Key concepts in clinical epidemiology: Stepped wedge trials

Efficient designs for three-sequence stepped wedge trials with continuous recruitment

BACKGROUND/AIMS

The standard approach to designing stepped wedge trials that recruit participants in a continuous stream is to divide time into periods of equal length. But the choice of design in such cases is infinitely more flexible: each cluster could cross from the control to the intervention at any point on the continuous time-scale. We consider the case of a stepped wedge design with clusters randomised to just three sequences (designs with small numbers of sequences may be preferred for their simplicity and practicality) and investigate the choice of design that minimises the variance of the treatment effect estimator under different assumptions about the intra-cluster correlation.

METHODS

We make some simplifying assumptions in order to calculate the variance: in particular that we recruit the same number of participants, m , from each cluster over the course of the trial, and that participants present at regularly spaced intervals. We consider an intra-cluster correlation that decays exponentially with separation in time between the presentation of two individuals from the same cluster, from a value of ρ for two individuals who present at the same time, to a value of ρ τ for individuals presenting at the start and end of the trial recruitment interval. We restrict attention to three-sequence designs with centrosymmetry - the property that if we reverse time and swap the intervention and control conditions then the design looks the same. We obtain an expression for the variance of the treatment effect estimator adjusted for effects of time, using methods for generalised least squares estimation, and we evaluate this expression numerically for different designs, and for different parameter values.

RESULTS

There is a two-dimensional space of possible three-sequence, centrosymmetric stepped wedge designs with continuous recruitment. The variance of the treatment effect estimator for given ρ and τ can be plotted as a contour map over this space. The shape of this variance surface depends on τ and on the parameter m ρ / ( 1 - ρ ) , but typically indicates a broad, flat region of close-to-optimal designs. The 'standard' design with equally spaced periods and 1:1:1 allocation rarely performs well, however.

CONCLUSIONS

In many different settings, a relatively simple design can be found (e.g. one based on simple fractions) that offers close-to-optimal efficiency in that setting. There may also be designs that are robustly efficient over a wide range of settings. Contour maps of the kind we illustrate can help guide this choice. If efficiency is offered as one of the justifications for using a stepped wedge design, then it is worth designing with optimal efficiency in mind.

Researchers' experiences of the design and conduct challenges associated with parallel-group cluster-randomised trials and views on a novel open-cohort design

BACKGROUND

Two accepted designs exist for parallel-group cluster-randomised trials (CRTs). Closed-cohort designs follow the same individuals over time with a single recruitment period before randomisation, but face challenges in settings with high attrition. (Repeated) cross-sectional designs recruit at one or more timepoints before and/or after randomisation, collecting data from different individuals present in the cluster at these timepoints, but are unsuitable for assessment of individual change over time. An 'open-cohort' design allows individual follow-up with recruitment before and after cluster-randomisation, but little literature exists on acceptability to inform their use in CRTs.

AIM

To document the views and experiences of expert trialists to identify: a) Design and conduct challenges with established parallel-group CRT designs,b) Perceptions of potential benefits and barriers to implementation of open-cohort CRTs,c) Methods for minimising, and investigating the impact of, bias in open-cohort CRTs.

METHODS

Qualitative consultation via two expert workshops including triallists (n = 24) who had worked on CRTs over a range of settings. Workshop transcripts were analysed using Descriptive Thematic Analysis utilising inductive and deductive coding.

RESULTS

Two central organising concepts were developed. Design and conduct challenges with established CRT designs confirmed that current CRT designs are unable to deal with many of the complex research and intervention circumstances found in some trial settings (e.g. care homes). Perceptions of potential benefits and barriers of open cohort designs included themes on: approaches to recruitment; data collection; analysis; minimising/investigating the impact of bias; and how open-cohort designs might address or present CRT design challenges. Open-cohort designs were felt to provide a solution for some of the challenges current CRT designs present in some settings.

CONCLUSIONS

Open-cohort CRT designs hold promise for addressing the challenges associated with standard CRT designs. Research is needed to provide clarity around definition and guidance on application.

