Preventing bias in cluster randomised trials

Covariate-constrained randomization in cluster randomized 2 × 2 factorial trials: application to a diabetes prevention study

BACKGROUND

Cluster randomized trials (CRTs) are randomized trials where randomization takes place at an administrative level (e.g., hospitals, clinics, or schools) rather than at the individual level. When the number of available clusters is small, researchers may not be able to rely on simple randomization to achieve balance on cluster-level covariates across treatment conditions. If these cluster-level covariates are predictive of the outcome, covariate imbalance may distort treatment effects, threaten internal validity, lead to a loss of power, and increase the variability of treatment effects. Covariate-constrained randomization (CR) is a randomization strategy designed to reduce the risk of imbalance in cluster-level covariates when performing a CRT. Existing methods for CR have been developed and evaluated for two- and multi-arm CRTs but not for factorial CRTs.

METHODS

Motivated by the BEGIN study-a CRT for weight loss among patients with pre-diabetes-we develop methods for performing CR in 2 × 2 factorial cluster randomized trials with a continuous outcome and continuous cluster-level covariates. We apply our methods to the BEGIN study and use simulation to assess the performance of CR versus simple randomization for estimating treatment effects by varying the number of clusters, the degree to which clusters are associated with the outcome, the distribution of cluster level covariates, the size of the constrained randomization space, and analysis strategies.

RESULTS

Compared to simple randomization of clusters, CR in the factorial setting is effective at achieving balance across cluster-level covariates between treatment conditions and provides more precise inferences. When cluster-level covariates are included in the analyses model, CR also results in greater power to detect treatment effects, but power is low compared to unadjusted analyses when the number of clusters is small.

CONCLUSIONS

CR should be used instead of simple randomization when performing factorial CRTs to avoid highly imbalanced designs and to obtain more precise inferences. Except when there are a small number of clusters, cluster-level covariates should be included in the analysis model to increase power and maintain coverage and type 1 error rates at their nominal levels.

Community-based management of arterial hypertension and cardiovascular risk factors by lay village health workers for people with controlled and uncontrolled blood pressure in rural Lesotho: joint protocol for two cluster-randomized trials within the ComBaCaL cohort study (ComBaCaL aHT Twic 1 and ComBaCaL aHT TwiC 2)

BACKGROUND

Arterial hypertension (aHT) is a major cause for premature morbidity and mortality. Control rates remain poor, especially in low- and middle-income countries. Task-shifting to lay village health workers (VHWs) and the use of digital clinical decision support systems may help to overcome the current aHT care cascade gaps. However, evidence on the effectiveness of comprehensive VHW-led aHT care models, in which VHWs provide antihypertensive drug treatment and manage cardiovascular risk factors is scarce.

METHODS

Using the trials within the cohort (TwiCs) design, we are assessing the effectiveness of VHW-led aHT and cardiovascular risk management in two 1:1 cluster-randomized trials nested within the Community-Based chronic disease Care Lesotho (ComBaCaL) cohort study (NCT05596773). The ComBaCaL cohort study is maintained by trained VHWs and includes the consenting inhabitants of 103 randomly selected villages in rural Lesotho. After community-based aHT screening, adult, non-pregnant ComBaCaL cohort participants with uncontrolled aHT (blood pressure (BP) ≥ 140/90 mmHg) are enrolled in the aHT TwiC 1 and those with controlled aHT (BP < 140/90 mmHg) in the aHT TwiC 2. In intervention villages, VHWs offer lifestyle counseling, basic guideline-directed antihypertensive, lipid-lowering, and antiplatelet treatment supported by a tablet-based decision support application to eligible participants. In control villages, participants are referred to a health facility for therapeutic management. The primary endpoint for both TwiCs is the proportion of participants with controlled BP levels (< 140/90 mmHg) 12 months after enrolment. We hypothesize that the intervention is superior regarding BP control rates in participants with uncontrolled BP (aHT TwiC 1) and non-inferior in participants with controlled BP at baseline (aHT TwiC 2).

DISCUSSION

The TwiCs were launched on September 08, 2023. On May 20, 2024, 697 and 750 participants were enrolled in TwiC 1 and TwiC 2. To our knowledge, these TwiCs are the first trials to assess task-shifting of aHT care to VHWs at the community level, including the prescription of basic antihypertensive, lipid-lowering, and antiplatelet medication in Africa. The ComBaCaL cohort and nested TwiCs are operating within the routine VHW program and countries with similar community health worker programs may benefit from the findings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05684055. Registered on January 04, 2023.

Covariate-constrained randomization in cluster randomized 2x2 factorial trials: Application to a diabetes prevention study

Background

Cluster randomized trials (CRTs) are randomized trials where randomization takes place at an administrative level (e.g., hospitals, clinics, or schools) rather than at the individual level. When the number of available clusters is small, researchers may not be able to rely on simple randomization to achieve balance on cluster-level covariates across treatment conditions. If these cluster-level covariates are predictive of the outcome, covariate imbalance may distort treatment effects, threaten internal validity, lead to a loss of power, and increase the variability of treatment effects. Covariate-constrained randomization (CR) is a randomization strategy designed to reduce the risk of imbalance in cluster-level covariates when performing a CRT. Existing methods for CR have been developed and evaluated for two- and multi-arm CRTs but not for factorial CRTs.

Methods

Motivated by the BEGIN study-a CRT for weight loss among patients with pre-diabetes-we develop methods for performing CR in 2x2 factorial cluster randomized trials. We apply our methods to the BEGIN study and use simulation to assess the performance of CR versus simple randomization for estimating treatment effects by varying the number of clusters, the degree to which clusters are associated with the outcome, the distribution of cluster level covariates, and analysis strategies.

Results

Compared to simple randomization of clusters, CR in the factorial setting is effective at achieving balance across cluster-level covariates between treatment conditions and provides more precise inferences. When cluster-level covariates are included in the analyses model, CR also results in greater power to detect treatment effects, but power is low compared to unadjusted analyses when the number of clusters is small.

Conclusions

CR should be used instead of simple randomization when performing factorial CRTs to avoid highly imbalanced designs and to obtain more precise inferences. Except when there are a small number of clusters, cluster-level covariates should be included in the analysis model to increase power and maintain coverage and Type 1 error rates at their nominal levels.

Practical considerations for sample size calculation for cluster randomized trials

Cluster randomized trials are an essential design in public health and medical research, when individual randomization is infeasible or undesirable for scientific or logistical reasons. However, the correlation among observations within clusters leads to a decrease in statistical power compared to an individually randomised trial with the same total sample size. This correlation - often quantified using the intra-cluster correlation coefficient - must be accounted for in the sample size calculation to ensure that the trial is adequately powered. In this paper, we first describe the principles of sample size calculation for parallel-arm CRTs, and explain how these calculations can be extended to CRTs with cross-over designs, with a baseline measurement and stepped-wedge designs. We introduce tools to guide researchers with their sample size calculation and discuss methods to inform the choice of the a priori estimate of the intra-cluster correlation coefficient for the calculation. We also include additional considerations with respect to anticipated attrition, a small number of clusters, and use of covariates in the randomisation process and in the analysis.

Why and when should we cluster randomize?

A cluster randomized trial is defined as a randomized trial in which intact social units of individuals are randomized rather than individuals themselves. Outcomes are observed on individual participants within clusters (such as patients). Such a design allows assessing interventions targeting cluster-level participants (such as physicians), individual participants or both. Indeed, many interventions assessed in cluster randomized trials are actually complex ones, with distinct components targeting different levels. For a cluster-level intervention, cluster randomization is an obvious choice: the intervention is not divisible at the individual-level. For individual-level interventions, cluster randomization may nevertheless be suitable to prevent group contamination, for logistical reasons, to enhance participants' adherence, or when objectives pertain to the cluster level. An unacceptable reason for cluster randomization would be to avoid obtaining individual consent. Indeed, participants in cluster randomized trials have to be protected as in any type of trial design. Participants may be people from whom data are collected, but they may also be people who are intervened upon, and this includes both patients and physicians (for example, physicians receiving training interventions). Consent should be sought as soon as possible, although there may exist situations where participants may consent only for data collection, not for being exposed to the intervention (because, for instance, they cannot opt-out). There may even be situations where participants are not able to consent at all. In this latter situation a waiver of consent must be granted by a research ethics committee.

Practical and methodological challenges when conducting a cluster randomized trial: Examples and recommendations

The use of cluster randomized trial design to answer research questions is increasing. This design and associated variants such as the cluster randomized crossover and stepped wedge are useful to assess complex interventions in a pragmatic way but when adopting such designs, one may face specific implementation challenges. This article summarizes common challenges faced when conducting cluster randomized trials, cluster randomized crossover trials, and stepped wedge trials, and provides recommendations.

Intracluster correlation coefficients in osteoarthritis cluster randomized trials: A systematic review

OBJECTIVES

The design, analysis, and interpretation of cluster randomized clinical trials (RCTs) require accounting for potential correlation of observations on individuals within the same cluster. Reporting of observed intracluster correlation coefficients (ICCs) in cluster RCTs, as recommended by Consolidated Standards of Reporting Trials (CONSORT), facilitates sample size calculation of future cluster RCTs and understanding of the trial statistical power. Our objective was to summarize observed ICCs in osteoarthritis (OA) cluster RCTs.

DESIGN

Systematic review of knee/hip OA cluster RCTs. We searched Cochrane Central Register of Controlled Trials for trials published from 2012, when CONSORT cluster RCTs extension was published, to September 2022. We calculated the proportion of cluster RCTs that reported observed ICCs. Of those that did, we extracted observed ICCs.

PROSPERO

CRD42022365660.

RESULTS

We screened 1121 references and included 20 cluster RCTs. Only 5 trials (25%) reported the observed ICC for at least one outcome variable. ICC values for pain outcomes were: 0, 0.01, 0.18; for physical function outcomes were: 0, 0.06, 0.13 (knee)/0.27 (hip); Western Ontario and McMaster Universities Arthritis Index (WOMAC) total: 0.02, 0.02; symptoms of anxiety/depression: 0.22; disability: 0; and global change: 0. One out of four (25%) trials reported an ICC that was larger than the ICC used for sample size calculation and thus was underpowered.

CONCLUSIONS

Despite CONSORT statement recommendations for reporting cluster RCTs, few OA trials reported the observed ICC. Given the importance of the ICC to interpretation of trial results and future trial design, this reporting gap warrants attention.

Assessing the representativeness of cluster randomized trials: Evidence from two large pragmatic trials in United States nursing homes

BACKGROUND/AIMS

When the randomized clusters in a cluster randomized trial are selected based on characteristics that influence treatment effectiveness, results from the trial may not be directly applicable to the target population. We used data from two large nursing home-based pragmatic cluster randomized trials to compare nursing home and resident characteristics in randomized facilities to eligible non-randomized and ineligible facilities.

