Admissible multiarm stepped-wedge cluster randomized trial designs.
Ontology highlight
ABSTRACT:
SUBMITTER: Grayling MJ
PROVIDER: S-EPMC6491976 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BACKGROUND:Controlled implementation trials often randomize the intervention at the site level, enrolling relatively few sites (e.g., 6-20) compared to trials that randomize by subject. Trials with few sites carry a substantial risk of an imbalance between intervened (cases) and non-intervened (control) sites in important site characteristics, thereby threatening the internal validity of the primary comparison. A stepped wedge design (SWD) staggers the intervention at sites over a sequence of times or time waves until all sites eventually receive the intervention. We propose a new randomization method, sequential balance, to control time trend in site allocation by minimizing sequential imbalance across multiple characteristics. We illustrate the new method by applying it to a SWD implementation trial. METHODS:The trial investigated the impact of blended internal-external facilitation on the establishment of evidence-based teams in general mental health clinics in nine US Department of Veterans Affairs medical centers. Prior to randomization to start time, an expert panel of implementation researchers and health system program leaders identified by consensus a series of eight facility-level characteristics judged relevant to the success of implementation. We characterized each of the nine sites according to these consensus features. Using a weighted sum of these characteristics, we calculated imbalance scores for each of 1680 possible site assignments to identify the most sequentially balanced assignment schemes. RESULTS:From 1680 possible site assignments, we identified 34 assignments with minimal imbalance scores, and then randomly selected one assignment by which to randomize start time. Initially, the mean imbalance score was 3.10, but restricted to the 34 assignments, it declined to 0.99. CONCLUSIONS:Sequential balancing of site characteristics across groups of sites in the time waves of a SWD strengthens the internal validity of study conclusions by minimizing potential confounding. TRIAL REGISTRATION:Registered at ClinicalTrials.gov as clinical trials # NCT02543840 ; entered 9/4/2015.
| S-EPMC6500026 | biostudies-literature
Project description:BackgroundDuring the 2014 Ebola virus disease (EVD) outbreak, policy-makers were confronted with difficult decisions on how best to test the efficacy of EVD vaccines. On one hand, many were reluctant to withhold a vaccine that might prevent a fatal disease from study participants randomized to a control arm. On the other, regulatory bodies called for rigorous placebo-controlled trials to permit direct measurement of vaccine efficacy prior to approval of the products. A stepped-wedge cluster study (SWCT) was proposed as an alternative to a more traditional randomized controlled vaccine trial to address these concerns. Here, we propose novel "ordered stepped-wedge cluster trial" (OSWCT) designs to further mitigate tradeoffs between ethical concerns, logistics, and statistical rigor.Methodology/principal findingsWe constructed a spatially structured mathematical model of the EVD outbreak in Sierra Leone. We used the output of this model to simulate and compare a series of stepped-wedge cluster vaccine studies. Our model reproduced the observed order of first case occurrence within districts of Sierra Leone. Depending on the infection risk within the trial population and the trial start dates, the statistical power to detect a vaccine efficacy of 90% varied from 14% to 32% for standard SWCT, and from 67% to 91% for OSWCTs for an alpha error of 5%. The model's projection of first case occurrence was robust to changes in disease natural history parameters.Conclusions/significanceOrdering clusters in a step-wedge trial based on the cluster's underlying risk of infection as predicted by a spatial model can increase the statistical power of a SWCT. In the event of another hemorrhagic fever outbreak, implementation of our proposed OSWCT designs could improve statistical power when a step-wedge study is desirable based on either ethical concerns or logistical constraints.
| S-EPMC4979980 | biostudies-literature
Project description:BackgroundA cluster trial with unequal cluster sizes often has lower precision than one with equal clusters, with a corresponding inflation of the design effect. For parallel group trials, adjustments to the design effect are available under sampling models with a single intracluster correlation. Design effects for equal clusters under more complex scenarios have appeared recently (including stepped wedge trials under cross-sectional or longitudinal sampling). We investigate the impact of unequal cluster size in these more general settings.ResultsAssuming a linear mixed model with an exchangeable correlation structure that incorporates cluster and subject autocorrelation, we compute the relative efficiency (RE) of a trial with clusters of unequal size under a size-stratified randomization scheme, as compared to an equal cluster trial with the same total number of observations. If there are no within-cluster time effects, the RE exceeds that for a parallel trial. In general, the RE is a weighted average of the RE for a parallel trial and the RE for a crossover trial in the same clusters. Existing approximations for parallel designs are extended to the general setting. Increasing the cluster size by the factor (1 + CV2 ), where CV is the coefficient of variation of cluster size, leads to conservative sample sizes, as in a popular method for parallel trials.ConclusionMethods to assess experimental precision for single-period parallel trials with unequal cluster sizes can be extended to stepped wedge and other complete layouts under longitudinal or cross-sectional sampling. In practice, the loss of precision due to unequal cluster sizes is unlikely to exceed 12%.
