Amaze: a double-blind, multicentre randomised controlled trial to investigate the clinical effectiveness and cost-effectiveness of adding an ablation device-based maze procedure as an adjunct to routine cardiac surgery for patients with pre-existing atrial fibrillation

Sharples, Linda D.; Everett, Colin; Singh, Jeshika; Mills, Christine; Spyt, Tom; Abu‐Omar, Yasir; Fynn, Simon P.; Thorpe, Benjamin; Stoneman, Victoria; Goddard, Hester; Fox-Rushby, Julia; Nashef, Samer A.M.

doi:10.3310/hta22190

Cited by 17 publications

(18 citation statements)

References 69 publications

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“…Studies of complex surgical interventions have reported changes in outcomes as a trial progresses [ 13 ]. Hence, studies may warrant investigation of a ‘period effect’, where patients recruited closer in time have more similar results due to protocol changes, learning effects or trial experience.…”

Section: Discussionmentioning

confidence: 99%

Including random centre effects in design, analysis and presentation of multi-centre trials

Roberts

Sharples

2021

Trials

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Background In large multicentre trials in diverse settings, there is uncertainty about the need to adjust for centre variation in design and analysis. A key distinction is the difference between variation in outcome (independent of treatment) and variation in treatment effect. Through re-analysis of the CRASH-2 trial (2010), this study clarifies when and how to use multi-level models for multicentre studies with binary outcomes. Methods CRASH-2 randomised 20,127 trauma patients across 271 centres and 40 countries to either single-dose tranexamic acid or identical placebo, with all-cause death at 4 weeks the primary outcome. The trial data had a hierarchical structure, with patients nested in hospitals which in turn are nested within countries. Reanalysis of CRASH-2 trial data assessed treatment effect and both patient and centre level baseline covariates as fixed effects in logistic regression models. Random effects were included to assess where there was variation between countries, and between centres within countries, both in underlying risk of death and in treatment effect. Results In CRASH-2, there was significant variation between countries and between centres in death at 4 weeks, but absolutely no differences between countries or centres in the effect of treatment. Average treatment effect was not altered after accounting for centre and country variation in this study. Conclusions It is important to distinguish between underlying variation in outcomes and variation in treatment effects; the former is common but the latter is not. Stratifying randomisation by centre overcomes many statistical problems and including random intercepts in analysis may increase power and decrease bias in mean and standard error estimates. Trial registration Current Controlled Trials ISRCTN86750102, ClinicalTrials.gov NCT00375258, and South African Clinical Trial Register DOH-27-0607-1919

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Section: Discussionmentioning

confidence: 99%

Including random centre effects in design, analysis and presentation of multi-centre trials

Roberts

Sharples

2021

Trials

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“…The Amaze cardiac surgical trial assessed whether ablation during heart surgery returns the heart to normal sinus rhythm in patients with a documented history of rapid or irregular heart rhythm. 7 , 16 This multi-centre, Phase III, pragmatic RCT randomised 352 patients to ablation plus planned surgery, or planned surgery alone (control arm). The primary outcome was sinus rhythm restoration at one year post-surgery (binary outcome).…”

Section: Resultsmentioning

confidence: 99%

“…[2][3][4] RCTs in surgery are increasingly used in a range of disease populations, including cancer, orthopaedic and cardiac patients. [5][6][7] These trials often adopt pragmatic designs to reflect the intervention as performed in clinical practice. During trial design, decisions are made about the inclusion and level of standardisation of each stage of the procedure, rather than imposing a strictly standardised protocol.…”

Section: Introductionmentioning

confidence: 99%

“…Methods are illustrated using the Amaze heart surgery trial. 7,16 We provide background, methods and assumptions for causal mediation methods based on counterfactual arguments, and an overview of resources for implementation of methods in standard statistical software in the section 'Methods'. These are applied to the Amaze trial, which motivated this work as described in the section 'Results'; conclusions and discussion are provided in the section 'Conclusion'.…”

