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Background/Objective: Despite the intuitive attractiveness of bringing research to participants rather than making them come to central study sites, widespread decentralized enrollment has not been common in clinical trials. Methods: The need for clinical research in the context of the COVID-19 pandemic, along with innovations in technology, led us to use a decentralized trial approach in our Phase 2 COVID-19 trial. We used real-time acquisition and transmission of health-related data using home-based monitoring devices and mobile applications to assess outcomes. This approach not only avoids spreading COVID-19 but it also can support inclusion of participants in more diverse socioeconomic circumstances and in rural settings. Results: Our team developed and deployed a decentralized trial platform to support patient engagement and adverse event reporting. Clinicians, engineers, and informaticians on our research team developed a Clinical-Trial-in-a-Box tool to optimally collect and analyze data from multiple decentralized platforms. Conclusion: Applying the decentralized model in Long COVID, using digital health technology and personal devices integrated with our telehealth platform, we share the lessons learned from our work, along with challenges and future possibilities.
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Importance: Multicenter clinical trials play a critical role in the translational processes that enable new treatments to reach all people and improve public health. However, conducting multicenter randomized clinical trials (mRCT) presents challenges. The Trial Innovation Network (TIN), established in 2016 to partner with the Clinical and Translational Science Award (CTSA) Consortium of academic medical institutions in the implementation of mRCTs, consists of 3 Trial Innovation Centers (TICs) and 1 Recruitment Innovation Center (RIC). This unique partnership has aimed to address critical roadblocks that impede the design and conduct of mRCTs, in expectation of accelerating the translation of novel interventions to clinical practice. The TIN's challenges and achievements are described in this article, along with examples of innovative resources and processes that may serve as useful models for other clinical trial networks providing operational and recruitment support. Observations: The TIN has successfully integrated more than 60 CTSA institution program hubs into a functional network for mRCT implementation and optimization. A unique support system for investigators has been created that includes the development and deployment of novel tools, operational and recruitment services, consultation models, and rapid communication pathways designed to reduce delays in trial start-up, enhance recruitment, improve engagement of diverse research participants and communities, and streamline processes that improve the quality, efficiency, and conduct of mRCTs. These resources and processes span the clinical trial spectrum and enable the TICs and RIC to serve as coordinating centers, data centers, and recruitment specialists to assist trials across the National Institutes of Health and other agencies. The TIN's impact has been demonstrated through its response to both historical operational challenges and emerging public health emergencies, including the national opioid public health crisis and the COVID-19 pandemic. Conclusions and Relevance: The TIN has worked to reduce barriers to implementing mRCTs and to improve mRCT processes and operations by providing needed clinical trial infrastructure and resources to CTSA investigators. These resources have been instrumental in more quickly and efficiently translating research discoveries into beneficial patient treatments.
Subject(s)
Awards and Prizes , COVID-19 , United States , Humans , Pandemics , Translational Science, Biomedical , CommunicationABSTRACT
New technologies and disruptions related to Coronavirus disease-2019 have led to expansion of decentralized approaches to clinical trials. Remote tools and methods hold promise for increasing trial efficiency and reducing burdens and barriers by facilitating participation outside of traditional clinical settings and taking studies directly to participants. The Trial Innovation Network, established in 2016 by the National Center for Advancing Clinical and Translational Science to address critical roadblocks in clinical research and accelerate the translational research process, has consulted on over 400 research study proposals to date. Its recommendations for decentralized approaches have included eConsent, participant-informed study design, remote intervention, study task reminders, social media recruitment, and return of results for participants. Some clinical trial elements have worked well when decentralized, while others, including remote recruitment and patient monitoring, need further refinement and assessment to determine their value. Partially decentralized, or "hybrid" trials, offer a first step to optimizing remote methods. Decentralized processes demonstrate potential to improve urban-rural diversity, but their impact on inclusion of racially and ethnically marginalized populations requires further study. To optimize inclusive participation in decentralized clinical trials, efforts must be made to build trust among marginalized communities, and to ensure access to remote technology.