METHODS

We linked data from the high-dose influenza vaccine trial and the Music & Memory Pragmatic TRIal for Nursing Home Residents with ALzheimer's Disease (METRICaL) to nursing home assessments and Medicare fee-for-service claims. The target population for the high-dose trial comprised Medicare-certified nursing homes; the target population for the METRICaL trial comprised nursing homes in one of four US-based nursing home chains. We used standardized mean differences to compare facility and individual characteristics across the three groups and logistic regression to model the probability of nursing home trial participation.

RESULTS

In the high-dose trial, 4476 (29%) of the 15,502 nursing homes in the target population were eligible for the trial, of which 818 (18%) were randomized. Of the 1,361,122 residents, 91,179 (6.7%) were residents of randomized facilities, 463,703 (34.0%) of eligible non-randomized facilities, and 806,205 (59.3%) of ineligible facilities. In the METRICaL trial, 160 (59%) of the 270 nursing homes in the target population were eligible for the trial, of which 80 (50%) were randomized. Of the 20,262 residents, 973 (34.4%) were residents of randomized facilities, 7431 (36.7%) of eligible non-randomized facilities, and 5858 (28.9%) of ineligible facilities. In the high-dose trial, randomized facilities differed from eligible non-randomized and ineligible facilities by the number of beds (132.5 vs 145.9 and 91.9, respectively), for-profit status (91.8% vs 66.8% and 68.8%), belonging to a nursing home chain (85.8% vs 49.9% and 54.7%), and presence of a special care unit (19.8% vs 25.9% and 14.4%). In the METRICaL trial randomized facilities differed from eligible non-randomized and ineligible facilities by the number of beds (103.7 vs 110.5 and 67.0), resource-poor status (4.6% vs 10.0% and 18.8%), and presence of a special care unit (26.3% vs 33.8% and 10.9%). In both trials, the characteristics of residents in randomized facilities were similar across the three groups.

CONCLUSION

In both trials, facility-level characteristics of randomized nursing homes differed considerably from those of eligible non-randomized and ineligible facilities, while there was little difference in resident-level characteristics across the three groups. Investigators should assess the characteristics of clusters that participate in cluster randomized trials, not just the individuals within the clusters, when examining the applicability of trial results beyond participating clusters.

Guidelines for Data and Safety Monitoring in Pragmatic Randomized Clinical Trials Using Case Studies

Pragmatic randomized clinical trials (pRCTs) have a unique set of considerations for data and safety monitoring. Because of their unconventional trial designs coupled with collection of multilevel data and implementation outcomes in real-world settings, thoughtful consideration is needed on the presentation of the trial design and accruing data to facilitate review and decision-making by the trial's data and safety monitoring board (DSMB). To our knowledge, there is limited information available in practical guidelines for generalists and medical general practitioners on what to monitor and to report to the DSMB during the conduct of pRCTs and what the DSMB should focus on in its review of reports. This article discusses these matters in the context of 3 case studies focusing on a set of critical data and safety monitoring questions that would be of interest to the generalist conducting pRCTs. In considering these questions, we provide tabular and graphical illustrations of how data can be presented to the DSMB while drawing attention to those areas that the DSMB should focus on in its review of the trial. The strategies and viewpoints discussed herein provide practical guidelines and can serve as a resource for the generalist conducting pRCTs.

Key considerations for designing, conducting and analysing a cluster randomized trial

Not only do cluster randomized trials require a larger sample size than individually randomized trials, they also face many additional complexities. The potential for contamination is the most commonly used justification for using cluster randomization, but the risk of contamination should be carefully weighed against the more serious problem of questionable scientific validity in settings with post-randomization identification or recruitment of participants unblinded to the treatment allocation. In this paper we provide some simple guidelines to help researchers conduct cluster trials in a way that minimizes potential biases and maximizes statistical efficiency. The overarching theme of this guidance is that methods that apply to individually randomized trials rarely apply to cluster randomized trials. We recommend that cluster randomization be only used when necessary-balancing the benefits of cluster randomization with its increased risks of bias and increased sample size. Researchers should also randomize at the lowest possible level-balancing the risks of contamination with ensuring an adequate number of randomization units-as well as exploring other options for statistically efficient designs. Clustering should always be allowed for in the sample size calculation; and the use of restricted randomization (and adjustment in the analysis for covariates used in the randomization) should be considered. Where possible, participants should be recruited before randomizing clusters and, when recruiting (or identifying) participants post-randomization, recruiters should be masked to the allocation. In the analysis, the target of inference should align with the research question, and adjustment for clustering and small sample corrections should be used when the trial includes less than about 40 clusters.

A randomized, parallel group, pragmatic comparative-effectiveness trial comparing medication-assisted treatment induction methods in primary care practices: The HOMER study protocol

Opioid use disorder (OUD) represents a public health crisis in the United States. Medication for opioid use disorder (MOUD) with buprenorphine in primary care is a proven OUD treatment strategy. MOUD induction is when patients begin withdrawal and receive the first doses of buprenorphine. Differences between induction methods might influence short-term stabilization, long-term maintenance, and quality of life. This paper describes the protocol for a study designed to: (1) compare short-term stabilization and long-term maintenance treatment engagement in MOUD in patients receiving office, home, or telehealth induction and (2) identify clinically-relevant practice and patient characteristics associated with successful long-term treatment. The study design is a randomized, parallel group, pragmatic comparative effectiveness trial of three care models of MOUD induction in 100 primary care practices in the United States. Eligible patients are at least 16 years old, have been identified by their clinician as having opioid dependence and would benefit from MOUD. Patients will be randomized to one of three induction comparators: office, home, or telehealth induction. Primary outcomes are buprenorphine medication-taking and illicit opioid use at 30, 90, and 270 days post-induction. Secondary outcomes include quality of life and potential mediators of treatment maintenance (intentions, planning, automaticity). Potential moderators include social determinants of health, substance use history and appeal, and executive function. An intent to treat analysis will assess effects of the interventions on long-term treatment, using general/generalized linear mixed models, adjusted for covariates, for the outcomes analysis. Analysis includes practice- and patient-level random effects for hierarchical/longitudinal data. No large-scale, randomized comparative effectiveness research has compared home induction to office or telehealth MOUD induction on long-term outcomes for patients with OUD seen in primary care settings. The results of this study will offer primary care providers evidence and guidance in selecting the most beneficial induction method(s) for specific patients.

Strategies to minimise and monitor biases and imbalances by arm in surgical cluster randomised trials: evidence from ChEETAh, a trial in seven low- and middle-income countries

BACKGROUND

Cluster randomised controlled trials (cRCT) present challenges regarding risks of bias and chance imbalances by arm. This paper reports strategies to minimise and monitor biases and imbalances in the ChEETAh cRCT.

METHODS

ChEETAh was an international cRCT (hospitals as clusters) evaluating whether changing sterile gloves and instruments prior to abdominal wound closure reduces surgical site infection at 30 days postoperative. ChEETAh planned to recruit 12,800 consecutive patients from 64 hospitals in seven low-middle income countries. Eight strategies to minimise and monitor bias were pre-specified: (1) minimum of 4 hospitals per country; (2) pre-randomisation identification of units of exposure (operating theatres, lists, teams or sessions) within clusters; (3) minimisation of randomisation by country and hospital type; (4) site training delivered after randomisation; (5) dedicated 'warm-up week' to train teams; (6) trial specific sticker and patient register to monitor consecutive patient identification; (7) monitoring characteristics of patients and units of exposure; and (8) low-burden outcome-assessment.

RESULTS

This analysis includes 10,686 patients from 70 clusters. The results aligned to the eight strategies were (1) 6 out of 7 countries included ≥ 4 hospitals; (2) 87.1% (61/70) of hospitals maintained their planned operating theatres (82% [27/33] and 92% [34/37] in the intervention and control arms); (3) minimisation maintained balance of key factors in both arms; (4) post-randomisation training was conducted for all hospitals; (5) the 'warm-up week' was conducted at all sites, and feedback used to refine processes; (6) the sticker and trial register were maintained, with an overall inclusion of 98.1% (10,686/10,894) of eligible patients; (7) monitoring allowed swift identification of problems in patient inclusion and key patient characteristics were reported: malignancy (20.3% intervention vs 12.6% control), midline incisions (68.4% vs 58.9%) and elective surgery (52.4% vs 42.6%); and (8) 0.4% (41/9187) of patients refused consent for outcome assessment.

CONCLUSION

cRCTs in surgery have several potential sources of bias that include varying units of exposure and the need for consecutive inclusion of all eligible patients across complex settings. We report a system that monitored and minimised the risks of bias and imbalances by arm, with important lessons for future cRCTs within hospitals.

The iHealth-T2D study: a cluster randomised trial for the prevention of type 2 diabetes amongst South Asians with central obesity and prediabetes-a statistical analysis plan

BACKGROUND

South Asians are at high risk of type 2 diabetes (T2D). Lifestyle modification is effective at preventing T2D amongst South Asians, but the approaches to screening and intervention are limited by high costs, poor scalability and thus low impact on T2D burden. An intensive family-based lifestyle modification programme for the prevention of T2D was developed. The aim of the iHealth-T2D trial is to compare the effectiveness of this programme with usual care.

METHODS

The iHealth-T2D trial is designed as a cluster randomised controlled trial (RCT) conducted at 120 sites across India, Pakistan, Sri Lanka and the UK. A total of 3682 South Asian men and women with age between 40 and 70 years without T2D but at elevated risk for T2D [defined by central obesity (waist circumference ≥ 95 cm in Sri Lanka or ≥ 100 cm in India, Pakistan and the UK) and/or prediabetes (HbA1c ≥ 6.0%)] were included in the trial. Here, we describe in detail the statistical analysis plan (SAP), which was finalised before outcomes were available to the investigators. The primary outcome will be evaluated after 3 years of follow-up after enrolment to the study and is defined as T2D incidence in the intervention arm compared to usual care. Secondary outcomes are evaluated both after 1 and 3 years of follow-up and include biochemical measurements, anthropometric measurements, behavioural components and treatment compliance.

DISCUSSION

The iHealth-T2D trial will provide evidence of whether an intensive family-based lifestyle modification programme for South Asians who are at high risk for T2D is effective in the prevention of T2D. The data from the trial will be analysed according to this pre-specified SAP.

ETHICS AND DISSEMINATION

The trial was approved by the international review board of each participating study site. Study findings will be disseminated through peer-reviewed publications and in conference presentations.

TRIAL REGISTRATION

EudraCT 2016-001,350-18 . Registered on 14 April 2016.

CLINICALTRIALS

gov NCT02949739 . Registered on 31 October 2016.