| S-EPMC6635744 | biostudies-literature
Project description:BACKGROUND:Stepped wedge cluster randomized trials (SW-CRT) are increasingly used to evaluate new clinical programs, yet there is limited guidance on practical aspects of applying this design. We report our early experiences conducting a SW-CRT to examine an inpatient mobility program (STRIDE) in the Veterans Health Administration (VHA). We provide recommendations for future research using this design to evaluate clinical programs. METHODS:Based on data from study records and reflections from the investigator team, we describe and assess the design and initial stages of a SW-CRT, from site recruitment to program launch in 8 VHA hospitals. RESULTS:Site recruitment consisted of thirty 1-h conference calls with representatives from 22 individual VAs who expressed interest in implementing STRIDE. Of these, 8 hospitals were enrolled and randomly assigned in two stratified blocks (4 hospitals per block) to a STRIDE launch date. Block 1 randomization occurred in July 2017 with first STRIDE launch in December 2017; block 2 randomization occurred in April 2018 with first STRIDE launch in January 2019. The primary study outcome of discharge destination will be assessed using routinely collected data in the electronic health record (EHR). Within randomized blocks, two hospitals per sequence launched STRIDE approximately every 3?months with primary outcome assessment paused during the 3-month time period of program launch. All sites received 6-8 implementation support calls, according to a pre-specified schedule, from the time of recruitment to program launch, and all 8 sites successfully launched within their assigned 3-month window. Seven of the eight sites initially started with a limited roll out (for example on one ward) or modified version of STRIDE (for example, using existing staff to conduct walks until new positions were filled). CONCLUSIONS:Future studies should incorporate sufficient time for site recruitment and carefully consider the following to inform design of SW-CRTs to evaluate rollout of a new clinical program: (1) whether a blocked randomization fits study needs, (2) the amount of time and implementation support sites will need to start their programs, and (3) whether clinical programs are likely to include a "ramp-up" period. Successful execution of SW-CRT designs requires both adherence to rigorous design principles and also careful consideration of logistical requirements for timing of program roll out. TRIAL REGISTRATION:ClinicalsTrials.gov NCT03300336 . Prospectively registered on 3 October 2017.
| S-EPMC7574435 | biostudies-literature
Project description:BackgroundStepped-wedge cluster randomized trial (SW-CRT) designs are often used when there is a desire to provide an intervention to all enrolled clusters, because of a belief that it will be effective. However, given there should be equipoise at trial commencement, there has been discussion around whether a pre-trial decision to provide the intervention to all clusters is appropriate. In pharmaceutical drug development, a solution to a similar desire to provide more patients with an effective treatment is to use a response adaptive (RA) design.MethodsWe introduce a way in which RA design could be incorporated in an SW-CRT, permitting modification of the intervention allocation during the trial. The proposed framework explicitly permits a balance to be sought between power and patient benefit considerations. A simulation study evaluates the methodology.ResultsIn one scenario, for one particular RA design, the proportion of cluster-periods spent in the intervention condition was observed to increase from 32.2% to 67.9% as the intervention effect was increased. A cost of this was a 6.2% power drop compared to a design that maximized power by fixing the proportion of time in the intervention condition at 45.0%, regardless of the intervention effect.ConclusionsAn RA approach may be most applicable to settings for which the intervention has substantial individual or societal benefit considerations, potentially in combination with notable safety concerns. In such a setting, the proposed methodology may routinely provide the desired adaptability of the roll-out speed, with only a small cost to the study's power.