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One challenge for multisite clinical trials is ensuring that the conditions of an informative trial are incorporated into all aspects of trial planning and execution. The multicenter model can provide the potential for a more informative environment, but it can also place a trial at risk of becoming uninformative due to lack of rigor, quality control, or effective recruitment, resulting in premature discontinuation and/or non-publication. Key factors that support informativeness are having the right team and resources during study planning and implementation and adequate funding to support performance activities. This communication draws on the experience of the National Center for Advancing Translational Science (NCATS) Trial Innovation Network (TIN) to develop approaches for enhancing the informativeness of clinical trials. We distilled this information into three principles: (1) assemble a diverse team, (2) leverage existing processes and systems, and (3) carefully consider budgets and contracts. The TIN, comprised of NCATS, three Trial Innovation Centers, a Recruitment Innovation Center, and 60+ CTSA Program hubs, provides resources to investigators who are proposing multicenter collaborations. In addition to sharing principles that support the informativeness of clinical trials, we highlight TIN-developed resources relevant for multicenter trial initiation and conduct.
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Established in 2015, the Multi-Stakeholder Engagement (MuSE) Consortium is an international network of over 120 individuals interested in stakeholder engagement in research and guidelines. The MuSE group is developing guidance for stakeholder engagement in the development of health and healthcare guideline development. The development of this guidance has included multiple meetings with stakeholders, including patients, payers/purchasers of health services, peer review editors, policymakers, program managers, providers, principal investigators, product makers, the public, and purchasers of health services and has identified a number of key issues. These include: (1) Definitions, roles, and settings (2) Stakeholder identification and selection (3) Levels of engagement, (4) Evaluation of engagement, (5) Documentation and transparency, and (6) Conflict of interest management. In this paper, we discuss these issues and our plan to develop guidance to facilitate stakeholder engagement in all stages of the development of health and healthcare guideline development.
A group of international researchers, patient partners, and other stakeholders are working together to create a checklist for when and how to involve stakeholders in health guideline development. Health guidelines include clinical practice guidelines, which your healthcare provider uses to determine treatments for health conditions. While working on this checklist, the team identified key issues to work on, including: (1) Definitions, roles, and settings (2) Stakeholder identification and selection (3) Levels of engagement, (4) Evaluation of engagement, (5) Documentation and transparency, and (6) Conflict of interest management. This paper describes each issue and how the team plans to produce guidance papers to address them.
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In 2016, the National Center for Advancing Translational Science launched the Trial Innovation Network (TIN) to address barriers to efficient and informative multicenter trials. The TIN provides a national platform, working in partnership with 60+ Clinical and Translational Science Award (CTSA) hubs across the country to support the design and conduct of successful multicenter trials. A dedicated Hub Liaison Team (HLT) was established within each CTSA to facilitate connection between the hubs and the newly launched Trial and Recruitment Innovation Centers. Each HLT serves as an expert intermediary, connecting CTSA Hub investigators with TIN support, and connecting TIN research teams with potential multicenter trial site investigators. The cross-consortium Liaison Team network was developed during the first TIN funding cycle, and it is now a mature national network at the cutting edge of team science in clinical and translational research. The CTSA-based HLT structures and the external network structure have been developed in collaborative and iterative ways, with methods for shared learning and continuous process improvement. In this paper, we review the structure, function, and development of the Liaison Team network, discuss lessons learned during the first TIN funding cycle, and outline a path toward further network maturity.
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Improving the quality and conduct of multi-center clinical trials is essential to the generation of generalizable knowledge about the safety and efficacy of healthcare treatments. Despite significant effort and expense, many clinical trials are unsuccessful. The National Center for Advancing Translational Science launched the Trial Innovation Network to address critical roadblocks in multi-center trials by leveraging existing infrastructure and developing operational innovations. We provide an overview of the roadblocks that led to opportunities for operational innovation, our work to develop, define, and map innovations across the network, and how we implemented and disseminated mature innovations.
