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Pragmatism in clinical trials is focused on increasing the generalizability of research findings for routine clinical care settings. Hybridism in clinical trials (i.e., assessing both clinical effectiveness and implementation success) is focused on speeding up the process by which evidence-based practices are developed and adopted into routine clinical care. Even though pragmatic trial methodologies and implementation science evolved from very different disciplines, Pragmatic Trials and Hybrid Effectiveness-Implementation Trials share many similar design features. In fact, these types of trials can easily be conflated, creating the potential for investigators to mislabel their trial type or mistakenly use the wrong trial type to answer their research question. Blurred boundaries between trial types can hamper the evaluation of grant applications, the scientific interpretation of findings, and policy-making. Acknowledging that most trials are not pure Pragmatic Trials nor pure Hybrid Effectiveness-Implementation Trials, there are key differences in these trial types and they answer very different research questions. The purpose of this paper is to clarify the similarities and differences of these trial types for funders, researchers, and policy-makers. In addition, recommendations are offered to help investigators choose, label, and operationalize the most appropriate trial type to answer their research question. These recommendations complement existing reporting guidelines for clinical effectiveness trials (TIDieR) and implementation trials (StaRI).

Background In the UK, routinely recorded data may benefit prospective studies including randomised controlled trials (RCTs). In an on-going study, we aim to assess the feasibility of access and agreement of routinely recorded clinical and non-clinical data compared to data collected during a RCT using standard prospective methods. This paper will summarise available UK routinely recorded data sources and discuss our experience with the feasibility of accessing routinely recorded data for participants of a RCT before finally proposing recommendations for improving the access and implementation of routinely recorded data in RCTs. Methods Setting: the case study RCT is the Standard and New Antiepileptic Drugs II (SANAD II) trial, a pragmatic, UK, multicentre, phase IV RCT assessing the clinical and cost-effectiveness of antiepileptic drug treatments for newly diagnosed epilepsy. Participants: 98 participants have provided written consent to permit the request of routinely recorded data. Study procedures: routinely recorded clinical and non-clinical data were identified and data requested through formal applications from available data holders for the duration that participants have been recruited into SANAD II. The feasibility of accessing routinely recorded data during a RCT is assessed and recommendations for improving access proposed. Results Secondary-care clinical and socioeconomic data is recorded on a national basis and can be accessed, although there are limitations in the application process. Primary-care data are recorded by a number of organisations on a de-identified basis but access for specific individuals has not been feasible. Access to data recorded by non-clinical sources, including The Department for Work and Pensions and The Driving and Vehicle Licensing Agency, was not successful. Conclusions Recommendations discussed include further research to assess the attributes of routinely recorded data, an assessment of public perceptions and the development of strategies to collaboratively improve access to routinely recorded data for research. Trial registration International Standard Randomised Controlled Trials, ISRCTN30294119 . Registered on 3 July 2012. EudraCT No: 2012-001884-64. Registered on 9 May 2012.

The “cohort multiple randomized controlled trial,” a new design for pragmatic trials, embeds multiple trials within a cohort. The cohort multiple RCT is an attractive alternative to conventional RCTs in fields where recruitment is slow, multiple new (competing) interventions for the same condition have to be tested, new interventions are highly preferred by patients and doctors, and the risk of disappointment bias, cross-over, and contamination is considerable. To prevent these unwanted effects, the cohort multiple RCT provides information on randomization to the intervention group/arm only, and only after randomization (i.e., prerandomization). To some, especially in a clinical setting, this is not ethically acceptable. In this article, we argue that prerandomization in the cohort multiple randomized controlled trial (cmRCT) can be avoided by adopting a staged-informed consent procedure. In the first stage, at entry into the cohort, all potential participants are asked for their informed consent to participate in a cohort study and broad consent to be either randomly selected to be approached for experimental interventions or to serve as control without further notice during participation in the cohort. In a second stage, at the initiation of an RCT within the cohort, informed consent to receive the intervention is then only sought in those randomly selected for the intervention arm. At the third stage, after completion of each RCT, all cohort participants receive aggregate disclosure of trial results. This staged-informed consent procedure avoids prerandomization in cmRCT and aims to keep participants actively engaged in the research process.

