BackgroundAccurate optical characterisation and removal of small adenomas (<10 mm) at colonoscopy would allow hyperplastic polyps to be left in situ and surveillance intervals to be determined without the need for histopathology. Although accurate in specialist practice the performance of narrow band imaging (NBI), colonoscopy in routine clinical practice is poorly understood.MethodsNBI-assisted optical diagnosis was compared with reference standard histopathological findings in a prospective, blinded study, which recruited adults undergoing routine colonoscopy in six general hospitals in the UK. Participating colonoscopists (N=28) were trained using the NBI International Colorectal Endoscopic (NICE) classification (relating to colour, vessel structure and surface pattern). By comparing the optical and histological findings in patients with only small polyps, test sensitivity was determined at the patient level using two thresholds: presence of adenoma and need for surveillance. Accuracy of identifying adenomatous polyps <10 mm was compared at the polyp level using hierarchical models, allowing determinants of accuracy to be explored.FindingsOf 1688 patients recruited, 722 (42.8%) had polyps <10 mm with 567 (78.5%) having only polyps <10 mm. Test sensitivity (presence of adenoma, N=499 patients) by NBI optical diagnosis was 83.4% (95% CI 79.6% to 86.9%), significantly less than the 95% sensitivity (p<0.001) this study was powered to detect. Test sensitivity (need for surveillance) was 73.0% (95% CI 66.5% to 79.9%). Analysed at the polyp level, test sensitivity (presence of adenoma, N=1620 polyps) was 76.1% (95% CI 72.8% to 79.1%). In fully adjusted analyses, test sensitivity was 99.4% (95% CI 98.2% to 99.8%) if two or more NICE adenoma characteristics were identified. Neither colonoscopist expertise, confidence in diagnosis nor use of high definition colonoscopy independently improved test accuracy.InterpretationThis large multicentre study demonstrates that NBI optical diagnosis cannot currently be recommended for application in routine clinical practice. Further work is required to evaluate whether variation in test accuracy is related to polyp characteristics or colonoscopist training.Trial registration numberThe study was registered with clinicaltrials.gov (NCT01603927).

Background: Participants in clinical research studies often do not reflect the populations for which healthcare interventions are needed or will be used. Enhancing representation of under-served groups in clinical research is important to ensure that research findings are widely applicable. We describe a multicomponent workstream project to improve representation of under-served groups in clinical trials. Methods: The project comprised three main strands: (1) a targeted scoping review of literature to identify previous work characterising under-served groups and barriers to inclusion, (2) surveys of professional stakeholders and participant representative groups involved in research delivery to refine these initial findings and identify examples of innovation and good practice and (3) a series of workshops bringing together key stakeholders from funding, design, delivery and participant groups to reach consensus on definitions, barriers and a strategic roadmap for future work. The work was commissioned by the UK National Institute for Health Research Clinical Research Network. Output from these strands was integrated by a steering committee to generate a series of goals, workstream plans and a strategic roadmap for future development work in this area. Results: 'Under-served groups' was identified and agreed by the stakeholder group as the preferred term. Threequarters of stakeholders felt that a clear definition of under-served groups did not currently exist; definition was challenging and context-specific, but exemplar groups (e.g. those with language barriers or mental illness) were identified as under-served. Barriers to successful inclusion of under-served groups could be clustered into communication between research teams and participant groups; how trials are designed and delivered, differing agendas of research teams and participant groups; and lack of trust in the research process. Four key goals for future work were identified: building long-term relationships with under-served groups, developing training resources to improve design and delivery of trials for under-served groups, developing infrastructure and systems to support this work and working with funders, regulators and other stakeholders to remove barriers to inclusion.

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ObjectiveTo provide guidance to researchers, funders, regulators and study delivery teams to ensure that research on COVID-19 is inclusive, particularly of groups disproportionately affected by COVID-19 and who may have been historically under-served by research.Summary of key pointsGroups who are disproportionately affected by COVID-19 include (but are not limited to) older people, people with multiple long-term conditions, people with disabilities, people from Black, Asian and Ethnic minority groups, people living with obesity, people who are socioeconomically deprived and people living in care homes. All these groups are under-served by clinical research, and there is an urgent need to rectify this if COVID-19 research is to deliver relevant evidence for these groups who are most in need. We provide a framework and checklists for addressing key issues when designing and delivering inclusive COVID-19 research, based on the National Institute for Health Research INnovations in CLinical trial design and delivery for the UnDEr-served project roadmap. Strong community engagement, codevelopment and prioritisation of research questions and interventions are essential. Under-served groups should be represented on funding panels and ethics committees, who should insist on the removal of barriers to participation. Exclusion criteria should be kept to a minimum; intervention delivery and outcome measurement should be simple, flexible and tailored to the needs of different groups, and local advice on the best way to reach and engage with under-served communities should be taken by study delivery teams. Data on characteristics that allow identification of under-served groups must be collected, analyses should include these data to enable subgroup comparisons and results should be shared with under-served groups at an early stage.ConclusionInclusive COVID-19 research is a necessity, not a luxury, if research is to benefit all the communities it seeks to serve. It requires close engagement with under-served groups and attention to aspects of study topic, design, delivery, analysis and dissemination across the research life cycle.

Background Adaptive designs offer great promise in improving the efficiency and patient-benefit of clinical trials. An important barrier to further increased use is a lack of understanding about which additional resources are required to conduct a high-quality adaptive clinical trial, compared to a traditional fixed design. The Costing Adaptive Trials (CAT) project investigated which additional resources may be required to support adaptive trials. Methods We conducted a mock costing exercise amongst seven Clinical Trials Units (CTUs) in the UK. Five scenarios were developed, derived from funded clinical trials, where a non-adaptive version and an adaptive version were described. Each scenario represented a different type of adaptive design. CTU staff were asked to provide the costs and staff time they estimated would be needed to support the trial, categorised into specified areas (e.g. statistics, data management, trial management). This was calculated separately for the non-adaptive and adaptive version of the trial, allowing paired comparisons. Interviews with 10 CTU staff who had completed the costing exercise were conducted by qualitative researchers to explore reasons for similarities and differences. Results Estimated resources associated with conducting an adaptive trial were always (moderately) higher than for the non-adaptive equivalent. The median increase was between 2 and 4% for all scenarios, except for sample size re-estimation which was 26.5% (as the adaptive design could lead to a lengthened study period). The highest increase was for statistical staff, with lower increases for data management and trial management staff. The percentage increase in resources varied across different CTUs. The interviews identified possible explanations for differences, including (1) experience in adaptive trials, (2) the complexity of the non-adaptive and adaptive design, and (3) the extent of non-trial specific core infrastructure funding the CTU had. Conclusions This work sheds light on additional resources required to adequately support a high-quality adaptive trial. The percentage increase in costs for supporting an adaptive trial was generally modest and should not be a barrier to adaptive designs being cost-effective to use in practice. Informed by the results of this research, guidance for investigators and funders will be developed on appropriately resourcing adaptive trials.