Informed consent in pragmatic trials: results from a survey of trials published 2014-2019.

OBJECTIVES: To describe reporting of informed consent in pragmatic trials, justifications for waivers of consent and reporting of alternative approaches to standard written consent. To identify factors associated with (1) not reporting and (2) not obtaining consent. METHODS: Survey of primary trial reports, published 2014-2019, identified using an electronic search filter for pragmatic trials implemented in MEDLINE, and registered in ClinicalTrials.gov. RESULTS: Among 1988 trials, 132 (6.6%) did not include a statement about participant consent, 1691 (85.0%) reported consent had been obtained, 139 (7.0%) reported a waiver and 26 (1.3%) reported consent for one aspect (eg, data collection) but a waiver for another (eg, intervention). Of the 165 trials reporting a waiver, 76 (46.1%) provided a justification. Few (53, 2.9%) explicitly reported use of alternative approaches to consent. In multivariable logistic regression analyses, lower journal impact factor (p=0.001) and cluster randomisation (p<0.0001) were significantly associated with not reporting on consent, while trial recency, cluster randomisation, higher-income country settings, health services research and explicit labelling as pragmatic were significantly associated with not obtaining consent (all p<0.0001). DISCUSSION: Not obtaining consent seems to be increasing and is associated with the use of cluster randomisation and pragmatic aims, but neither cluster randomisation nor pragmatism are currently accepted justifications for waivers of consent. Rather than considering either standard written informed consent or waivers of consent, researchers and research ethics committees could consider alternative consent approaches that may facilitate the conduct of pragmatic trials while preserving patient autonomy and the public's trust in research.

Heterogeneity of antidiabetic treatment effect on the risk of major adverse cardiovascular events in type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: We explored whether clinically relevant baseline characteristics of patients with type 2 diabetes can modify the effect of glucagon-like peptide-1 receptor agonists (GLP-1 RA) or sodium-glucose cotransporter-2 inhibitors (SGLT-2i) on the risk of major adverse cardiovascular events (MACE). METHODS: We investigated Medline and EMBASE through June 2019. We included randomized clinical trials reporting the effect of GLP-1 RA or SGLT-2i on MACE in subgroups of patients with type 2 diabetes, identified through key baseline factors: established cardiovascular disease; heart failure; chronic kidney disease; uncontrolled diabetes; duration of diabetes; hypertension; obesity; age; gender and race. Hazard ratios (HRs) and 95% confidence intervals (CIs) from trials were meta-analyzed using random-effects models. RESULTS: Ten trials enrolling 89,790 patients were included in the analyses. Subgroup meta-analyses showed a 14% risk reduction of MACE in patients with established cardiovascular disease [GLP1-RA: HR, 0.86 (95% CI, 0.80-0.93); SGLT-2i: 0.86 (0.80-0.93)], and no effect in at-risk patients without history of cardiovascular events [GLP1-RA: 0.94 (0.82-1.07); SGLT-2i: 1.00 (0.87-1.16)]. We observed a trend toward larger treatment benefits with SGLT-2i among patients with chronic kidney disease [0.82 (0.69-0.97)], and patients with uncontrolled diabetes for both GLP1-RA or SGLT-2i [GLP1-RA: 0.82 (0.71-0.95); SGLT-2i: 0.84 (0.75-0.95)]. Uncontrolled hypertension, obesity, gender, age and race did not appear to modify the effect of these drugs. CONCLUSIONS: In this exploratory analysis, history of cardiovascular disease appeared to modify the treatment effect of SGLT2i or GLP1-RA on MACE. Chronic kidney disease and uncontrolled diabetes should be further investigated as potential effect modifiers.

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.

Community-engaged Evidence Synthesis to Inform Public Health Policy and Clinical Practice: A Case Study.