| S-EPMC7612601 | biostudies-literature
Project description:BACKGROUND:Variable standards of care may contribute to poor outcomes associated with AKI. We evaluated whether a multifaceted intervention (AKI e-alerts, an AKI care bundle, and an education program) would improve delivery of care and patient outcomes at an organizational level. METHODS:A multicenter, pragmatic, stepped-wedge cluster randomized trial was performed in five UK hospitals, involving patients with AKI aged ?18 years. The intervention was introduced sequentially across fixed three-month periods according to a randomly determined schedule until all hospitals were exposed. The primary outcome was 30-day mortality, with pre-specified secondary endpoints and a nested evaluation of care process delivery. The nature of the intervention precluded blinding, but data collection and analysis were independent of project delivery teams. RESULTS:We studied 24,059 AKI episodes, finding an overall 30-day mortality of 24.5%, with no difference between control and intervention periods. Hospital length of stay was reduced with the intervention (decreases of 0.7, 1.1, and 1.3 days at the 0.5, 0.6, and 0.7 quantiles, respectively). AKI incidence increased and was mirrored by an increase in the proportion of patients with a coded diagnosis of AKI. Our assessment of process measures in 1048 patients showed improvements in several metrics including AKI recognition, medication optimization, and fluid assessment. CONCLUSIONS:A complex, hospital-wide intervention to reduce harm associated with AKI did not reduce 30-day AKI mortality but did result in reductions in hospital length of stay, accompanied by improvements in in quality of care. An increase in AKI incidence likely reflected improved recognition.
| S-EPMC6405151 | biostudies-literature
Project description:Practice facilitation has been associated with meaningful improvements in disease prevention and quality of patient care. Using practice facilitation, the Improved Delivery of Cardiovascular Care (IDOCC) project aimed to improve the delivery of evidence-based cardiovascular care in primary care practices across a large health region. Our goal was to evaluate IDOCC's impact on adherence to processes of care delivery.A pragmatic stepped wedge cluster randomized trial recruiting primary care providers in practices located in Eastern Ontario, Canada (ClinicalTrials.gov: NCT00574808). Participants were randomly assigned by region to one of three steps. Practice facilitators were intended to visit practices every 3-4 (year 1-intensive) or 6-12 weeks (year 2-sustainability) to support changes in practice behavior. The primary outcome was mean adherence to indicators of evidence-based care measured at the patient level. Adherence was assessed by chart review of a randomly selected cohort of 66 patients per practice in each pre-intervention year, as well as in year 1 and year 2 post-intervention.Eighty-four practices (182 physicians) participated. On average, facilitators had 6.6 (min: 2, max: 11) face-to-face visits with practices in year 1 and 2.5 (min: 0 max: 10) visits in year 2. We collected chart data from 5292 patients. After adjustment for patient and provider characteristics, there was a 1.9 % (95 % confidence interval (CI): -2.9 to -0.9 %) and 4.2 % (95 % CI: -5.7 to -2.6 %) absolute decrease in mean adherence from baseline to intensive and sustainability years, respectively.IDOCC did not improve adherence to best-practice guidelines. Our results showed a small statistically significant decrease in mean adherence of questionable clinical significance. Potential reasons for this result include implementation challenges, competing priorities in practices, a broad focus on multiple chronic disease indicators, and use of an overall index of adherence. These results contrast with findings from previously reported facilitation trials and highlight the complexities and challenges of translating research findings into clinical practice.ClinicalTrials.gov NCT00574808.