The staircase cluster randomised trial design: A pragmatic alternative to the stepped wedge

This article introduces the 'staircase' design, derived from the zigzag pattern of steps along the diagonal of a stepped wedge design schematic where clusters switch from control to intervention conditions. Unlike a complete stepped wedge design where all participating clusters must collect and provide data for the entire trial duration, clusters in a staircase design are only required to be involved and collect data for a limited number of pre- and post-switch periods. This could alleviate some of the burden on participating clusters, encouraging involvement in the trial and reducing the likelihood of attrition. Staircase designs are already being implemented, although in the absence of a dedicated methodology, approaches to sample size and power calculations have been inconsistent. We provide expressions for the variance of the treatment effect estimator when a linear mixed model for an outcome is assumed for the analysis of staircase designs in order to enable appropriate sample size and power calculations. These include explicit variance expressions for basic staircase designs with one pre- and one post-switch measurement period. We show how the variance of the treatment effect estimator is related to key design parameters and demonstrate power calculations for examples based on a real trial.

The impact of adding cost information to a conversation aid to support shared decision making about low-risk prostate cancer treatment: Results of a stepped-wedge cluster randomised trial

BACKGROUND

Decision aids help patients consider the benefits and drawbacks of care options but rarely include cost information. We assessed the impact of a conversation-based decision aid containing information about low-risk prostate cancer management options and their relative costs.

METHODS

We conducted a stepped-wedge cluster randomised trial in outpatient urology practices within a US-based academic medical center. We randomised five clinicians to four intervention sequences and enroled patients newly diagnosed with low-risk prostate cancer. Primary patient-reported outcomes collected postvisit included the frequency of cost conversations and referrals to address costs. Other patient-reported outcomes included: decisional conflict postvisit and at 3 months, decision regret at 3 months, shared decision-making postvisit, financial toxicity postvisit and at 3 months. Clinicians reported their attitudes about shared decision-making pre- and poststudy, and the intervention's feasibility and acceptability. We used hierarchical regression analysis to assess patient outcomes. The clinician was included as a random effect; fixed effects included education, employment, telehealth versus in-person visit, visit date, and enrolment period.

RESULTS

Between April 2020 and March 2022, we screened 513 patients, contacted 217 eligible patients, and enroled 117/217 (54%) (51 in usual care, 66 in the intervention group). In adjusted analyses, the intervention was not associated with cost conversations (β = .82, p = .27), referrals to cost-related resources (β = -0.36, p = .81), shared decision-making (β = -0.79, p = .32), decisional conflict postvisit (β = -0.34, p= .70), or at follow-up (β = -2.19, p = .16), decision regret at follow-up (β = -9.76, p = .11), or financial toxicity postvisit (β = -1.32, p = .63) or at follow-up (β = -2.41, p = .23). Most clinicians and patients had positive attitudes about the intervention and shared decision-making. In exploratory unadjusted analyses, patients in the intervention group experienced more transient indecision (p < .02) suggesting increased deliberation between visit and follow-up.

DISCUSSION

Despite enthusiasm from clinicians, the intervention was not significantly associated with hypothesised outcomes, though we were unable to robustly test outcomes due to recruitment challenges. Recruitment at the start of the COVID-19 pandemic impacted eligibility, sample size/power, study procedures, and increased telehealth visits and financial worry, independent of the intervention. Future work should explore ways to support shared decision-making, cost conversations, and choice deliberation with a larger sample. Such work could involve additional members of the care team, and consider the detail, quality, and timing of addressing these issues.

PATIENT OR PUBLIC CONTRIBUTION

Patients and clinicians were engaged as stakeholder advisors meeting monthly throughout the duration of the project to advise on the study design, measures selected, data interpretation, and dissemination of study findings.

Implementation of a batched stepped wedge trial evaluating a quality improvement intervention for surgical teams to reduce anastomotic leak after right colectomy

BACKGROUND

Large-scale quality improvement interventions demand robust trial designs with flexibility for delivery in different contexts, particularly during a pandemic. We describe innovative features of a batched stepped wedge trial, ESCP sAfe Anastomosis proGramme in CoLorectal SurgEry (EAGLE), intended to reduce anastomotic leak following right colectomy, and reflect on lessons learned about the implementation of quality improvement programmes on an international scale.