Performance, Detection, Contamination, Compliance, and Cointervention Biases in Rehabilitation Research: What Are They and How Can They Affect the Results of Randomized Controlled Trials? Basic Information for Junior Researchers and Clinicians

ABSTRACT

Bias is a systematic error that can cause distorted results leading to incorrect conclusions. Intervention bias (i.e., contamination bias, cointervention bias, compliance bias, and performance bias) and detection bias are the most common biases in rehabilitation research. A better understanding of these biases is essential at all stages of research to enhance the quality of evidence in rehabilitation trials. Therefore, this narrative review aims to provide insights to the readers, clinicians, and researchers about contamination, cointervention, compliance, performance, and detection biases and ways of recognizing and mitigating them. The literature selected for this review was obtained mainly by compiling the information from several reviews looking at biases in rehabilitation. In addition, separate searches by biases and looking at reference lists of selected studies as well as using Scopus forward citation for relevant references were used.This review provides several strategies to guard against the impact of bias on study results. Clinicians, researchers, and other stakeholders are encouraged to apply these recommendations when designing and conducting rehabilitation trials.

Successes and lessons learned in database development for national multi-site cancer care delivery research trials: the Alliance for Clinical Trials in Oncology experience

INTRODUCTION

Alliance for Clinical Trials in Oncology (Alliance) coordinated trials utilize Medidata Rave® (Rave) as the primary clinical data capture system. A growing number of innovative and complex cancer care delivery research (CCDR) trials are being conducted within the Alliance with the aims of studying and improving cancer-related care. Because these trials encompass patients, providers, practices, and their interactions, a defining characteristic of CCDR trials is multilevel data collection in pragmatic settings. Consequently, CCDR trials necessitated innovative strategies for database development, centralized data management, and data monitoring in the presence of these real-world multilevel relationships. Having real trial experience in working with community and academic centers, and having recently implemented five CCDR trials in Rave, we are committed to sharing our strategies and lessons learned in implementing such pragmatic trials in oncology.

METHODS

Five Alliance CCDR trials are used to describe our approach to analyzing the database development needs and the novel strategies applied to overcome the unanticipated challenges we encountered. The strategies applied are organized into 3 categories: multilevel (clinic, clinic stakeholder, patient) enrollment, multilevel quantitative and qualitative data capture, including nontraditional data capture mechanisms being applied, and multilevel data monitoring.

RESULTS

A notable lesson learned in each category was (1) to seek long-term solutions when developing the functionality to push patient and non-patient enrollments to their respective Rave study database that affords flexibility if new participant types are later added; (2) to be open to different data collection modalities, particularly if such modalities remove barriers to participation, recognizing that additional resources are needed to develop the infrastructure to exchange data between that modality and Rave; and (3) to facilitate multilevel data monitoring, orient site coordinators to the their trial's multiple study databases, each corresponding to a level in the hierarchy, and remind them to establish the link between patient and non-patient participants in the site-facing NCI web-based enrollment system.

CONCLUSION

Although the challenges due to multilevel data collection in pragmatic settings were surmountable, our shared experience can inform and foster collaborations to collectively build on our past successes and improve on our past failures to address the gaps.

Impact of a phone call with a medical student/general practitioner team on morbidity of chronic patients during the first French COVID-19 lockdown (COVIQuest): a cluster randomised trial

OBJECTIVES

The first COVID-19 lockdown led to a significantly reduced access to healthcare, which may have increased decompensations in frail patients with chronic diseases, especially older patients living with a chronic cardiovascular disease (CVD) or a mental health disorder (MHD). The objective of COVIQuest was to evaluate whether a general practitioner (GP)-initiated phone call to patients with CVD and MHD during the COVID-19 lockdown could reduce the number of hospitalisation(s) over a 1-month period.

DESIGN

This is a cluster randomised controlled trial. Clusters were GPs from eight French regions.

PARTICIPANTS

Patients ≥70 years old with chronic CVD (COVIQuest_CV subtrial) or ≥18 years old with MHD (COVIQuest_MH subtrial).

INTERVENTIONS

A standardised GP-initiated phone call aiming to evaluate patients' need for urgent healthcare, with a control group benefiting from usual care (ie, the contact with the GP was by the patient's initiative).

MAIN OUTCOME MEASURES

Hospital admission within 1 month after the phone call.

RESULTS

In the COVIQuest_CV subtrial, 131 GPs and 1834 patients were included in the intervention group and 136 GPs and 1510 patients were allocated to the control group. Overall, 65 (3.54%) patients were hospitalised in the intervention group vs 69 (4.57%) in the control group (OR 0.82, 95% CI 0.56 to 1.20; risk difference -0.77, 95% CI -2.28 to 0.74). In the COVIQuest_MH subtrial, 136 GPs and 832 patients were included in the intervention group and 131 GPs and 548 patients were allocated to the control group. Overall, 27 (3.25%) patients were hospitalised in the intervention group vs 12 (2.19%) in the control group (OR 1.52, 95% CI 0.82 to 2.81; risk difference 1.38, 95% CI 0.06 to 2.70).

CONCLUSION

A GP-initiated phone call may have been associated with more hospitalisations within 1 month for patients with MHD, but results lack robustness and significance depending on the statistical approach used.

TRIAL REGISTRATION NUMBER

NCT04359875.

Ready for SDM- evaluation of an interprofessional training module in shared decision making - A cluster randomized trial

OBJECTIVE

Ready for SDM was developed in Norway as a comprehensive modularized curriculum for health care providers (HCP). The current study evaluated the efficacy of one of the modules, a 2-hour interprofessional SDM training designed to enhance SDM competencies.

METHODS

A cluster randomized controlled trial was conducted with eight District Psychiatric Centres randomized to wait-list control (CG) or intervention group (IG). Participants and trainers were not blinded to their allocation. The IG received a 2-hour didactic and interactive training, using video examples. The primary outcome was the agreement between the participants' and an expert assessment of patient involvement in a video recorded consultation. The SDM-knowledge score was a secondary outcome.

RESULTS

Compared to the CG (n = 65), the IG (n = 69) judged involvement behavior in a communication example more accurately (mean difference of weighted T, adjusted for age and gender:=-0.098, p = 0.028) and demonstrated better knowledge (mean difference=-0.58; p = 0.014). A sensitivity analysis entering a random effect for cluster turned out not significant.

CONCLUSION

The interprofessional group training can improve HCPs' SDM-competencies.

PRACTICE IMPLICATIONS

Addressing interprofessional teams using SDM communication training could supplement existing SDM training approaches. More research is needed to evaluate the training module's effects as a component of large-scale implementation of SDM.

A first step towards best practice recommendations for the design and statistical analyses of pragmatic clinical trials: a modified Delphi approach

AIM

Pragmatic clinical trials (PCTs) are randomised trials implemented through routine clinical practice, where design parameters of traditional randomised controlled trials are modified to increase generalizability. However, this may introduce statistical challenges. We aimed to identify these challenges and discuss possible solutions leading to best practice recommendations for the design and analysis of PCTs.

METHODS

A modified Delphi method was used to reach consensus among a panel of 11 experts in clinical trials and statistics. Statistical issues were identified in a focused literature review and aggregated with insights and possible solutions from expert collected through a series of survey iterations. Issues were ranked according to their importance.

RESULTS

27 articles were included and combined with experts' insight to generate a list of issues categorized into: participants; recruiting sites; randomisation, blinding and intervention; outcome (selection and measurement); and data analysis. Consensus was reached about the most important issues: risk of participants' attrition; heterogeneity of "usual care" across sites; absence of blinding; use of a subjective endpoint; and data analysis aligned with the trial estimand. Potential issues should be anticipated and preferably be addressed in the trial protocol. The experts provided solutions regarding data collection and data analysis, which were considered of equal importance.

DISCUSSION

A set of important statistical issues in PCTs was identified and approaches were suggested to anticipate and/or minimize these through data analysis. Any impact of choosing a pragmatic design feature should be gauged in the light of the trial estimand.

Digital smartphone intervention to recognise and manage early warning signs in schizophrenia to prevent relapse: the EMPOWER feasibility cluster RCT

BACKGROUND

Relapse is a major determinant of outcome for people with a diagnosis of schizophrenia. Early warning signs frequently precede relapse. A recent Cochrane Review found low-quality evidence to suggest a positive effect of early warning signs interventions on hospitalisation and relapse.

OBJECTIVE

How feasible is a study to investigate the clinical effectiveness and cost-effectiveness of a digital intervention to recognise and promptly manage early warning signs of relapse in schizophrenia with the aim of preventing relapse?

DESIGN

A multicentre, two-arm, parallel-group cluster randomised controlled trial involving eight community mental health services, with 12-month follow-up.

SETTINGS

Glasgow, UK, and Melbourne, Australia.

PARTICIPANTS

Service users were aged > 16 years and had a schizophrenia spectrum disorder with evidence of a relapse within the previous 2 years. Carers were eligible for inclusion if they were nominated by an eligible service user.

INTERVENTIONS

The Early signs Monitoring to Prevent relapse in psychosis and prOmote Wellbeing, Engagement, and Recovery (EMPOWER) intervention was designed to enable participants to monitor changes in their well-being daily using a mobile phone, blended with peer support. Clinical triage of changes in well-being that were suggestive of early signs of relapse was enabled through an algorithm that triggered a check-in prompt that informed a relapse prevention pathway, if warranted.

MAIN OUTCOME MEASURES

The main outcomes were feasibility of the trial and feasibility, acceptability and usability of the intervention, as well as safety and performance. Candidate co-primary outcomes were relapse and fear of relapse.

RESULTS

We recruited 86 service users, of whom 73 were randomised (42 to EMPOWER and 31 to treatment as usual). Primary outcome data were collected for 84% of participants at 12 months. Feasibility data for people using the smartphone application (app) suggested that the app was easy to use and had a positive impact on motivations and intentions in relation to mental health. Actual app usage was high, with 91% of users who completed the baseline period meeting our a priori criterion of acceptable engagement (> 33%). The median time to discontinuation of > 33% app usage was 32 weeks (95% confidence interval 14 weeks to ∞). There were 8 out of 33 (24%) relapses in the EMPOWER arm and 13 out of 28 (46%) in the treatment-as-usual arm. Fewer participants in the EMPOWER arm had a relapse (relative risk 0.50, 95% confidence interval 0.26 to 0.98), and time to first relapse (hazard ratio 0.32, 95% confidence interval 0.14 to 0.74) was longer in the EMPOWER arm than in the treatment-as-usual group. At 12 months, EMPOWER participants were less fearful of having a relapse than those in the treatment-as-usual arm (mean difference -4.29, 95% confidence interval -7.29 to -1.28). EMPOWER was more costly and more effective, resulting in an incremental cost-effectiveness ratio of £3041. This incremental cost-effectiveness ratio would be considered cost-effective when using the National Institute for Health and Care Excellence threshold of £20,000 per quality-adjusted life-year gained.

LIMITATIONS

This was a feasibility study and the outcomes detected cannot be taken as evidence of efficacy or effectiveness.

CONCLUSIONS

A trial of digital technology to monitor early warning signs that blended with peer support and clinical triage to detect and prevent relapse is feasible.

FUTURE WORK

A main trial with a sample size of 500 (assuming 90% power and 20% dropout) would detect a clinically meaningful reduction in relapse (relative risk 0.7) and improvement in other variables (effect sizes 0.3-0.4).