Section: Introductionmentioning

confidence: 99%

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Exploring mechanisms of action in clinical trials of complex surgical interventions using mediation analysis

et al. 2020

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Background: Surgical interventions allow for tailoring of treatment to individual patients and implementation may vary with surgeon and healthcare provider. In addition, in clinical trials assessing two competing surgical interventions, the treatments may be accompanied by co-interventions. Aims: This study explores the use of causal mediation analysis to (1) delineate the treatment effect that results directly from the surgical intervention under study and the indirect effect acting through a co-intervention and (2) to evaluate the benefit of the surgical intervention if either everybody in the trial population received the co-intervention or nobody received it. Methods: Within a counterfactual framework, relevant direct and indirect effects of a surgical intervention are estimated and adjusted for confounding via parametric regression models, for the situation where both mediator and outcome are binary, with baseline stratification factors included as fixed effects and surgeons as random intercepts. The causal difference in probability of a successful outcome (estimand of interest) is calculated using Monte Carlo simulation with bootstrapping for confidence intervals. Packages for estimation within standard statistical software are reviewed briefly. A step by step application of methods is illustrated using the Amaze randomised trial of ablation as an adjunct to cardiac surgery in patients with irregular heart rhythm, with a co-intervention (removal of the left atrial appendage) administered to a subset of participants at the surgeon’s discretion. The primary outcome was return to normal heart rhythm at one year post surgery. Results: In Amaze, 17% (95% confidence interval: 6%, 28%) more patients in the active arm had a successful outcome, but there was a large difference between active and control arms in the proportion of patients who received the co-intervention (55% and 30%, respectively). Causal mediation analysis suggested that around 1% of the treatment effect was attributable to the co-intervention (16% natural direct effect). The controlled direct effect ranged from 18% (6%, 30%) if the co-intervention were mandated, to 14% (2%, 25%) if it were prohibited. Including age as a moderator of the mediation effects showed that the natural direct effect of ablation appeared to decrease with age. Conclusions: Causal mediation analysis is a useful quantitative tool to explore mediating effects of co-interventions in surgical trials. In Amaze, investigators could be reassured that the effect of the active treatment, not explainable by differential use of the co-intervention, was significant across analyses.

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“…Preference-based PROs were used in six trials as primary outcomes, including five [21][22][23][24][25] that used the EQ-5D and one 26 that used the SF-6D. Seven trials used the qualityadjusted survival, including three 22 23 25 that used the EQ-5D and four [27][28][29][30] that used specific PROs for estimation. Patient satisfaction was used as the primary outcome Open access in two trials.…”

Section: Trial Characteristicsmentioning

confidence: 99%

Comprehensive review of statistical methods for analysing patient-reported outcomes (PROs) used as primary outcomes in randomised controlled trials (RCTs) published by the UK’sHealth Technology Assessment(HTA) journal (1997–2020)

et al. 2021

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ObjectivesTo identify how frequently patient-reported outcomes (PROs) are used as primary and/or secondary outcomes in randomised controlled trials (RCTs) and to summarise what statistical methods are used for the analysis of PROs.DesignComprehensive review.SettingRCTs funded and published by the United Kingdom’s (UK) National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme.Data sources and eligibilityHTA reports of RCTs published between January 1997 and December 2020 were reviewed.Data extractionInformation relating to PRO use and analysis methods was extracted.Primary and secondary outcome measuresThe frequency of using PROs as primary and/or secondary outcomes; statistical methods that were used for the analysis of PROs as primary outcomes.ResultsIn this review, 37.6% (114/303) of trials used PROs as primary outcomes, and 82.8% (251/303) of trials used PROs as secondary outcomes from 303 NIHR HTA reports of RCTs. In the 114 RCTs where the PRO was the primary outcome, the most used PRO was the Short-Form 36 (8/114); the most popular methods for multivariable analysis were linear mixed model (45/114), linear regression (29/114) and analysis of covariance (13/114); logistic regression was applied for binary and ordinal outcomes in 14/114 trials; and the repeated measures analysis was used in 39/114 trials.ConclusionThe majority of trials used PROs as primary and/or secondary outcomes. Conventional methods such as linear regression are widely used, despite the potential violation of their assumptions. In recent years, there is an increasing trend of using complex models (eg, with mixed effects). Statistical methods developed to address these violations when analysing PROs, such as beta-binomial regression, are not routinely used in practice. Future research will focus on evaluating available statistical methods for the analysis of PROs.

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Amaze: a double-blind, multicentre randomised controlled trial to investigate the clinical effectiveness and cost-effectiveness of adding an ablation device-based maze procedure as an adjunct to routine cardiac surgery for patients with pre-existing atrial fibrillation

Abstract: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in ; Vol. 22, No. 19. See the NIHR Journals Library website for further project information.

Cited by 17 publications

References 69 publications

Including random centre effects in design, analysis and presentation of multi-centre trials

Including random centre effects in design, analysis and presentation of multi-centre trials

Exploring mechanisms of action in clinical trials of complex surgical interventions using mediation analysis

Comprehensive review of statistical methods for analysing patient-reported outcomes (PROs) used as primary outcomes in randomised controlled trials (RCTs) published by the UK’sHealth Technology Assessment(HTA) journal (1997–2020)

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