BACKGROUND: This case study documents the work of the Rhode Island Arts and Health Advisory Group, which convened in 2016 to develop a set of policy, clinical practice, and research recommendations for implementation by the Rhode Island Department of Health, The Rhode Island State Council on the Arts, and partners. Comprised of artists, clinicians, community members, and patients, the group partnered with researchers to complete an evidence synthesis project of arts-based health care interventions. METHODS: The group took a community-engaged approach to evidence synthesis, featuring the use of online, and in-person training materials to facilitate the codesign and coexecution of the evidence synthesis protocol. The final evidence map was translated into an online evidence map to facilitate analysis and discussion on arts-based interventions in health care. RESULTS: The evidence map informed the development of recommendations for advancing the integration of arts and health in the state. The project evaluation indicated that our community-engaged approach to evidence synthesis promoted engagement as defined by the PCORI Engagement Strategy Rubric (ie, reciprocal relationships, partnership, colearning, transparency, honesty, and trust). Participation also improved community research partners confidence in engaging with the health care system, developed greater empathy and understanding of others in the community, and increased interest in using science or research in advocacy efforts. CONCLUSIONS: Engaging community partners in evidence synthesis promotes community dialogue and engagement in research, specifically towards: (1) elucidating outcomes of import to patients and communities that are not represented in the medical literature; and (2) identifying comparisons among interventions that resonate with patients and communities.

Heuristics and Explanation in Translational Medicine.

The reigning paradigm of rational drug discovery in translational medicine attempts to exploit biological theories and pathophysiological explanations to identify novel drug targets and therapeutic strategies. Yet because many theories in medicine are either incomplete (at best) or false (at worst), relying on theoretical explanations can have some puzzling and troubling consequences. New drugs may be shown to be effective in clinical trials and receive regulatory approval despite a faulty explanation for why they are effective. If physicians rely on this explanation to make treatment decisions, it can lead to systematic misdiagnoses and patient harm. For research programs, underdetermination may shield faulty biomedical explanations, and this can result in wasted research resources and avoidable burdens on human subjects. These problematic features of biomedical explanations can be resolved by reconceiving the epistemology of translational medicine in terms of heuristics.

Thinking clearly about the FIRST trial: addressing ethical challenges in cluster randomised trials of policy interventions involving health providers.

The ethics of the Flexibility In duty hour Requirements for Surgical Trainees (FIRST) trial have been vehemently debated. Views on the ethics of the FIRST trial range from it being completely unethical to wholly unproblematic. The FIRST trial illustrates the complex ethical challenges posed by cluster randomised trials (CRTs) of policy interventions involving healthcare professionals. In what follows, we have three objectives. First, we critically review the FIRST trial controversy, finding that commentators have failed to sufficiently identify and address many of the relevant ethical issues. The 2012 Ottawa Statement on the Ethical Design and Conduct of Cluster Randomized Trials provides researchers and research ethics committees with specific guidance for the ethical design and conduct of CRTs. Second, we aim to demonstrate how the Ottawa Statement provides much-needed clarity to the ethical issues in the FIRST trial, including: research participant identification; consent requirements; gatekeeper roles; benefit-harm analysis and identification of vulnerable participants. We nonetheless also find that the FIRST trial raises ethical issues not adequately addressed by the Ottawa Statement. Hence, third and finally, we raise important questions requiring further ethical analysis and guidance, including: Does clinical equipoise apply to policy interventions with little or no evidence-base? Do healthcare providers have an obligation to participate in research? Does the power-differential in certain healthcare settings render healthcare providers vulnerable to duress and coercion to participant in research? If so, what safeguards might be implemented to protect providers, while allowing important research to proceed?

Stakeholder views regarding ethical issues in the design and conduct of pragmatic trials: study protocol.