TRIAL REGISTRATION

This trial is registered as ISRCTN99559262.

FUNDING

This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 27. See the NIHR Journals Library website for further project information. Funding in Australia was provided by the National Health and Medical Research Council (APP1095879).

Effects of a gluten-reduced or gluten-free diet for the primary prevention of cardiovascular disease

BACKGROUND

Cardiovascular diseases (CVD) are a major cause of disability and the leading cause of death worldwide. To reduce mortality and morbidity, prevention strategies such as following an optimal diet are crucial. In recent years, low-gluten and gluten-free diets have gained strong popularity in the general population. However, study results on the benefits of a gluten-reduced or gluten-free diet are conflicting, and it is unclear whether a gluten-reduced diet has an effect on the primary prevention of CVD.

OBJECTIVES

To determine the effects of a gluten-reduced or gluten-free diet for the primary prevention of CVD in the general population.

SEARCH METHODS

We systematically searched CENTRAL, MEDLINE, Embase, CINAHL and Web of Science up to June 2021 without language restrictions or restrictions regarding publication status. Additionally, we searched ClinicalTrials.gov for ongoing or unpublished trials and checked reference lists of included studies as well as relevant systematic reviews for additional studies.

SELECTION CRITERIA

We planned to include randomised controlled trials (RCTs) and non-randomised studies of interventions (NRSIs), such as prospective cohort studies, comparing a low-gluten or gluten-free diet or providing advice to decrease gluten consumption with no intervention, diet as usual, or a reference gluten-intake category. The population of interest comprised adults from the general population, including those at increased risk for CVD (primary prevention). We excluded cluster-RCTs, case-control studies, studies focusing on participants with a previous myocardial infarction and/or stroke, participants who have undergone a revascularisation procedure as well as participants with angina or angiographically-defined coronary heart disease, with a confirmed diagnosis of coeliac disease or with type 1 diabetes.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed eligibility of studies in a two-step procedure following Cochrane methods. Risk of bias (RoB) was assessed using the Cochrane risk of bias tool (RoB2) and the 'Risk Of Bias In Non-randomised Studies - of Interventions' (ROBINS-I) tool, and the certainty of evidence was rated using the GRADE approach.

MAIN RESULTS

One RCT and three NRSIs (with an observational design reporting data on four cohorts: Health Professionals Follow-up Study (HPFS), Nurses' Health Study (NHS-I), NHS-II, UK Biobank) met the inclusion criteria. The RCT was conducted in Italy (60 participants, mean age 41 ± 12.1 years), two NRSIs (three cohorts, HPFS, NHS-I, NHS II) were conducted across the USA (269,282 health professionals aged 24 to 75 years) and one NRSI (Biobank cohort) was conducted across the UK (159,265 participants aged 49 to 62 years). Two NRSIs reported that the lowest gluten intake ranged between 0.0 g/day and 3.4 g/day and the highest gluten intake between 6.2 g/day and 38.4 g/day. The NRSI reporting data from the UK Biobank referred to a median gluten intake of 8.5 g/day with an interquartile range from 5.1 g/day to 12.4 g/day without providing low- and high-intake categories. Cardiovascular mortality From a total of 269,282 participants, 3364 (1.3%) died due to cardiovascular events during 26 years of follow-up. Low-certainty evidence may show no association between gluten intake and cardiovascular mortality (adjusted hazard ratio (HR) for low- versus high-gluten intake 1.00, 95% confidence interval (CI) 0.95 to 1.06; 2 NRSIs (3 cohorts)). All-cause mortality From a total of 159,265 participants, 6259 (3.9%) died during 11.1 years of follow-up. Very low-certainty evidence suggested that it is unclear whether gluten intake is associated with all-cause mortality (adjusted HR for low vs high gluten intake 1.00, 95% CI 0.99 to 1.01; 1 NRSI (1 cohort)). Myocardial infarction  From a total of 110,017 participants, 4243 (3.9%) participants developed non-fatal myocardial infarction within 26 years. Low-certainty evidence suggested that gluten intake may not be associated with the development of non-fatal myocardial infarction (adjusted HR for low versus high gluten intake 0.99, 95% CI 0.89 to 1.10; 1 NRSI (2 cohorts)). Lowering gluten intake by 5 g/day also showed no association on the primary prevention of non-fatal and fatal myocardial infarction (composite endpoint) in linear dose-response meta-analyses (adjusted HR 1.02, 95% CI 0.98 to 1.06; 1 NRSI (2 cohorts)). Coronary risk factors  Type 2 diabetes From a total of 202,114 participants, 15,947 (8.0%) developed type 2 diabetes after a follow-up between 22 and 28 years. There was low-certainty evidence that a lower compared with a higher gluten intake may be associated with a slightly increased risk to develop type 2 diabetes (adjusted HR 1.14, 95% CI 1.07 to 1.22; 1 NRSI (3 cohorts)). Furthermore, lowering gluten intake by 5 g/day may be associated with a slightly increased risk to develop type 2 diabetes in linear dose-response meta-analyses (adjusted HR 1.12, 95% CI 1.08 to 1.16; 1 NRSI (3 cohorts)). Blood pressure, low-density lipoprotein level, body mass index (BMI) After six months of follow-up, very low-certainty evidence suggested that it is unclear whether gluten intake affects systolic blood pressure (mean difference (MD) -6.9, 95% CI -17.1 to 3.3 mmHg). There was also no difference between the interventions for diastolic blood pressure (MD -0.8, 95% CI -5.9 to 4.3 mmHg), low-density lipoprotein levels (MD -0.1, 95% CI -0.5 to 0.3 mmol/L) and BMI (MD -0.1, 95% CI -3.3 to 3.1 kg/m²).  No study reported data on adverse events or on other outcomes. Funding sources did not appear to have distorted the results in any of the studies.

AUTHORS' CONCLUSIONS

Very low-certainty evidence suggested that it is unclear whether gluten intake is associated with all-cause mortality. Our findings also indicate that low-certainty evidence may show little or no association between gluten intake and cardiovascular mortality and non-fatal myocardial infarction. Low-certainty evidence suggested that a lower compared with a higher gluten intake may be associated with a slightly increased risk to develop type 2 diabetes - a major cardiovascular risk factor. For other cardiovascular risk factors it is unclear whether there is a difference between a gluten-free and normal diet. Given the limited findings from this review predominantly based on observational studies, no recommendations for practice can be made.

Clarifying selection bias in cluster randomized trials

BACKGROUND

In cluster randomized trials, patients are typically recruited after clusters are randomized, and the recruiters and patients may not be blinded to the assignment. This often leads to differential recruitment and consequently systematic differences in baseline characteristics of the recruited patients between intervention and control arms, inducing post-randomization selection bias. We aim to rigorously define causal estimands in the presence of selection bias. We elucidate the conditions under which standard covariate adjustment methods can validly estimate these estimands. We further discuss the additional data and assumptions necessary for estimating causal effects when such conditions are not met.

METHODS

Adopting the principal stratification framework in causal inference, we clarify there are two average treatment effect (ATE) estimands in cluster randomized trials: one for the overall population and one for the recruited population. We derive analytical formula of the two estimands in terms of principal-stratum-specific causal effects. Furthermore, using simulation studies, we assess the empirical performance of the multivariable regression adjustment method under different data generating processes leading to selection bias.

RESULTS

When treatment effects are heterogeneous across principal strata, the average treatment effect on the overall population generally differs from the average treatment effect on the recruited population. A naïve intention-to-treat analysis of the recruited sample leads to biased estimates of both average treatment effects. In the presence of post-randomization selection and without additional data on the non-recruited subjects, the average treatment effect on the recruited population is estimable only when the treatment effects are homogeneous between principal strata, and the average treatment effect on the overall population is generally not estimable. The extent to which covariate adjustment can remove selection bias depends on the degree of effect heterogeneity across principal strata.

CONCLUSION

There is a need and opportunity to improve the analysis of cluster randomized trials that are subject to post-randomization selection bias. For studies prone to selection bias, it is important to explicitly specify the target population that the causal estimands are defined on and adopt design and estimation strategies accordingly. To draw valid inferences about treatment effects, investigators should (1) assess the possibility of heterogeneous treatment effects, and (2) consider collecting data on covariates that are predictive of the recruitment process, and on the non-recruited population from external sources such as electronic health records.

Interim data monitoring in cluster randomised trials: Practical issues and a case study

BACKGROUND

There is an abundance of guidance for the interim monitoring of individually randomised trials. While methodological literature exists on how to extend these methods to cluster randomised trials, there is little guidance on practical implementation. Cluster trials have many features which make their monitoring needs different. We outline the methodological and practical challenges of interim monitoring of cluster trials; and apply these considerations to a case study.

CASE STUDY

The E-MOTIVE study is an 80-cluster randomised trial of a bundle of interventions to treat postpartum haemorrhage. The proposed data monitoring plan includes (1) monitor sample size assumptions, (2) monitor for evidence of selection bias, and (3) an interim assessment of the primary outcome, as well as monitoring data completeness. The timing of the sample size monitoring is chosen with both consideration of statistical precision and to allow time to recruit more clusters. Monitoring for selection bias involves comparing individual-level characteristics and numbers recruited between study arms to identify any post-randomisation participant identification bias. An interim analysis of outcomes presented with 99.9% confidence intervals using the Haybittle-Peto approach should mitigate any concern regarding the inflation of type-I error. The pragmatic nature of the trial means monitoring for adherence is not relevant, as it is built into a process evaluation.

CONCLUSIONS

The interim analyses of cluster trials have a number of important differences to monitoring individually randomised trials. In cluster trials, there will often be a greater need to monitor nuisance parameters, yet there will often be considerable uncertainty in their estimation. This means the utility of sample size re-estimation can be questionable particularly when there are practical or funding difficulties associated with making any changes to planned sample sizes. Perhaps most importantly interim monitoring has the potential to identify selection bias, particularly in trials with post-randomisation identification or recruitment. Finally, the pragmatic nature of cluster trials might mean that the utility of methods to allow for interim monitoring of outcomes based on statistical testing, or monitoring for adherence to study interventions, are less relevant. Our intention is to facilitate the planning of future cluster randomised trials and to promote discussion and debate to improve monitoring of these studies.

Cluster randomized trials of individual-level interventions were at high risk of bias

OBJECTIVES

To describe the prevalence of risks of bias in cluster-randomized trials of individual-level interventions, according to the Cochrane Risk of Bias tool.

STUDY DESIGN AND SETTING

Review undertaken in duplicate of a random sample of 40 primary reports of cluster-randomized trials of individual-level interventions.

RESULTS

The most common reported reasons for adopting cluster randomization were the need to avoid contamination (17, 42.5%) and practical considerations (14, 35%). Of the 40 trials all but one was assessed as being at risk of bias. A majority (27, 67.5%) were assessed as at risk due to the timing of identification and recruitment of participants; many (21, 52.5%) due to an apparent lack of adequate allocation concealment; and many due to selectively reported results (22, 55%), arising from a mixture of reasons including lack of documentation of primary outcome. Other risks mostly occurred infrequently.