| S-EPMC4625868 | biostudies-literature
Project description:BackgroundAdherence to and completion of tuberculosis (TB) treatment remain problematic in many high-burden countries. 99DOTS is a low-cost digital adherence technology that could increase TB treatment completion.Methods and findingsWe conducted a pragmatic stepped-wedge cluster-randomized trial including all adults treated for drug-susceptible pulmonary TB at 18 health facilities across Uganda over 8 months (1 December 2018-31 July 2019). Facilities were randomized to switch from routine (control period) to 99DOTS-based (intervention period) TB treatment supervision in consecutive months. Patients were allocated to the control or intervention period based on which facility they attended and their treatment start date. Health facility staff and patients were not blinded to the intervention. The primary outcome was TB treatment completion. Due to the pragmatic nature of the trial, the primary analysis was done according to intention-to-treat (ITT) and per protocol (PP) principles. This trial is registered with the Pan African Clinical Trials Registry (PACTR201808609844917). Of 1,913 eligible patients at the 18 health facilities (1,022 and 891 during the control and intervention periods, respectively), 38.0% were women, mean (SD) age was 39.4 (14.4) years, 46.8% were HIV-infected, and most (91.4%) had newly diagnosed TB. In total, 463 (52.0%) patients were enrolled on 99DOTS during the intervention period. In the ITT analysis, the odds of treatment success were similar in the intervention and control periods (adjusted odds ratio [aOR] 1.04, 95% CI 0.68-1.58, p = 0.87). The odds of treatment success did not increase in the intervention period for either men (aOR 1.24, 95% CI 0.73-2.10) or women (aOR 0.67, 95% CI 0.35-1.29), or for either patients with HIV infection (aOR 1.51, 95% CI 0.81-2.85) or without HIV infection (aOR 0.78, 95% CI 0.46-1.32). In the PP analysis, the 99DOTS-based intervention increased the odds of treatment success (aOR 2.89, 95% CI 1.57-5.33, p = 0.001). The odds of completing the intensive phase of treatment and the odds of not being lost to follow-up were similarly improved in PP but not ITT analyses. Study limitations include the likelihood of selection bias in the PP analysis, inability to verify medication dosing in either arm, and incomplete implementation of some components of the intervention.Conclusions99DOTS-based treatment supervision did not improve treatment outcomes in the overall study population. However, similar treatment outcomes were achieved during the control and intervention periods, and those patients enrolled on 99DOTS achieved high treatment completion. 99DOTS-based treatment supervision could be a viable alternative to directly observed therapy for a substantial proportion of patients with TB.Trial registrationPan-African Clinical Trials Registry (PACTR201808609844917).
| S-EPMC8136841 | biostudies-literature
Project description:PurposeDespite the growing popularity of stepped-wedge cluster randomized trials (SW-CRTs) for practice-based research, the design's advantages and challenges are not well documented. The objective of this study was to identify the advantages and challenges of the SW-CRT design for large-scale intervention implementations in primary care settings.MethodsThe EvidenceNOW: Advancing Heart Health initiative, funded by the Agency for Healthcare Research and Quality, included a large collection of SW-CRTs. We conducted qualitative interviews with 17 key informants from EvidenceNOW grantees to identify the advantages and challenges of using SW-CRT design.ResultsAll interviewees reported that SW-CRT can be an effective study design for large-scale intervention implementations. Advantages included (1) incentivized recruitment, (2) staggered resource allocation, and (3) statistical power. Challenges included (1) time-sensitive recruitment, (2) retention, (3) randomization requirements and practice preferences, (4) achieving treatment schedule fidelity, (5) intensive data collection, (6) the Hawthorne effect, and (7) temporal trends.ConclusionsThe challenges experienced by EvidenceNOW grantees suggest that certain favorable real-world conditions constitute a context that increases the odds of a successful SW-CRT. An existing infrastructure can support the recruitment of many practices. Strong retention plans are needed to continue to engage sites waiting to start the intervention. Finally, study outcomes should be ones already captured in routine practice; otherwise, funders and investigators should assess the feasibility and cost of data collection.VISUAL ABSTRACT.
| S-EPMC9199039 | biostudies-literature
Project description:The stepped wedge cluster randomized trial (SW-CRT) is an increasingly popular design for evaluating health service delivery or policy interventions. An essential consideration of this design is the need to account for both within-period and between-period correlations in sample size calculations. Especially when embedded in health care delivery systems, many SW-CRTs may have subclusters nested in clusters, within which outcomes are collected longitudinally. However, existing sample size methods that account for between-period correlations have not allowed for multiple levels of clustering. We present computationally efficient sample size procedures that properly differentiate within-period and between-period intracluster correlation coefficients in SW-CRTs in the presence of subclusters. We introduce an extended block exchangeable correlation matrix to characterize the complex dependencies of outcomes within clusters. For Gaussian outcomes, we derive a closed-form sample size expression that depends on the correlation structure only through two eigenvalues of the extended block exchangeable correlation structure. For non-Gaussian outcomes, we present a generic sample size algorithm based on linearization and elucidate simplifications under canonical link functions. For example, we show that the approximate sample size formula under a logistic linear mixed model depends on three eigenvalues of the extended block exchangeable correlation matrix. We provide an extension to accommodate unequal cluster sizes and validate the proposed methods via simulations. Finally, we illustrate our methods in two real SW-CRTs with subclusters.
| S-EPMC9054939 | biostudies-literature