in stepped wedge cluster randomized trial using open cohort design
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040235/
https://www.ncbi.nlm.nih.gov/pubmed/35473492
http://dx.doi.org/10.1186/s12874-022-01552-6
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