CONCLUSION

Many cluster-randomized trials evaluating individual-level interventions appear to be at risk of bias, mostly due to identification and recruitment biases. We recommend that investigators carefully consider the need for cluster randomization; follow recommended procedures to mitigate risks of identification and recruitment bias; and adhere to good reporting practices including clear documentation of primary outcome and allocation concealment methods.

The SOFIA pilot trial: a cluster-randomized trial of coordinated, co-produced care to reduce mortality and improve quality of life in people with severe mental illness in the general practice setting

Background

People with severe mental illness (SMI) have an increased risk of premature mortality, predominantly due to somatic health conditions. Evidence indicates that primary and tertiary prevention and improved treatment of somatic conditions in patients with SMI could reduce this excess mortality. This paper reports a protocol designed to evaluate the feasibility of a coordinated co-produced care program (SOFIA model, a Danish acronym for Severe Mental Illness and Physical Health in General Practice) in the general practice setting to reduce mortality and improve quality of life in patients with severe mental illness.

Methods

The SOFIA pilot trial is designed as a cluster randomized controlled trial targeting general practices in two regions in Denmark. We aim to include 12 practices, each of which is instructed to recruit up to 15 community-dwelling patients aged 18 and older with SMI. Practices will be randomized by a computer in a ratio of 2:1 to deliver a coordinated care program or usual care during a 6-month study period. A randomized algorithm is used to perform randomization. The coordinated care program includes educational training of general practitioners and their clinical staff educational training of general practitioners and their clinical staff, which covers clinical and diagnostic management and focus on patient-centered care of this patient group, after which general practitioners will provide a prolonged consultation focusing on individual needs and preferences of the patient with SMI and a follow-up plan if indicated. The outcomes will be parameters of the feasibility of the intervention and trial methods and will be assessed quantitatively and qualitatively. Assessments of the outcome parameters will be administered at baseline, throughout, and at end of the study period.

Discussion

If necessary the intervention will be revised based on results from this study. If delivery of the intervention, either in its current form or after revision, is considered feasible, a future, definitive trial to determine the effectiveness of the intervention in reducing mortality and improving quality of life in patients with SMI can take place. Successful implementation of the intervention would imply preliminary promise for addressing health inequities in patients with SMI.

Trial registration

The trial was registered in Clinical Trials as of November 5, 2020, with registration number NCT04618250.

Protocol version: January 22, 2021; original version

Is randomized trial design adapted to population health intervention research?

Randomized trials are frequently used in clinical research and considered the gold standard, but they are less common in population health intervention research (PHIR). We discuss issues that are sometimes shared and sometimes distinct between PHIR and clinical research, notably the randomization unit, design, standardization of the intervention, outcome(s) and ethical issues. In the end, both PHIR and clinical research share the common aim of assessing interventions, and randomized trials should be more widely used in PHIR, provided that how they are planned and conducted is adapted to the PHIR context.

Effectiveness of a 'do not interrupt' vest intervention to reduce medication errors during medication administration: a multicenter cluster randomized controlled trial

Background

The use of a ‘do not interrupt’ vest during medication administration rounds is recommended but there have been no controlled randomized studies to evaluate its impact on reducing administration errors. We aimed to evaluate the impact of wearing such a vest on reducing such errors. The secondary objectives were to evaluate the types and potential clinical impact of errors, the association between errors and several risk factors (such as interruptions), and nurses’ experiences.

Methods

This was a multicenter, cluster, controlled, randomized study (March–July 2017) in 29 adult units (4 hospitals). Data were collected by direct observation by trained observers. All nurses from selected units were informed. A ‘Do not interrupt’ vest was implemented in all units of the experimental group. A poster was placed at the entrance of these units to inform patients and relatives. The main outcome was the administration error rate (number of Opportunities for Error (OE), calculated as one or more errors divided by the Total Opportunities for Error (TOE) and multiplied by 100).

Results

We enrolled 178 nurses and 1346 patients during 383 medication rounds in 14 units in the experimental group and 15 units in the control group. During the intervention period, the administration error rates were 7.09% (188 OE with at least one error/2653 TOE) for the experimental group and 6.23% (210 OE with at least one error/3373 TOE) for the control group (p = 0.192). Identified risk factors (patient age, nurses’ experience, nurses’ workload, unit exposition, and interruption) were not associated with the error rate. The main error type observed for both groups was wrong dosage-form. Most errors had no clinical impact for the patient and the interruption rates were 15.04% for the experimental group and 20.75% for the control group.

Conclusions

The intervention vest had no impact on medication administration error or interruption rates. Further studies need to be performed taking into consideration the limitations of our study and other risk factors associated with other interventions, such as nurse’s training and/or a barcode system.

Trial registration

The PERMIS study protocol (V2–1, 11/04/2017) was approved by institutional review boards and ethics committees (CPP Ile de France number 2016-A00211–50, CNIL 21/03/2017, CCTIRS 11/04/2016). It is registered at ClinicalTrials.gov (registration number: NCT03062852, date of first registration: 23/02/2017).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12912-021-00671-7.

A collaborative, computer-assisted, psycho-educational intervention for depressed patients with chronic disease at primary care: protocol for a cluster randomized controlled trial

BACKGROUND

Depression and chronic diseases are frequently comorbid public health problems. However, clinical guidelines often fail to consider comorbidities. This study protocol describes a cluster randomized trial (CRT) aimed to compare the effectiveness of a collaborative, computer-assisted, psycho-educational intervention versus enhanced usual care (EUC) in the treatment of depressed patients with hypertension and/or diabetes in primary care clinics (PCC) in Santiago, Chile.

METHODS

Two-arm, single-blind, CRT carried out at two municipalities in Santiago, Chile. Eight PCC will be randomly assigned (1:1 ratio within each municipality, 4 PCC in each municipality) to the INTERVENTION or EUC. A total of 360 depressed patients, aged at least 18 years, with Patient Health Questionnaire-9 Item [PHQ-9] scores ≥15, and enrolled in the Cardiovascular Health Program at the participating PCC. Patients with alcohol/substance abuse; current treatment for depression, bipolar disorder, or psychosis; illiteracy; severe impairment; and resident in long-term care facilities, will be excluded. Patients in both arms will be invited to use the Web page of the project, which includes basic health education information. Patients in the INTERVENTION will receive eight sessions of a computer-assisted, psycho-educational intervention delivered by trained therapists, a structured telephone calls to monitor progress, and usual medical care for chronic diseases. Therapists will receive biweekly and monthly supervision by psychologist and psychiatrist, respectively. A monthly meeting will be held between the PCC team and a member of the research team to ensure continuity of care. Patients in EUC will receive depression treatment according to clinical guidelines and usual medical care for chronic diseases. Outcome assessments will be conducted at 3, 6, and 12 months after enrollment. The primary outcome will be depression improvement at 6 months, defined as ≥50% reduction in baseline PHQ-9 scores. Intention-to-treat analyses will be performed.

DISCUSSION

This study will be one of the first to provide evidence for the effectiveness of a collaborative, computer-assisted, psycho-educational intervention for depressed patients with chronic disease at primary care in a Latin American country.

TRIAL REGISTRATION

retrospectively registered in ClinicalTrials.gov , first posted: November 3, 2020, under identifier: NCT04613076 .

The role and challenges of cluster randomised trials for global health

Evaluating whether an intervention works when trialled in groups of individuals can pose complex challenges for clinical research. Cluster randomised controlled trials involve the random allocation of groups or clusters of individuals to receive an intervention, and they are commonly used in global health research. In this paper, we describe the potential reasons for the increasing popularity of cluster trials in low-income and middle-income countries. We also draw on key areas of global health research for an assessment of common trial planning practices, and we address their methodological shortcomings and pitfalls. Lastly, we discuss alternative approaches for population-level intervention trials that could be useful for research undertaken in low-income and middle-income countries for situations in which the use of cluster randomisation might not be appropriate.

Designing and undertaking randomised implementation trials: guide for researchers

Implementation science is the study of methods to promote the systematic uptake of evidence based interventions into practice and policy to improve health. Despite the need for high quality evidence from implementation research, randomised trials of implementation strategies often have serious limitations. These limitations include high risks of bias, limited use of theory, a lack of standard terminology to describe implementation strategies, narrowly focused implementation outcomes, and poor reporting. This paper aims to improve the evidence base in implementation science by providing guidance on the development, conduct, and reporting of randomised trials of implementation strategies. Established randomised trial methods from seminal texts and recent developments in implementation science were consolidated by an international group of researchers, health policy makers, and practitioners. This article provides guidance on the key components of randomised trials of implementation strategies, including articulation of trial aims, trial recruitment and retention strategies, randomised design selection, use of implementation science theory and frameworks, measures, sample size calculations, ethical review, and trial reporting. It also focuses on topics requiring special consideration or adaptation for implementation trials. We propose this guide as a resource for researchers, healthcare and public health policy makers or practitioners, research funders, and journal editors with the goal of advancing rigorous conduct and reporting of randomised trials of implementation strategies.

Evaluation of a multi-component, non-pharmacological intervention to prevent and reduce sleep disturbances in people with dementia living in nursing homes (MoNoPol-sleep): study protocol for a cluster-randomized exploratory trial

BACKGROUND

Sleep problems are highly prevalent in people with dementia. Nevertheless, there is no "gold standard" intervention to prevent or reduce sleep problems in people with dementia. Existing interventions are characterized by a pronounced heterogeneity as well as insufficient knowledge about the possibilities and challenges of implementation. The aim of this study is to pilot and evaluate the effectiveness of a newly developed complex intervention to prevent and reduce sleep problems in people with dementia living in nursing homes.

METHODS

This study is a parallel group cluster-randomized controlled trial. The intervention consists of six components: (1) the assessment of established sleep-promoting interventions and an appropriate environment in the participating nursing homes, (2) the implementation of two "sleep nurses" as change agents per nursing home, (3) a basic education course for nursing staff: "Sleep problems in dementia", (4) an advanced education course for nursing staff: "Tailored problem-solving" (two workshops), (5) workshops: "Development of an institutional sleep-promoting concept" (two workshops with nursing management and sleep nurses) and (6) written information and education material (e.g. brochure and "One Minute Wonder" poster). The intervention will be performed over a period of 16 weeks and compared with usual care in the control group. Overall, 24 nursing homes in North, East and West Germany will be included and randomized in a 1:1 ratio. The primary outcome is the prevalence of sleep problems in people with dementia living in nursing homes. Secondary outcomes are quality of life, quality of sleep, daytime sleepiness and agitated behavior of people with dementia, as well as safety parameters like psychotropic medication, falls and physical restraints. The outcomes will be assessed using a mix of instruments based on self- and proxy-rating. A cost analysis and a process evaluation will be performed in conjunction with the study.