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Background: The Clinical and Translational Science Award Program (CTSA) Trial Innovation Network (TIN) was launched in 2016 to increase the efficiency and effectiveness of multisite trials by supporting the development of national infrastructure. With the advent of the COVID-19 pandemic, it was therefore well-positioned to support clinical trial collaboration. The TIN was leveraged to support two initiatives: (1) to create and evaluate a mechanism for coordinating Data and Safety Monitoring Board (DSMB) activities among multiple ongoing trials of the same therapeutic agents, and (2) to share data across clinical trials so that smaller, likely underpowered studies, could be combined to produce meaningful and actionable data through pooled analyses. The success of these initiatives was understood to be dependent upon the willingness of investigators, study teams, and US National Institutes of Health research networks to collaborate and share information. Methods: To inform these two initiatives, we conducted semistructured interviews with members of CTSA hubs and clinical research stakeholders that probed barriers and facilitators to collaboration. Thematic analysis identified topics relevant across institutions, individuals, and DSMBs. Results: The DSMB coordination initiative was viewed as less controversial, while the data pooling initiative was seen as complex because of its potential impact on publication, authorship, and the rewards of discovery. Barriers related to resources, centralization, and technical work were significant, but interviewees suggested these could be handled by the provision of central funding and supportive frameworks. The more intractable findings were related to issues around credit and ownership of data. Conclusion: Based on our interviews, we conclude with nine recommended actions that can be implemented to support collaboration.
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Clinicians and patients often try a treatment for an initial period to inform longer-term therapeutic decisions. A more rigorous approach involves N-of-1 trials. In these single-patient crossover trials, typically conducted in patients with chronic conditions, individual patients are given candidate treatments in a double-blinded, random sequence of alternating periods to determine the most effective treatment for that patient. However, to date, these trials are rarely done outside of research settings and have not been integrated into general care where they could offer substantial benefit. Designating this classical, N-of-1 trial design as type 1, there also are new and evolving uses of N-of-1 trials that we designate as type 2. In these, rather than focusing on optimizing treatment for chronic diseases when multiple approved choices are available, as is typical of type 1, a type 2 N-of-1 trial tests treatments designed specifically for a patient with a rare disease, to facilitate personalized medicine. While the aims differ, both types face the challenge of collecting individual-patient evidence using standard, trusted, widely accepted methods. To fulfill their potential for producing both clinical and research benefits, and to be available for wide use, N-of-1 trials will have to fit into the current healthcare ecosystem. This will require generalizable and accepted processes, platforms, methods, and standards. This also will require sustainable value-based arrangements among key stakeholders. In this article, we review opportunities, stakeholders, issues, and possible approaches that could support general use of N-of-1 trials and deliver benefit to patients and the healthcare enterprise. To assess and expand the benefits of N-of-1 trials, we propose multistakeholder meetings, workshops, and the generation of methods, standards, and platforms that would support wider availability and the value of N-of-1 trials.
Subject(s)
Delivery of Health Care , Ecosystem , Humans , Treatment OutcomeABSTRACT
The psychometric tools used for the assessment of generalized anxiety disorder (GAD) either do not conform to the current concept of the condition or have important limitations. We aimed to develop and validate a new questionnaire for the assessment of symptom profile and severity of GAD. An original pool of potential scale items was subjected to a series of studies in non-clinical and clinical populations, in order to determine the final composition of the scale. The psychometric properties of the new scale, the Generalized Anxiety Disorder Inventory (GADI), were evaluated using a factor analytic model suitable for ordinal data and the Graded Response Model. The precision of measurement of the GADI was quantified through the item information functions.A total of 197 outpatients and 522 non-clinical subjects participated in four studies and completed the GADI. The final 18-item scale was derived from an original pool of 30 potential items. The GADI showed good reliability, convergent and divergent validity. The scale comprises three factors, relating to cognitive, somatic and sleep symptoms. It accurately distinguished GAD patients from non-patient controls. The cognitive factor also distinguished GAD from other anxiety disorders and depression. The GADI is a useful tool in the assessment of the breadth of symptoms and the severity of generalized anxiety disorder in clinical settings.
