A scoping review described diversity in methods of randomization and reporting of baseline balance in stepped-wedge cluster randomized trials

Nevins, Pascale; Davis‐Plourde, Kendra; Macedo, Jules Pereira; Ouyang, Yongdong; Ryan, Mary P.; Tong, Guangyu; Wang, Xueqi; Meng, Can; Ortiz-Reyes, Luis; Li, Fan; Caille, Agnès; Taljaard, Monica

doi:10.1016/j.jclinepi.2023.03.010

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…Our search strategy, eligibility criteria, screening and data sources have been described in detail elsewhere 14 and are briefly summarized here.…”

Section: Methodsmentioning

confidence: 99%

“…We previously published a descriptive analysis of SW-CRTs with a focus on randomization procedures and reporting of baseline covariate balance. 14 In the present manuscript, we report on a descriptive analysis of the same set of SW-CRTs with the primary objectives of describing: (1) design features commonly used in practice; (2) analytical approaches and adherence to key requirements for statistical analysis including accounting for period effects, complex correlations, and methods appropriate for small number of clusters; and (3) current practices around covariate adjustment in the analysis. We also examined adherence to key methodological requirements over time and by journal impact factor.…”

Section: Fixed Time Recruitmentmentioning

confidence: 99%

See 1 more Smart Citation

Adherence to key recommendations for design and analysis of stepped-wedge cluster randomized trials: A review of trials published 2016–2022

Nevins,

Ryan,

Davis-Plourde

et al. 2023

Clinical Trials

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Background/Aims The stepped-wedge cluster randomized trial (SW-CRT), in which clusters are randomized to a time at which they will transition to the intervention condition – rather than a trial arm – is a relatively new design. SW-CRTs have additional design and analytical considerations compared to conventional parallel arm trials. To inform future methodological development, including guidance for trialists and the selection of parameters for statistical simulation studies, we conducted a review of recently published SW-CRTs. Specific objectives were to describe (1) the types of designs used in practice, (2) adherence to key requirements for statistical analysis, and (3) practices around covariate adjustment. We also examined changes in adherence over time and by journal impact factor. Methods We used electronic searches to identify primary reports of SW-CRTs published 2016–2022. Two reviewers extracted information from each trial report and its protocol, if available, and resolved disagreements through discussion. Results We identified 160 eligible trials, randomizing a median (Q1–Q3) of 11 (8–18) clusters to 5 (4–7) sequences. The majority (122, 76%) were cross-sectional (almost all with continuous recruitment), 23 (14%) were closed cohorts and 15 (9%) open cohorts. Many trials had complex design features such as multiple or multivariate primary outcomes (50, 31%) or time-dependent repeated measures (27, 22%). The most common type of primary outcome was binary (51%); continuous outcomes were less common (26%). The most frequently used method of analysis was a generalized linear mixed model (112, 70%); generalized estimating equations were used less frequently (12, 8%). Among 142 trials with fewer than 40 clusters, only 9 (6%) reported using methods appropriate for a small number of clusters. Statistical analyses clearly adjusted for time effects in 119 (74%), for within-cluster correlations in 132 (83%), and for distinct between-period correlations in 13 (8%). Covariates were included in the primary analysis of the primary outcome in 82 (51%) and were most often individual-level covariates; however, clear and complete pre-specification of covariates was uncommon. Adherence to some key methodological requirements (adjusting for time effects, accounting for within-period correlation) was higher among trials published in higher versus lower impact factor journals. Substantial improvements over time were not observed although a slight improvement was observed in the proportion accounting for a distinct between-period correlation. Conclusions Future methods development should prioritize methods for SW-CRTs with binary or time-to-event outcomes, small numbers of clusters, continuous recruitment designs, multivariate outcomes, or time-dependent repeated measures. Trialists, journal editors, and peer reviewers should be aware that SW-CRTs have additional methodological requirements over parallel arm designs including the need to account for period effects as well as complex intracluster correlations.

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“…Our search strategy, eligibility criteria, screening and data sources have been described in detail elsewhere 14 and are briefly summarized here.…”

Section: Methodsmentioning

confidence: 99%

Section: Fixed Time Recruitmentmentioning

confidence: 99%

Adherence to key recommendations for design and analysis of stepped-wedge cluster randomized trials: A review of trials published 2016–2022

Nevins,

Ryan,

Davis-Plourde

et al. 2023

Clinical Trials

Self Cite

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“…Thus, this introduces a linear/sequential imbalance across the 6 sites with sites with high levels of training being under-represented in the study due to later entrance. While this is a hypothetical extreme case of low probability, other sequences of less severe sequential imbalance may occur more frequently, especially given that SWCRTs usually randomize a small number of clusters [ 12 ]. In addition, site-level covariates may be imbalanced in a non-linear (e.g.…”

Section: Introductionmentioning

confidence: 99%

Comparing analytical strategies for balancing site-level characteristics in stepped-wedge cluster randomized trials: a simulation study

Ma,

Lee,

Courtney

et al. 2023

BMC Med Res Methodol

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Background Stepped-wedge cluster randomized trials (SWCRTs) are a type of cluster-randomized trial in which clusters are randomized to cross-over to the active intervention sequentially at regular intervals during the study period. For SWCRTs, sequential imbalances of cluster-level characteristics across the random sequence of clusters may lead to biased estimation. Our study aims to examine the effects of balancing cluster-level characteristics in SWCRTs. Methods To quantify the level of cluster-level imbalance, a novel imbalance index was developed based on the Spearman correlation and rank regression of the cluster-level characteristic with the cross-over timepoints. A simulation study was conducted to assess the impact of sequential cluster-level imbalances across different scenarios varying the: number of sites (clusters), sample size, number of cross-over timepoints, site-level intra-cluster correlation coefficient (ICC), and effect sizes. SWCRTs assumed either an immediate “constant” treatment effect, or a gradual “learning” treatment effect which increases over time after crossing over to the active intervention. Key performance metrics included the relative root mean square error (RRMSE) and relative mean bias. Results Fully-balanced designs almost always had the highest efficiency, as measured by the RRMSE, regardless of the number of sites, ICC, effect size, or sample sizes at each time for SWCRTs with learning effect. A consistent decreasing trend of efficiency was observed by increasing RRMSE as imbalance increased. For example, for a 12-site study with 20 participants per site/timepoint and ICC of 0.10, between the most balanced and least balanced designs, the RRMSE efficiency loss ranged from 52.5% to 191.9%. In addition, the RRMSE was decreased for larger sample sizes, larger number of sites, smaller ICC, and larger effect sizes. The impact of pre-balancing diminished when there was no learning effect. Conclusion The impact of pre-balancing on preventing efficiency loss was easily observed when there was a learning effect. This suggests benefit of pre-balancing with respect to impacting factors of treatment effects.

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Editors’ Choice: May 23

Tovey¹,

Tricco²,

Veroniki³

2023

Journal of Clinical Epidemiology

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A scoping review described diversity in methods of randomization and reporting of baseline balance in stepped-wedge cluster randomized trials

Cited by 8 publications

References 29 publications

Adherence to key recommendations for design and analysis of stepped-wedge cluster randomized trials: A review of trials published 2016–2022

Adherence to key recommendations for design and analysis of stepped-wedge cluster randomized trials: A review of trials published 2016–2022

Comparing analytical strategies for balancing site-level characteristics in stepped-wedge cluster randomized trials: a simulation study

Editors’ Choice: May 23

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