CONCLUSIONS

It is expected that the intervention will reduce the prevalence of sleep problems in people with dementia, thus not only improving the quality of life for people with dementia, but also relieving the burden on nursing staff caused by sleep problems.

TRIAL REGISTRATION

Current controlled trials: ISRCTN36015309 . Date of registration: 06/11/2020.

Intent-to-treat analysis of cluster randomized trials when clusters report unidentifiable outcome proportions

BACKGROUND

Cluster randomized trials are designed to evaluate interventions at the cluster or group level. When clusters are randomized but some clusters report no or non-analyzable data, intent-to-treat analysis, the gold standard for the analysis of randomized controlled trials, can be compromised. This article presents a very flexible statistical methodology for cluster randomized trials whose outcome is a cluster-level proportion (e.g. proportion from a cluster reporting an event) in the setting where clusters report non-analyzable data (which in general could be due to nonadherence, dropout, missingness, etc.). The approach is motivated by a previously published stratified randomized controlled trial called, "The Randomized Recruitment Intervention Trial (RECRUIT)," designed to examine the effectiveness of a trust-based continuous quality improvement intervention on increasing minority recruitment into clinical trials (ClinicalTrials.gov Identifier: NCT01911208).

METHODS

The novel approach exploits the use of generalized estimating equations for cluster-level reports, such that all clusters randomized at baseline are able to be analyzed, and intervention effects are presented as risk ratios. Simulation studies under different outcome missingness scenarios and a variety of intra-cluster correlations are conducted. A comparative analysis of the method with imputation and per protocol approaches for RECRUIT is presented.

RESULTS

Simulation results show the novel approach produces unbiased and efficient estimates of the intervention effect that maintain the nominal type I error rate. Application to RECRUIT shows similar effect sizes when compared to the imputation and per protocol approach.

CONCLUSION

The article demonstrates that an innovative bivariate generalized estimating equations framework allows one to implement an intent-to-treat analysis to obtain risk ratios or odds ratios, for a variety of cluster randomized designs.

Incomparability of treatment groups is often blindly ignored in randomised controlled trials - a post hoc analysis of baseline characteristic tables

OBJECTIVES

Randomisation is often believed to lead to baseline comparability of treatment groups in controlled trials. This study aims to challenge this popular belief, which is relevant in expectation- but not necessarily in realisation.

STUDY DESIGN AND SETTING

After presenting an overview of methods for assessing baseline comparability of treatment groups in randomised controlled trials (RCTs), we reviewed RCTs published over 1 year in three high-impact medical journals. We extracted data regarding the methods used to evaluate baseline comparability. To quantify baseline balance, we calculated post hoc standardised mean differences (SMDs) in baseline characteristics reported in these trials.

RESULTS

Amongst 142 RCTs, 120 (84.5%) claimed that baseline comparability was achieved. However, 81 RCTs (57%) did not report how they assessed this balance. The rest (61 RCTs, 43%) used traditional statistical tests, which are deemed inappropriate for balance checking. Our post hoc calculation of SMDs showed that 49 (34.5%) RCTs had at least one baseline variable, which might have been strongly unbalanced (i.e., SMD ≥25%) across treatment groups.

CONCLUSION

Baseline incomparability of treatment groups in RCTs is often blindly ignored. We suggest it be thoroughly evaluated and transparently reported, using the standardised mean difference or other proper balance metrics.

Feasibility cluster randomised controlled trial evaluating a theory-driven group-based complex intervention versus usual physiotherapy to support self-management of osteoarthritis and low back pain (SOLAS)

BACKGROUND

The self-management of osteoarthritis (OA) and low back pain (LBP) through activity and skills (SOLAS) theory-driven group-based complex intervention was developed primarily for the evaluation of its acceptability to patients and physiotherapists and the feasibility of trial procedures, to inform the potential for a definitive trial.

METHODS

This assessor-blinded multicentre two-arm parallel cluster randomised controlled feasibility trial compared the SOLAS intervention to usual individual physiotherapy (UP; pragmatic control group). Patients with OA of the hip, knee, lumbar spine and/or chronic LBP were recruited in primary care physiotherapy clinics (i.e. clusters) in Dublin, Ireland, between September 2014 and November 2015. The primary feasibility objectives were evaluated using quantitative methods and individual telephone interviews with purposive samples of participants and physiotherapists. A range of secondary outcomes were collected at baseline, 6 weeks (behaviour change only), 2 months and 6 months to explore the preliminary effects of the intervention. Analysis was by intention-to-treat according to participants' cluster allocation and involved descriptive analysis of the quantitative data and inductive thematic analysis of the qualitative interviews. A linear mixed model was used to contrast change over time in participant secondary outcomes between treatment arms, while adjusting for study waves and clusters.

RESULTS

Fourteen clusters were recruited (7 per trial arm), each cluster participated in two waves of recruitment, with the average cluster size below the target of six participants (intervention: mean (SD) = 4.92 (1.31), range 2-7; UP: mean (SD) = 5.08 (2.43), range 1-9). One hundred twenty participants (83.3% of n = 144 expected) were recruited (intervention n = 59; UP n = 61), with follow-up data obtained from 80.8% (n = 97) at 6 weeks, 84.2% (n = 101) at 2 months and 71.7% (n = 86) at 6 months. Most participants received treatment as allocated (intervention n = 49; UP n = 54). The qualitative interviews (12 participants; 10 physiotherapists (PTs) found the intervention and trial procedures acceptable and appropriate, with minimal feasible adaptations required. Linear mixed methods showed improvements in most secondary outcomes at 2 and 6 months with small between-group effects.

CONCLUSIONS

While the SOLAS intervention and trial procedures were acceptable to participants and PTs, the recruitment of enough participants is the biggest obstacle to a definitive trial.

TRIAL REGISTRATION

ISRCTN ISRCTN49875385 . Registered on 26 March 2014.

Engaging Caregivers in Health-Related Housing Decisions for Older Adults With Cognitive Impairment: A Cluster Randomized Trial

Background and Objectives

Informal caregivers are rarely as involved as they want to be in the housing decisions of cognitively impaired older adults. Lack of awareness of available options and their benefits and risks may lead to decisions that do not reflect older adults’ preferences, and to guilt and regret. We assessed the effect of training home care teams in interprofessional shared decision-making (SDM) on the proportion of caregivers who report being active in this decision.

Research Design and Methods

In a two-arm pragmatic cluster randomized trial with home care teams working in health centers in the Province of Quebec, we randomized health centers to receive training in interprofessional SDM (intervention) or not (control). Eligible caregivers had made a housing decision for a cognitively impaired adult aged 65 years or older who was receiving services from a home care team. The primary outcome was the proportion of caregivers reporting an active role in decision making. We performed intention-to-treat multilevel analysis.

Results

We consecutively enrolled a random group of 16 health centers and recruited 309 caregivers, among whom 296 were included in the analysis. In the intervention arm, the proportion of caregivers reporting an active role in decision making increased by 12% (95% CI −2% to 27%; p = .10). After removal of an influential cluster outlier, the proportion increased to 18% (95% CI: 7%–29%; p < .01).

Discussion and Implications

Training home care teams in interprofessional SDM increased caregiver involvement in health-related housing decisions for cognitively impaired older adults.

Participation in adherence clubs and on-time drug pickup among HIV-infected adults in Zambia: A matched-pair cluster randomized trial

BACKGROUND

Current models of HIV service delivery, with frequent facility visits, have led to facility congestion, patient and healthcare provider dissatisfaction, and suboptimal quality of services and retention in care. The Zambian urban adherence club (AC) is a health service innovation designed to improve on-time drug pickup and retention in HIV care through off-hours facility access and pharmacist-led group drug distribution. Similar models of differentiated service delivery (DSD) have shown promise in South Africa, but observational analyses of these models are prone to bias and confounding. We sought to evaluate the effectiveness and implementation of ACs in Zambia using a more rigorous study design.

METHODS AND FINDINGS

Using a matched-pair cluster randomized study design (ClinicalTrials.gov: NCT02776254), 10 clinics were randomized to intervention (5 clinics) or control (5 clinics). At each clinic, between May 19 and October 27, 2016, a systematic random sample was assessed for eligibility (HIV+, age ≥ 14 years, on ART >6 months, not acutely ill, CD4 count not <200 cells/mm3) and willingness to participate in an AC. Clinical and antiretroviral drug pickup data were obtained through the existing electronic medical record. AC meeting attendance data were collected at intervention facilities prospectively through October 28, 2017. The primary outcome was time to first late drug pickup (>7 days late). Intervention effect was estimated using unadjusted Kaplan-Meier survival curves and a Cox proportional hazards model to derive an adjusted hazard ratio (aHR). Medication possession ratio (MPR) and implementation outcomes (adoption, acceptability, appropriateness, feasibility, and fidelity) were additionally evaluated as secondary outcomes. Baseline characteristics were similar between 571 intervention and 489 control participants with respect to median age (42 versus 41 years), sex (62% versus 66% female), median time since ART initiation (4.8 versus 5.0 years), median CD4 count at study enrollment (506 versus 533 cells/mm3), and baseline retention (53% versus 55% with at least 1 late drug pickup in previous 12 months). The rate of late drug pickup was lower in intervention participants compared to control participants (aHR 0.26, 95% CI 0.15-0.45, p < 0.001). Median MPR was 100% in intervention participants compared to 96% in control participants (p < 0.001). Although 18% (683/3,734) of AC group meeting visits were missed, on-time drug pickup (within 7 days) still occurred in 51% (350/683) of these missed visits through alternate means (use of buddy pickup or early return to the facility). Qualitative evaluation suggests that the intervention was acceptable to both patients and providers. While patients embraced the convenience and patient-centeredness of the model, preference for traditional adherence counseling and need for greater human resources influenced intervention appropriateness and feasibility from the provider perspective. The main limitations of this study were the small number of clusters, lack of viral load data, and relatively short follow-up period.

CONCLUSIONS

ACs were found to be an effective model of service delivery for reducing late ART drug pickup among HIV-infected adults in Zambia. Drug pickup outside of group meetings was relatively common and underscores the need for DSD models to be flexible and patient-centered if they are to be effective.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02776254.

Effect on thromboprophylaxis among hospitalized patients using a system-wide multifaceted quality improvement intervention: Rationale and design for a multicenter cluster randomized clinical trial in China

BACKGROUND

Venous thromboembolism (VTE) is a life-threatening disease that can affect each hospitalized patient. But the current in-hospital thromboprophylaxis remains suboptimal and there exists a large gap between clinical practice and guideline-recommended care in China.

