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Background Site performance is key to the success of large multicentre randomised trials. A standardised set of clear and accessible summaries of site performance could facilitate the timely identification and resolution of potential problems, minimising their impact. The aim of this study was to identify and agree a core set of key performance metrics for managing multicentre randomised trials. Methods We used a mixed methods approach to identify potential metrics and to achieve consensus about the final set, adapting methods that are recommended by the COMET Initiative for developing core outcome sets in health care. We used performance metrics identified from our systematic search and focus groups to create an online Delphi survey. We invited respondents to score each metric for inclusion in the final core set, over three survey rounds. Metrics scored as critical by ≥70% and unimportant by <15% of respondents were taken forward to a consensus meeting of representatives from key UK-based stakeholders. Participants in the consensus meeting discussed and voted on each metric, using anonymous electronic voting. Metrics with >50% of participants voting for inclusion were retained. Results Round 1 of the Delphi survey presented 28 performance metrics, and a further six were added in round 2. Of 294 UK-based stakeholders who registered for the Delphi survey, 211 completed all three rounds. At the consensus meeting, 17 metrics were discussed and voted on: 15 metrics were retained following survey round 3, plus two others that were preferred by consensus meeting participants. Consensus was reached on a final core set of eight performance metrics in three domains: (1) recruitment and retention, (2) data quality and (3) protocol compliance. A simple tool for visual reporting of the metrics is available from the Nottingham Clinical Trials Unit website. Conclusions We have established a core set of metrics for measuring the performance of sites in multicentre randomised trials. These metrics could improve trial conduct by enabling researchers to identify and address problems before trials are adversely affected. Future work could evaluate the effectiveness of using the metrics and reporting tool.

Background Non-retention of participants seriously affects the credibility of clinical trial results and significantly reduces the potential of a trial to influence clinical practice. Non-retention can be defined as instances where participants leave the study prematurely. Examples include withdrawal of consent and loss to follow-up and thus outcome data cannot be obtained. The majority of existing interventions targeting retention fail to describe any theoretical basis for the observed improvement, or lack of improvement. Moreover, most of these interventions lack involvement of participants in their conception and/or design, raising questions about their relevance and acceptability. Many of the causes of non-retention involve people performing a behaviour (e.g. not returning a questionnaire). Behaviour change is difficult, and the importance of a strong theoretical basis for interventions that aim to change behaviour is increasingly recognised. This research aims to develop and pilot theoretically informed, participant-centred, evidence-based behaviour change interventions to improve retention in trials. Methods This research will generate data through semi-structured interviews on stakeholders’ perspectives of the reasons for trial non-retention. It will identify perceived barriers and enablers to trial retention using the Theoretical Domains Framework. The intervention development work will involve identification of behaviour change techniques, using recognised methodology, and co-production of retention interventions through discussion groups with end-users. An evaluation of intervention acceptability and feasibility will be conducted in focus groups. Finally, a ready-to-use evaluation framework to deploy in Studies Within A Trial as well as an explanatory retention framework will be developed for identifying and tackling modifiable issues to improve trial retention. Discussion We believe this to be one of the first studies to apply a theoretical lens to the development of interventions to improve trial retention that have been informed by, and are embedded within, participants’ experiential accounts. By developing and identifying priority interventions this study will support efforts to reduce research waste.

To provide recommendations for the selection of comparators for randomized controlled trials of health-related behavioral interventions. The National Institutes of Health Office of Behavioral and Social Science Research convened an expert panel to critically review the literature on control or comparison groups for behavioral trials and to develop strategies for improving comparator choices and for resolving controversies and disagreements about comparators. The panel developed a Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials. The model indicates that the optimal comparator is the one that best serves the primary purpose of the trial but that the optimal comparator's limitations and barriers to its use must also be taken into account. We developed best practice recommendations for the selection of comparators for health-related behavioral trials. Use of the Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials can improve the comparator selection process and help resolve disagreements about comparator choices.

Background The process of obtaining informed consent for participation in randomised controlled trials (RCTs) was established as a mechanism to protect participants against undue harm from research and allow people to recognise any potential risks or benefits associated with the research. A number of interventions have been put forward to improve this process. Outcomes reported in trials of interventions to improve the informed consent process for decisions about trial participation tend to focus on the ‘understanding’ of trial information. However, the operationalization of understanding as a concept, the tools used to measure it and the timing of the measurements are heterogeneous. A lack of clarity exists regarding which outcomes matter (to whom) and why. This inconsistency between studies results in difficulties when making comparisons across studies as evidenced in two recent systematic reviews of informed consent interventions. As such, no optimal method for measuring the impact of these interventions aimed at improving informed consent for RCTs has been identified. Methods/Design The project will adopt and adapt methodology previously developed and used in projects developing core outcome sets for assessment of clinical treatments. Specifically, the work will consist of three stages: 1) A systematic methodology review of existing outcome measures of trial informed consent interventions; 2) Interviews with key stakeholders to explore additional outcomes relevant for trial participation decisions; and 3) A Delphi study to refine the core outcome set for evaluation of trial informed consent interventions. All stages will include the stakeholders involved in the various aspects of RCT consent: users (that is, patients), developers (that is, trialists), deliverers (focusing on research nurses) and authorisers (that is, ethics committees). A final consensus meeting including all stakeholders will be held to review outcomes. Discussion The ELICIT study aims to develop a core outcome set for the evaluation of interventions intended to improve informed consent for RCTs for use in future RCTs and reviews, thereby improving the reliability and consistency of research in this area.