We established a large database of trials to serve as a resource for future methodological and ethical analyses. Here, we use meta-data to describe the broad landscape of pragmatic trials including research areas, identification as pragmatic, quality of trial registry data and enrolment. Trials were identified by a validated search filter and included if a primary report of a health-related randomized trial published January 2014-April 2019. Data were collated from MEDLINE, Web of Science, ClinicalTrials.gov, and full text. 4337 eligible trials were identified from 13,065 records, of which 1988 were registered in ClinicalTrials.gov. Research areas were diverse, with the most common being general and internal medicine; public, environmental and occupational health; and health care sciences and services. The term “pragmatic” was seldom used in titles or abstracts. Several domains in ClinicalTrials.gov had questionable data quality. We estimated that one-fifth of trials under-accrued by at least 15%. There is a need to improve reporting of pragmatic trials and quality of trial registry data. Under accrual remains a challenge in pragmatic RCTs despite calls for more streamlined recruitment approaches. The diversity of pragmatic trials should be reflected in future ethical analyses.

Despite efforts to improve research equity in clinical trials, a lack of representativeness continues to threaten the generalizability of clinical trial evidence and leads to several ethical and economic consequences. Decentralized clinical trials (DCTs) and pragmatic clinical trials (PCTs), novel clinical trial models that use technology to enable alternative data collection methods and integrate studies into clinical care, hold great promise for addressing representativeness challenges but also face several limitations. Leveraging technology and clinical care settings to conduct trial visits and collect trial data inherently limits participation from people without reliable access to technology and consistent medical care. Further, representativeness needs to be improved across the full spectrum of clinical trials, from trials conducted in early product development phases to trials conducted after a product is approved, but the DCT and PCT elements that can improve representativeness are more likely to be deployed after seminal evidence for a new medical product’s regulatory approval has already been generated. We propose three solutions to help ensure the defining aspects of DCTs and PCTs increase representativeness and the generalizability of evidence generated in clinical trials conducted at all phases in the product lifecycle. We suggest that efforts should be centered around collaborative work with regulators to define data standards and validate outcomes when alternative data sources and collection methods are used, the creation of technical support resources and transparent processes for the conduct of trials facilitated by technology, and the incorporation of health equity principles into the design and deployment of technology-based tools used to facilitate DCTs and PCTs.

Background Adaptive designs (ADs) are intended to make clinical trials more flexible, offering efficiency and potentially cost-saving benefits. Despite a large number of statistical methods in the literature on different adaptations to trials, the characteristics, advantages and limitations of such designs remain unfamiliar to large parts of the clinical and research community. This systematic review provides an overview of the use of ADs in published clinical trials (Part I). A follow-up (Part II) will compare the application of AD in trials in adult and pediatric studies, to provide real-world examples and recommendations for the child health community. Methods Published studies from 2010 to April 2020 were searched in the following databases: MEDLINE (Ovid), Embase (Ovid), and International Pharmaceutical Abstracts (Ovid). Clinical trial protocols, reports, and a secondary analyses using AD were included. We excluded trial registrations and interventions other than drugs or vaccines to align with regulatory guidance. Data from the published literature on study characteristics, types of adaptations, statistical analysis, stopping boundaries, logistical challenges, operational considerations and ethical considerations were extracted and summarized herein. Results Out of 23,886 retrieved studies, 317 publications of adaptive trials, 267 (84.2%) trial reports, and 50 (15.8%) study protocols), were included. The most frequent disease was oncology (168/317, 53%). Most trials included only adult participants (265, 83.9%),16 trials (5.4%) were limited to only children and 28 (8.9%) were for both children and adults, 8 trials did not report the ages of the included populations. Some studies reported using more than one adaptation (there were 390 reported adaptations in 317 clinical trial reports). Most trials were early in drug development (phase I, II (276/317, 87%). Dose-finding designs were used in the highest proportion of the included trials (121/317, 38.2 %). Adaptive randomization (53/317, 16.7%), with drop-the-losers (or pick-the-winner) designs specifically reported in 29 trials (9.1%) and seamless phase 2-3 design was reported in 27 trials (8.5%). Continual reassessment methods (60/317, 18.9%) and group sequential design (47/317, 14.8%) were also reported. Approximately two-thirds of trials used frequentist statistical methods (203/309, 64%), while Bayesian methods were reported in 24% (75/309) of included trials. Conclusion This review provides a comprehensive report of methodological features in adaptive clinical trials reported between 2010 and 2020. Adaptation details were not uniformly reported, creating limitations in interpretation and generalizability. Nevertheless, implementation of existing reporting guidelines on ADs and the development of novel educational strategies that address the scientific, operational challenges and ethical considerations can help in the clinical trial community to decide on when and how to implement ADs in clinical trials. Study protocol registration https://doi.org/10.1186/s13063-018-2934-7 .