METHODS

To facilitate implementation of guideline recommendations, we conduct a multicenter, adjudicator-blinded, cluster-randomized clinical trial, aiming to assess the effectiveness of a system-wide multifaceted quality improvement (QI) strategy on VTE prophylaxis improvement and thromboembolism reduction in clinical setting. Hospitals are randomized into intervention or control group. In intervention group, hospitals receive the concept of appropriate in-hospital thromboprophylaxis plus a multifaceted QI which encompasses four components: (1) an electronic alert combining computer-based clinical decision support system and electronic reminders, (2) appropriate prophylaxis based on dynamic VTE and bleeding risk assessments, (3) periodical audit and interactive feedback on performance, (4) strengthened training and patient education. In control, hospitals receive the concept of recommended prophylaxis alone without QI. Thromboprophylaxis will be at the discretion of hospitals and conducted as usual. With a final sample size of 5760 hospitalized patients in 32 hospitals on mainland China, this trial will examine the effect of QI on improvement in thromboprophylaxis and patient-centered outcomes. This is an open-label trial that patients and healthcare professionals will know group allocation after enrollment, but endpoint adjudicators and statisticians will be blinded. RCT# NCT04211181 CONCLUSIONS: The system-wide multifaceted QI intervention is expected to facilitate implementation of recommended VTE prophylaxis in hospital, thereafter reducing VTE incidence and relevant adverse events among hospitalized patients in China.

Reflection on modern methods: when is a stepped-wedge cluster randomized trial a good study design choice?

The stepped-wedge cluster randomized trial (SW-CRT) involves the sequential transition of clusters (such as hospitals, public health units or communities) from control to intervention conditions in a randomized order. The use of the SW-CRT is growing rapidly. Yet the SW-CRT is at greater risks of bias compared with the conventional parallel cluster randomized trial (parallel-CRT). For this reason, the CONSORT extension for SW-CRTs requires that investigators provide a clear justification for the choice of study design. In this paper, we argue that all other things being equal, the SW-CRT is at greater risk of bias due to misspecification of the secular trends at the analysis stage. This is particularly problematic for studies randomizing a small number of heterogeneous clusters. We outline the potential conditions under which an SW-CRT might be an appropriate choice. Potentially appropriate and often overlapping justifications for conducting an SW-CRT include: (i) the SW-CRT provides a means to conduct a randomized evaluation which otherwise would not be possible; (ii) the SW-CRT facilitates cluster recruitment as it enhances the acceptability of a randomized evaluation either to cluster gatekeepers or other stakeholders; (iii) the SW-CRT is the only feasible design due to pragmatic and logistical constraints (for example the roll-out of a scare resource); and (iv) the SW-CRT has increased statistical power over other study designs (which will include situations with a limited number of clusters). As the number of arguments in favour of an SW-CRT increases, the likelihood that the benefits of using the SW-CRT, as opposed to a parallel-CRT, outweigh its risks also increases. We argue that the mere popularity and novelty of the SW-CRT should not be a factor in its adoption. In situations when a conventional parallel-CRT is feasible, it is likely to be the preferred design.

Challenges in Protocol Development and Interpretation of the Schistosomiasis Consortium for Operational Research and Evaluation Intervention Studies

In 2010, the Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) began the design of randomized controlled trials to compare different strategies for praziquantel mass drug administration, whether for gaining or sustaining control of schistosomiasis or for approaching local elimination of Schistosoma transmission. The goal of this operational research was to expand the evidence base for policy-making for regional and national control of schistosomiasis in sub-Saharan Africa. Over the 10-year period of its research programs, as SCORE operational research projects were implemented, their scope and scale posed important challenges in terms of research performance and the final interpretation of their results. The SCORE projects yielded valuable data on program-level effectiveness and strengths and weaknesses in performance, but in most of the trials, a greater-than-expected variation in community-level responses to assigned schedules of mass drug administration meant that identification of a dominant control strategy was not possible. This article critically reviews the impact of SCORE’s cluster randomized study design on performance and interpretation of large-scale operational research such as ours.

Cluster over individual randomization: are study design choices appropriately justified? Review of a random sample of trials

Background:

Novel rationales for randomizing clusters rather than individuals appear to be emerging from the push for more pragmatic trials, for example, to facilitate trial recruitment, reduce the costs of research, and improve external validity. Such rationales may be driven by a mistaken perception that choosing cluster randomization lessens the need for informed consent. We reviewed a random sample of published cluster randomized trials involving only individual-level health care interventions to determine (a) the prevalence of reporting a rationale for the choice of cluster randomization; (b) the types of explicit, or if absent, apparent rationales for the use of cluster randomization; (c) the prevalence of reporting patient informed consent for study interventions; and (d) the types of justifications provided for waivers of consent. We considered cluster randomized trials for evaluating exclusively the individual-level health care interventions to focus on clinical trials where individual randomization is only theoretically possible and where there is a general expectation of informed consent.

Methods:

A random sample of 40 cluster randomized trials were identified by implementing a validated electronic search filter in two electronic databases (Ovid MEDLINE and Embase), with two reviewers independently extracting information from each trial. Inclusion criteria were the following: primary report of a cluster randomized trial, evaluating exclusively an individual-level health care intervention, published between 2007 and 2016, and conducted in Canada, the United States, European Union, Australia, or low- and middle-income country settings.

Results:

Twenty-five trials (62.5%, 95% confidence interval = 47.5%–77.5%) reported an explicit rationale for the use of cluster randomization. The most commonly reported rationales were those with logistical or administrative convenience (15 trials, 60%) and those that need to avoid contamination (13 trials, 52%); five trials (20%) were cited rationales related to the push for more pragmatic trials. Twenty-one trials (52.5%, 95% confidence interval = 37%–68%) reported written informed consent for the intervention, two (5%) reported verbal consent, and eight (20%) reported waivers of consent, while in nine trials (22.5%) consent was unclear or not mentioned. Reported justifications for waivers of consent included that study interventions were already used in clinical practice, patients were not randomized individually, and the need to facilitate the pragmatic nature of the trial. Only one trial reported an explicit and appropriate justification for waiver of consent based on minimum criteria in international research ethics guidelines, namely, infeasibility and minimal risk.

Conclusion:

Rationales for adopting cluster over individual randomization and for adopting consent waivers are emerging, related to the need to facilitate pragmatic trials. Greater attention to clear reporting of study design rationales, informed consent procedures, as well as justification for waivers is needed to ensure that such trials meet appropriate ethical standards.

Bidirectional relationships in the development of internalising symptoms and alcohol use in adolescence

INTRODUCTION AND AIMS

Previous literature has demonstrated an inconsistent relationship between alcohol use and internalising symptoms (anxiety, depression) in youth. This study aimed to clarify this link examining the bidirectional relationships between internalising symptoms and alcohol use in a community sample of adolescents, taking into account the effect of gender and externalising symptoms.

DESIGN AND METHODS

Parallel latent growth models were run to prospectively explore the bidirectional relationships between internalising symptoms and alcohol use when assessed five times over 2 years, among 1557 (67% female) adolescents from age 13.5 years.

RESULTS

Results showed that higher initial levels of internalising symptoms predicted increasing alcohol use frequency; however, this association was no longer significant once externalising symptoms and gender were accounted for. No bidirectional associations between internalising symptoms and alcohol use were found.

DISCUSSION AND CONCLUSIONS

This study adds to the literature examining the bidirectional relationships between internalising symptoms and alcohol use in adolescence. Findings highlight the importance of both gender and externalising symptoms in the development of this type of comorbidity and may help explain discrepant findings in the existing literature. Future prevention efforts for internalising problems and alcohol use should consider gender and externalising symptoms.

Effectiveness of Group Problem Management Plus (Group-PM+) for adults affected by humanitarian crises in Nepal: study protocol for a cluster randomized controlled trial

BACKGROUND

Globally, the lack of availability of psychological services for people exposed to adversities has led to the development of a range of scalable psychological interventions with features that enable better scale-up. Problem Management Plus (PM+) is a brief intervention of five sessions that can be delivered by non-specialists. It is designed for people in communities in low- and middle-income countries (LMIC) affected by any kind of adversity. Two recent randomized controlled trials in Pakistan and Kenya demonstrated the effectiveness of individually delivered PM+. A group version of PM+ has been developed to make the intervention more scalable and acceptable. This paper describes the protocol for a cluster randomized controlled trial (c-RCT) on locally adapted Group PM+ in Nepal.

METHODS/DESIGN

This c-RCT will compare Group PM+ to enhanced usual care (EUC) in participants with high levels of psychological distress recruited from the community. The study is designed as a two-arm, single-blind c-RCT that will be conducted in a community-based setting in Morang, a flood affected district in Eastern Nepal. Randomization will occur at ward level, the smallest administrative level in Nepal, with 72 enrolled wards allocated to Group PM+ or to EUC (ratio 1:1). Group PM+ consists of five approximately 2.5-h sessions, in which participants are taught techniques to manage their stressors and problems, and is delivered by trained and supervised community psychosocial workers (CPSWs). EUC consists of a family meeting with (a) basic information on adversity and mental health, (b) benefits of getting support, (c) information on seeking services from local health facilities with mhGAP-trained staff. The primary outcome measure is levels of individual psychological distress at endline (equivalent to 20 ± 1 weeks after baseline), measured by the General Health Questionnaire (GHQ-12). Secondary outcome measures include levels of functioning, depressive symptoms, post-traumatic stress disorder symptoms, levels of social support, somatic symptoms, and ways of coping. We hypothesize that skills acquired will mediate any impact of the intervention.

DISCUSSION

This c-RCT will contribute to the growing evidence-base for transdiagnostic psychological interventions delivered by non-specialists for people in communities affected by adversity. If Group PM+ is proven effective, the intervention manual will be released for use, giving the opportunity for further adaptation and implementation of the intervention in diverse settings with communities that require better access to psychological interventions.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03747055.

Challenges in Implementing Hospice Clinical Trials: Preserving Scientific Integrity While Facing Change

BACKGROUND/AIMS

Numerous changes can occur between the original design plans for clinical trials, the submission of funding proposals, and the implementation of the clinical trial. In the hospice setting, environmental changes can present significant obstacles, which require changes to the original plan designs, recruitment, and staffing. The purpose of the study was to share lessons and problem-solving strategies that can assist in future hospice trials.

METHODS

This study uses one hospice clinical trial as an exemplar to demonstrate challenges for clinical trial research in this setting. Using preliminary data collected during the first months of a trial, the research team details the many ways their current protocol reflects changes from the originally proposed plans. Experiences are used as an exemplar to address the following questions: 1) How do research environments change between the initial submission of a funding proposal and the eventual award? 2) How can investigators maintain the integrity of the research and accommodate unexpected changes in the research environment?

RESULTS

The changing environment within the hospice setting required design, sampling, and recruitment changes within the first year. The decision-making process resulted in a stronger design with greater generalization. As a result of necessary protocol changes, the study results are positioned to be translational following the study conclusion.

CONCLUSION

Researchers would do well to review their protocol and statistics early in a clinical trial. They should be prepared for adjustments to accommodate market and environmental changes outside their control. Ongoing data monitoring, specifically related to recruitment, is advised.