A systematic search of seven electronic databases was done to identify randomized controlled trials that assessed the effect of computer-generated patient education material (PEM) on professional practice. Three studies met the authors' criteria. All three studies involved preventive care. All used a complex intervention of which computer-generated PEM was a major component. Improvements in practice were seen in all studies, although these gains were generally modest. One study showed improvement in patient outcomes. Mann-Whitney statistics calculated for the studies' outcome measures ranged from 0.48 to 0.66, equivalent to risk differences of -4 to 32 percent. Computer-generated PEM seems to have a small, positive effect on professional practice. The small number of included studies and the complex nature of the interventions makes it difficult to draw conclusions about the ability of computer-generated PEM to change professional practice. Future work should involve well-defined interventions that can be clearly evaluated in terms of effect and cost.

PRECIS is a tool to help trialists make design decisions consistent with the intended purpose of their trial. This paper gives guidance on how to use an improved, validated version, PRECIS-2, which has been developed with the help of over 80 international trialists, clinicians, and policymakers. Keeping the original simple wheel format, PRECIS-2 has nine domains—eligibility criteria, recruitment, setting, organisation, flexibility (delivery), flexibility (adherence), follow-up, primary outcome, and primary analysis—scored from 1 (very explanatory) to 5 (very pragmatic) to facilitate domain discussion and consensus. It is hoped PRECIS-2 will be valuable in supporting the explicit matching of design decisions to how the trial results are intended to be used

The prevalence of male obesity is increasing but few men take part in weight loss programmes. We assessed the effect of a weight loss and healthy living programme on weight loss in football (soccer) fans. We did a two-group, pragmatic, randomised controlled trial of 747 male football fans aged 35–65 years with a body-mass index (BMI) of 28 kg/m2 or higher from 13 Scottish professional football clubs. Participants were randomly assigned with SAS (version 9·2, block size 2–9) in a 1:1 ratio, stratified by club, to a weight loss programme delivered by community coaching staff in 12 sessions held every week. The intervention group started a weight loss programme within 3 weeks, and the comparison group were put on a 12 month waiting list. All participants received a weight management booklet. Primary outcome was mean difference in weight loss between groups at 12 months, expressed as absolute weight and a percentage of their baseline weight. Primary outcome assessment was masked. Analyses were based on intention to treat. The trial is registered with Current Controlled Trials, number ISRCTN32677491. 374 men were allocated to the intervention group and 374 to the comparison group. 333 (89%) of the intervention group and 355 (95%) of the comparison group completed 12 month assessments. At 12 months the mean difference in weight loss between groups, adjusted for baseline weight and club, was 4·94 kg (95% CI 3·95–5·94) and percentage weight loss, similarly adjusted, was 4·36% (3·64–5·08), both in favour of the intervention (p<0·0001). Eight serious adverse events were reported, five in the intervention group (lost consciousness due to drugs for pre-existing angina, gallbladder removal, hospital admission with suspected heart attack, ruptured gut, and ruptured Achilles tendon) and three in the comparison group (transient ischaemic attack, and two deaths). Of these, two adverse events were reported as related to participation in the programme (gallbladder removal and ruptured Achilles tendon). The FFIT programme can help a large proportion of men to lose a clinically important amount of weight; it offers one effective strategy to challenge male obesity. Scottish Government and The UK Football Pools funded delivery of the programme through a grant to the Scottish Premier League Trust. The National Institute for Health Research Public Health Research Programme funded the assessment (09/3010/06).