Over half a century ago, the terms “pragmatic” and “explanatory” were introduced to biomedicine by Schwartz and Lellouch, presenting two distinct conceptual approaches to trial design. Today, we frequently say that there are pragmatic trials and there are explanatory trials. Pragmatic trials inform decision-making in practice, and explanatory trials aim to understand the mechanism of an intervention. They are often perceived as diametral extremes of a continuum. In this commentary, we argue that with the digitalization of health care and clinical research, ways for modern trial designs were paved and new avenues opened, and that there is no such continuum. Since the groundbreaking work of Schwartz and Lellouch, new approaches and methods have become available that allow researchers to address pragmatic and explanatory questions in parallel in the same trial. Emerging availability of routinely collected “real-world” data, development of decentralized trial techniques, and creation of digital biomarkers allow to observe health outcomes with minimal or no interference in real-world care. This overcomes previous limitations to studying mechanisms of interventions in routine care and makes the idea of a continuum obsolete. We argue that pragmatism and explanatorism need to be understood as two distinct but compatible conceptual dimensions to open new perspectives for using novel technologies to design the most informative clinical trials and make better clinical and regulatory decisions. We base our argument on an analysis of the concept of a continuum and highlight its limitations. We review key trial design features and introduce a new concept that sees explanatory design features as fundamental, invasive or noninvasive, or sufficient or insufficient. We describe their impact on pragmatism and explanatorism and show how multidimensional pragmatic explanatory trials that are most useful are possible today. •Modern trial designs and approaches have emerged allowing to address pragmatic and explanatory questions in parallel in the same trial.•Pragmatism and explanatorism are not extremes of a continuum.•Pragmatism and explanatorism need to be understood as two distinct but compatible conceptual dimensions.•Pragmatic trials can include noninvasive explanatory trial design features to not only inform decisions but also to understand the mechanisms of interventions.•Multidimensional trials combining pragmatic and explanatory attitudes that are most useful are now possible by leveraging the digitalization of health care and clinical research.

What's new•Blinding in clinical trials has the potential to reduce bias.•There is a live yet underreported debate about the value of measuring blinding success.•Interpreting the success of blinding can be problematic and potentially misleading.•However, failure to report the success of blinding, if it is measured, seems like willful withholding of information that is at least potentially useful.•We suggest a middle road whereby the success of blinding be measured (where feasible) and interpreted with caution. ‘Blinding’ involves concealing knowledge of which trial participants received the interventions from participants themselves and other trial personnel throughout the trial. Blinding reduces bias arising from the beliefs and expectations of these groups. It is agreed that where possible, blinding should be attempted, for example by ensuring that experimental and control treatments look the same. However, there is a debate about if we should measure whether blinding has been successful, this manuscript will discuss this controversy, including the benefits and risks of measuring blinding within the randomised controlled trial.