The Invested in Diabetes Study Protocol: a cluster randomized pragmatic trial comparing standardized and patient-driven diabetes shared medical appointments

Background

Shared medical appointments (SMAs) have been shown to be an efficient and effective strategy for providing diabetes self-management education and self-management support. SMA features vary and it is not known which features are most effective for different patients and practice settings. The Invested in Diabetes study tests the comparative effectiveness of SMAs with and without multidisciplinary care teams and patient topic choice for improving patient-centered and clinical outcomes related to diabetes.

Methods

This study compares the effectiveness of two SMA approaches using the Targeted Training for Illness Management (TTIM) curriculum. Standardized SMAs are led by a health educator with a set order of TTIM topics. Patient-driven SMAs are delivered collaboratively by a multidisciplinary care team (health educator, medical provider, behavioral health provider, and a peer mentor); patients select the order and emphasis on TTIM topics. Invested in Diabetes is a cluster randomized pragmatic trial involving approximately 1440 adult patients with type 2 diabetes. Twenty primary care practices will be randomly assigned to either standardized or patient-driven SMAs. A mixed-methods evaluation will include quantitative (practice- and patient-level data) and qualitative (practice and patient interviews, observation) components. The primary patient-centered outcome is diabetes distress. Secondary outcomes include autonomy support, self-management behaviors, clinical outcomes, patient reach, and practice-level value and sustainability.

Discussion

Practice and patient stakeholder input guided protocol development for this pragmatic trial comparing SMA approaches. Implementation strategies from the enhanced Replicating Effective Programs framework will help ensure practices maintain fidelity to intervention protocols while tailoring workflows to their settings. Invested in Diabetes will contribute to the literature on chronic illness management and implementation science using the RE-AIM model.

Trial registration

ClinicalTrials.gov, NCT03590041. Registered on 5 July 2018.

Impact of baseline covariate imbalance on bias in treatment effect estimation in cluster randomized trials: Race as an example

Individual-level baseline covariate imbalance could happen more frequently in cluster randomized trials, and may influence the observed treatment effect. Using computer and real-data simulations, this paper quantifies the extent and impact of covariate imbalance on the estimated treatment effect for both continuous and binary outcomes, and relates it to the degree of imbalance for different numbers of clusters, cluster sizes, and covariate intraclass correlation coefficients. We focused on the impact of race as a covariate, given the emphasis of regulatory and funding bodies on understanding the influence of demographic characteristics on treatment effectiveness. We found that bias in the treatment effect is proportional to both the degree of baseline covariate imbalance and the covariate effect size. Larger numbers of clusters result in lower covariate imbalance, and increasing cluster size is less effective in reducing imbalance compared to increasing the number of clusters. Models adjusted for important baseline confounders are superior to unadjusted models for minimizing bias in both model-based simulations and an innovative simulation based on real clinical trial data. Higher outcome intraclass correlation coefficients did not affect bias but resulted in greater variance in treatment estimates.

Effectiveness of a scalable group-based education and monitoring program, delivered by health workers, to improve control of hypertension in rural India: A cluster randomised controlled trial

BACKGROUND

New methods are required to manage hypertension in resource-poor settings. We hypothesised that a community health worker (CHW)-led group-based education and monitoring intervention would improve control of blood pressure (BP).

METHODS AND FINDINGS

We conducted a baseline community-based survey followed by a cluster randomised controlled trial of people with hypertension in 3 rural regions of South India, each at differing stages of epidemiological transition. Participants with hypertension, defined as BP ≥ 140/90 mm Hg or taking antihypertensive medication, were advised to visit a doctor. In each region, villages were randomly assigned to intervention or usual care (UC) in a 1:2 ratio. In intervention clusters, trained CHWs delivered a group-based intervention to people with hypertension. The program, conducted fortnightly for 3 months, included monitoring of BP, education about hypertension, and support for healthy lifestyle change. Outcomes were assessed approximately 2 months after completion of the intervention. The primary outcome was control of BP (BP < 140/90 mm Hg), analysed using mixed effects regression, clustered by village within region and adjusted for baseline control of hypertension (using intention-to-treat principles). Of 2,382 potentially eligible people, 637 from 5 intervention clusters and 1,097 from 10 UC clusters were recruited between November 2015 and April 2016, with follow-up occurring in 459 in the intervention group and 1,012 in UC. Mean age was 56.9 years (SD 13.7). Baseline BP was similar between groups. Control of BP improved from baseline to follow-up more in the intervention group (from 227 [49.5%] to 320 [69.7%] individuals) than in the UC group (from 528 [52.2%] to 624 [61.7%] individuals) (odds ratio [OR] 1.6, 95% CI 1.2-2.1; P = 0.001). In secondary outcome analyses, there was a greater decline in systolic BP in the intervention than UC group (-5.0 mm Hg, 95% CI -7.1 to -3.0; P < 0.001) and a greater decline in diastolic BP (-2.1 mm Hg, 95% CI -3.6 to -0.6; P < 0.006), but no detectable difference in the use of BP-lowering medications between groups (OR 1.2, 95% CI 0.8-1.9; P = 0.34). Similar results were found when using imputation analyses that included those lost to follow-up. Limitations include a relatively short follow-up period and use of outcome assessors who were not blinded to the group allocation.

CONCLUSIONS

While the durability of the effect is uncertain, this trial provides evidence that a low-cost program using CHWs to deliver an education and monitoring intervention is effective in controlling BP and is potentially scalable in resource-poor settings globally.

TRIAL REGISTRATION

The trial was registered with the Clinical Trials Registry-India (CTRI/2016/02/006678).

Effectiveness of upgraded maternity waiting homes and local leader training in improving institutional births among women in the Jimma zone, Ethiopia: study protocol for a cluster-randomized controlled trial

Background

Ethiopia is one of the ten countries in the world that together account for almost 60% of all maternal deaths. Recent reductions in maternal mortality have been seen, yet just 26% of women who gave birth in Ethiopia in 2016 reported doing so at a health facility. Maternity waiting homes (MWHs) have been introduced to overcome geographical and financial barriers to institutional births but there is no conclusive evidence as to their effectiveness. We aim to evaluate the effects of upgraded MWHs and local leader training in increasing institutional births in the Jimma zone of Ethiopia.

Methods

A parallel, three-arm, stratified, cluster-randomized controlled trial design is being employed to evaluate intervention effects on institutional births, which is the primary outcome. Trial arms are: (1) upgraded MWH + religious/community leader training; (2) leader training alone; and (3) standard care. Twenty-four primary health care unit catchment areas (clusters) have been randomized and 3840 women of reproductive age who had a pregnancy outcome (livebirth, stillbirth or abortion) are being randomly recruited for each survey round. Outcome assessments will be made using repeat cross-sectional surveys at baseline and 24 months postintervention. An intention to treat approach will be used and the primary outcome analysed using generalized linear mixed models with a random effect for cluster and time. A cost-effectiveness analysis will also be conducted from a societal perspective.

Discussion

This is one of the first trials to evaluate the effectiveness of upgraded MWHs and will provide much needed evidence to policy makers about aspects of functionality and the community engagement required as they scale-up this programme in Ethiopia.

Trial registration

ClinicalTrial.gov, NCT03299491. Retrospectively registered on 3 October 2017.

Efficacy of a mindful-eating programme to reduce emotional eating in patients suffering from overweight or obesity in primary care settings: a cluster-randomised trial protocol

INTRODUCTION

Little is known about the applicability of mindfulness-based interventions in Spanish adults with overweight/obesity. The objective of the present study protocol is to describe the methods that will be used in a cluster randomised trial (CRT) that aims to evaluate the effectiveness of a mindfulness eating (ME) programme to reduce emotional eating (EE) in adults with overweight/obesity in primary care (PC) settings.

METHODS AND ANALYSIS

A CRT will be conducted with approximately 76 adults with overweight/obesity from four PC health centres (clusters) in the city of Zaragoza, Spain. Health centres matched to the average per capita income of the assigned population will be randomly allocated into two groups: 'ME +treatment as usual (TAU)' and 'TAU alone'. The ME programme will be composed of seven sessions delivered by a clinical psychologist, and TAU will be offered by general practitioners. The primary outcome will be EE measured by the Dutch Eating Behaviour Questionnaire (DEBQ) at post test as primary endpoint. Other outcomes will be external and restrained eating (DEBQ), binge eating (Bulimic Investigatory Test Edinburgh), eating disorder (Eating Attitude Test), anxiety (General Anxiety Disorder-7), depression (Patient Health Questionnaire-9), mindful eating (Mindful Eating Scale), dispositional mindfulness (Five Facet Mindfulness Questionnaire) and self-compassion (Self-Compassion Scale). Anthropometric measures, vital signs and blood tests will be taken. A primary intention-to-treat analysis on EE will be conducted using linear mixed models. Supplementary analyses will include secondary outcomes and 1-year follow-up measures; adjusted models controlling for sex, weight status and levels of anxiety and depression; the complier average causal effect of treatment; and the clinical significance of improvements.

ETHICS AND DISSEMINATION

Positive results of this study may have a significant impact on one of the most important current health-related problems. Approval was obtained from the Ethics Committee of the Regional Authority. The results will be submitted to peer-reviewed journals, and reports will be sent to participants.

TRIAL REGISTRATION NUMBER

NCT03927534 (5/2019).

Cluster-Randomized Studies

BACKGROUND

Cluster-randomized trials (CRT) are needed to compare interventions that are allocated to entire groups of subjects, rather than to individuals. Publications about CRT have become steadily more common over the past decade. Readers of such publications should be able to categorize and interpret the findings of CRT correctly while considering the methodological requirements applicable to this type of study.

METHODS

This review is based on a selection of pertinent literature and on the authors' expertise. CRT-specific methodological aspects of the planning, performance, and interpretation of studies are discussed.

RESULTS

Readers of publications on CRT should check whether due consideration has been given to correlations within and between the clusters during the planning of the study. These correlations enable the determination whether persons within a cluster resemble each other more closely, or respond more similarly to the study intervention, than persons drawn from different clusters. It should also be checked whether the randomization for the study has been carried out with such methods as stratification and covariate-adjusted randomization. CRT can be analyzed on either the individual or the cluster level. The rationale for the choice of a clusterrandomized design should be explained, and intracluster correlation coefficients (ICC) should be reported as an aid to the planning of future studies. Particular requirements are also described in an extended version of the CONSORT guidelines that has been developed specifically for CRT.

CONCLUSION

Readers of publications on CRT should be aware of the special requirements mentioned above with respect to the design, performance, and analysis of this type of study as opposed to individually randomized studies. If no special techniques are applied in the design, performance, and analysis of a CRT, or if the assumptions underlying each of these steps have not been properly checked, then the findings of the study may well be misleading.

Design of vaccine efficacy trials during public health emergencies

Public health emergencies, such as an Ebola disease outbreak, provide a complex and challenging environment for the evaluation of candidate vaccines. Here, we outline the need for flexible and responsive vaccine trial designs to be used in public health emergencies, and we summarize recommendations for their use in this setting.