Reducing sitting time as well as increasing physical activity in inactive people is beneficial for their health. This paper investigates the effectiveness of the European Fans in Training (EuroFIT) programme to improve physical activity and sedentary time in male football fans, delivered through the professional football setting. A total of 1,113 men aged 30-65 with self-reported body mass index (BMI) ≥27 kg/m2 took part in a randomised controlled trial in 15 professional football clubs in England, the Netherlands, Norway, and Portugal. Recruitment was between September 19, 2015, and February 2, 2016. Participants consented to study procedures and provided usable activity monitor baseline data. They were randomised, stratified by club, to either the EuroFIT intervention or a 12-month waiting list comparison group. Follow-up measurement was post-programme and 12 months after baseline. EuroFIT is a 12-week, group-based programme delivered by coaches in football club stadia in 12 weekly 90-minute sessions. Weekly sessions aimed to improve physical activity, sedentary time, and diet and maintain changes long term. A pocket-worn device (SitFIT) allowed self-monitoring of sedentary time and daily steps, and a game-based app (MatchFIT) encouraged between-session social support. Primary outcome (objectively measured sedentary time and physical activity) measurements were obtained for 83% and 85% of intervention and comparison participants. Intention-to-treat analyses showed a baseline-adjusted mean difference in sedentary time at 12 months of -1.6 minutes/day (97.5% confidence interval [CI], -14.3-11.0; p = 0.77) and in step counts of 678 steps/day (97.5% CI, 309-1.048; p < 0.001) in favor of the intervention. There were significant improvements in diet, weight, well-being, self-esteem, vitality, and biomarkers of cardiometabolic health in favor of the intervention group, but not in quality of life. There was a 0.95 probability of EuroFIT being cost-effective compared with the comparison group if society is willing to pay £1.50 per extra step/day, a maximum probability of 0.61 if society is willing to pay £1,800 per minute less sedentary time/day, and 0.13 probability if society is willing to pay £30,000 per quality-adjusted life-year (QALY). It was not possible to blind participants to group allocation. Men attracted to the programme already had quite high levels of physical activity at baseline (8,372 steps/day), which may have limited room for improvement. Although participants came from across the socioeconomic spectrum, a majority were well educated and in paid work. There was an increase in recent injuries and in upper and lower joint pain scores post-programme. In addition, although the five-level EuroQoL questionnaire (EQ-5D-5L) is now the preferred measure for cost-effectiveness analyses across Europe, baseline scores were high (0.93), suggesting a ceiling effect for QALYs. Participation in EuroFIT led to improvements in physical activity, diet, body weight, and biomarkers of cardiometabolic health, but not in sedentary time at 12 months. Within-trial analysis suggests it is not cost-effective in the short term for QALYs due to a ceiling effect in quality of life. Nevertheless, decision-makers may consider the incremental cost for increase in steps worth the investment. International Standard Randomised Controlled Trials, ISRCTN-81935608.

Objective To identify the number of drug-disease and drug-drug interactions for exemplar index conditions within National Institute of Health and Care Excellence (NICE) clinical guidelines.Design Systematic identification, quantification, and classification of potentially serious drug-disease and drug-drug interactions for drugs recommended by NICE clinical guidelines for type 2 diabetes, heart failure, and depression in relation to 11 other common conditions and drugs recommended by NICE guidelines for those conditions.Setting NICE clinical guidelines for type 2 diabetes, heart failure, and depressionMain outcome measures Potentially serious drug-disease and drug-drug interactions.Results Following recommendations for prescription in 12 national clinical guidelines would result in several potentially serious drug interactions. There were 32 potentially serious drug-disease interactions between drugs recommended in the guideline for type 2 diabetes and the 11 other conditions compared with six for drugs recommended in the guideline for depression and 10 for drugs recommended in the guideline for heart failure. Of these drug-disease interactions, 27 (84%) in the type 2 diabetes guideline and all of those in the two other guidelines were between the recommended drug and chronic kidney disease. More potentially serious drug-drug interactions were identified between drugs recommended by guidelines for each of the three index conditions and drugs recommended by the guidelines for the 11 other conditions: 133 drug-drug interactions for drugs recommended in the type 2 diabetes guideline, 89 for depression, and 111 for heart failure. Few of these drug-disease or drug-drug interactions were highlighted in the guidelines for the three index conditions.Conclusions Drug-disease interactions were relatively uncommon with the exception of interactions when a patient also has chronic kidney disease. Guideline developers could consider a more systematic approach regarding the potential for drug-disease interactions, based on epidemiological knowledge of the comorbidities of people with the disease the guideline is focused on, and should particularly consider whether chronic kidney disease is common in the target population. In contrast, potentially serious drug-drug interactions between recommended drugs for different conditions were common. The extensive number of potentially serious interactions requires innovative interactive approaches to the production and dissemination of guidelines to allow clinicians and patients with multimorbidity to make informed decisions about drug selection.

The role of biomarkers in risk-based early detection of lung cancer may enable screening to become cost effective and widely accessible. EarlyCDT-Lung is an example of such a blood-based autoantibody biomarker which may improve accessibility to Low dose Computed Tomography (LDCT) screening for those at highest risk. We randomized 12 208 individuals aged 50–75 at high risk of developing lung cancer to either the test or to standard clinical care. Outcomes were ascertained from Register of Deaths and Cancer Registry. Cox proportional hazards models were used to estimate the hazard ratio of the rate of deaths from all causes and lung cancer. Additional analyses were performed for cases of lung cancer diagnosed within two years of the initial test. After 5 years 326 lung cancers were detected (2.7% of those enrolled). The total number of deaths reported from all causes in the intervention group was 344 compared to 388 in the control group. There were 73 lung cancer deaths in the intervention arm and 90 in the controls (Adjusted HR 0.789 (0.636, 0.978). An analysis of cases of lung cancer detected within 2 years of randomization in the intervention group showed that there were 34 deaths from all causes and 29 from lung cancer. In the control group there were 56 deaths with 49 from lung cancer. In those diagnosed with lung cancer within 2 years of randomization the hazard ratio for all cause mortality was 0.615 (0.401,0.942) and for lung cancer 0.598 (0.378, 0.946). Further large-scale studies of the role of biomarkers to target lung cancer screening, in addition to LDCT, are likely to provide additional value.