METHODS

Surgical units were recruited and randomised in batches to receive a hospital-level education intervention designed to reduce anastomotic leak, either before, during, or following data collection. All consecutive patients undergoing right colectomy were included. Online learning, patient risk stratification and an in-theatre checklist constituted the intervention. The study was powered to detect an absolute risk reduction of anastomotic leak from 8.1 to 5.6%. Statistical efficiency was optimised using an incomplete stepped wedge trial design and study batches analysed separately then meta-analysed to calculate the intervention effect. An established collaborative group helped nurture strong working relationships between units/countries and a prospectively designed process evaluation will enable evaluation of both the intervention and its implementation.

RESULTS

The batched trial design allowed sequential entry of clusters, targeted research training and proved to be robust to pandemic interruptions. Staggered start times in the incomplete stepped wedge design with long lead-in times can reduce motivation and engagement and require careful administration.

CONCLUSION

EAGLE's robust but flexible study design allowed completion of the study across globally distributed geographical locations in spite of the pandemic. The primary outcome analysed in conjunction with the process evaluation will ensure a rich understanding of the intervention and the effects of the study design.

TRIAL REGISTRATION

National Institute of Health Research Clinical Research Network portfolio IRAS ID: 272,250. Health Research Authority approval 18 October 2019.

CLINICALTRIALS

gov, identifier NCT04270721, protocol ID RG_19196.

A Stepped-Wedge Cluster-Randomized Trial to Improve Adherence to Evidence-Based Practices for Acute Stroke Management

BACKGROUND

There is limited evidence regarding the optimal design and composition of multifaceted quality improvement programs to improve acute stroke care. The researchers aimed to test the effectiveness of a co-designed multifaceted intervention (STELAR: Shared Team Efforts Leading to Adherence Results) directed at hospital clinicians for improving acute stroke care tailored to the local context using feedback of national registry indicator data.

METHODS

STELAR was a stepped-wedge cluster trial (partial randomization) using routinely collected Australian Stroke Clinical Registry data from Victorian hospitals segmented in two-month blocks. Each hospital (cluster) contributed control data from May 2017 and data for the intervention phase from July 2017 until September 2018. The intervention was multifaceted, delivered predominantly in two educational outreach workshops by experienced, external improvement facilitators, consisting of (1) feedback of registry data to identify practice gaps and (2) interprofessional education, barrier assessment, and documentation of an agreed action plan initiated by local clinical leaders appointed as change champions for prioritized clinical indicators. The researchers provided additional outreach support by e-mail/telephone for two months. Multilevel, multivariable regression models were used to assess change in a composite outcome of indicators selected for actions plans (primary outcome) and individual indicators (secondary outcome). Patient survival and disability 90-180 days after stroke were also compared.

RESULTS

Nine hospitals (clusters) participated, and 144 clinicians attended 18 intervention workshops. The control phase included 1,001 patients (median age 76.7 years; 47.4% female, 64.7% ischemic stroke), and the intervention phase 2,146 patients (median age 74.9 years; 44.2% female, 73.8% ischemic stroke). Compared to the control phase, the median score for the composite outcome for the intervention phase was 17% greater for the indicators included in the hospitals' action plans (range 3% to 30%, p = 0.016) and overall for the 10 indicators 6% greater (range 3% to 10%, p < 0.001). Compared to the control phase, patients in the intervention phase more often received stroke unit care (odds ratio [OR] 1.39, 95% confidence interval [CI] 1.05-1.84), were discharged on antithrombotic medications (OR 1.87, 95% CI 1.50-2.33), and received a discharge care plan (OR 1.27, 95% CI 1.05-1.53). Patient outcomes were unchanged.

CONCLUSION

External quality improvement facilitation using workshops and remote support, aligned with routine monitoring via registries, can improve acute stroke care.