BACKGROUND: Randomized controlled trial (RCT) trial designs exist on an explanatory-pragmatic spectrum, depending on the degree to which a study aims to address a question of efficacy or effectiveness. As conceptualized by Schwartz and Lellouch in 1967, an explanatory approach to trial design emphasizes hypothesis testing about the mechanisms of action of treatments under ideal conditions (efficacy), whereas a pragmatic approach emphasizes testing effectiveness of two or more available treatments in real-world conditions. Interest in, and the number of, pragmatic trials has grown substantially in recent years, with increased recognition by funders and stakeholders worldwide of the need for credible evidence to inform clinical decision-making. This increase has been accompanied by the onset of learning healthcare systems, as well as an increasing focus on patient-oriented research. However, pragmatic trials have ethical challenges that have not yet been identified or adequately characterized. The present study aims to explore the views of key stakeholders with respect to ethical issues raised by the design and conduct of pragmatic trials. It is embedded within a large, four-year project that seeks to develop guidance for the ethical design and conduct of pragmatic trials. As a first step, this study will address important gaps in the current empirical literature with respect to identifying a comprehensive range of ethical issues arising from the design and conduct of pragmatic trials. By opening up a broad range of topics for consideration within our parallel ethical analysis, we will extend the current debate, which has largely emphasized issues of consent, to the range of ethical considerations that may flow from specific design choices. METHODS: Semi-structured interviews with key stakeholders (e.g. trialists, methodologists, lay members of study teams, bioethicists, and research ethics committee members), across multiple jurisdictions, identified based on their known experience and/or expertise with pragmatic trials. DISCUSSION: We expect that the study outputs will be of interest to a wide range of knowledge users including trialists, ethicists, research ethics committees, journal editors, regulators, healthcare policymakers, research funders and patient groups. All publications will adhere to the Tri-Agency Open Access Policy on Publications.

The Challenges of Validating in Precision Medicine: The Case of Excision Repair Cross-Complement Group 1 Diagnostic Testing.

Personalized medicine relies upon the successful identification and translation of predictive biomarkers. Unfortunately, biomarker development has often fallen short of expectations. To better understand the obstacles to successful biomarker development, we systematically mapped research activities for a biomarker that has been in development for at least 12 years: excision repair cross-complement group 1 protein (ERCC1) as a biomarker for predicting clinical benefit with platinum-based chemotherapy in non-small cell lung cancer. We found that although research activities explored a wide range of approaches to ERCC1 testing, there was little replication or validation of techniques, and design and reporting of results were generally poor. Our analysis points to problems with coordinating and standardizing research in biomarker development. Clinically meaningful progress in personalized medicine will require concerted efforts to address these problems. In the interim, health care providers should be aware of the complexity involved in biomarker development, cautious about their near-term clinical value, and conscious of applying only validated diagnostics in the clinic. THE ONCOLOGIST: 2017;22:89-96 IMPLICATIONS FOR PRACTICE: : Many hospitals, policy makers, and scientists have made ambitious claims about the promise of personalizing cancer care. When one uses a case example of excision repair cross-complement group 1 protein-a biomarker that has a strong biological rationale and that has been researched for 12 years-the current research environment seems poorly suited for efficient development of biomarker tests. The findings provide grounds for tempering expectations about personalized cancer care-at least in the near term-and shed light on the current gap between the promise and practice of personalized medicine.

An Uninformative Truth: The Logic of Amarin's Off-Label Promotion.

Spencer Phillips Hey and Aaron Kesselheim propose that informativeness-asserting scientific facts-rather than truthfulness ought to be the standard for regulating commercial speech about pharmaceuticals.

Epistemology, Ethics, and Progress in Precision Medicine.

The emerging paradigm of precision medicine strives to leverage the tools of molecular biology to prospectively tailor treatments to the individual patient. Fundamental to the success of this movement is the discovery and validation of "predictive biomarkers," which are properties of a patient's biological specimens that can be assayed in advance of therapy to inform the treatment decision. Unfortunately, research into biomarkers and diagnostics for precision medicine has fallen well short of expectations. In this essay, we examine the portfolio of research activities into the excision repair cross complement group 1 (ERCC1) gene as a predictive biomarker for precision lung cancer therapy as a case study in elucidating the epistemological and ethical obstacles to developing new precision medicines.

Do We Know Whether Researchers and Reviewers are Estimating Risk and Benefit Accurately?

Accurate estimation of risk and benefit is integral to good clinical research planning, ethical review, and study implementation. Some commentators have argued that various actors in clinical research systems are prone to biased or arbitrary risk/benefit estimation. In this commentary, we suggest the evidence supporting such claims is very limited. Most prior work has imputed risk/benefit beliefs based on past behavior or goals, rather than directly measuring them. We describe an approach - forecast analysis - that would enable direct and effective measure of the quality of risk/benefit estimation. We then consider some objections and limitations to the forecasting approach.

What questions can a placebo answer?

The concept of clinical equipoise restricts the use of placebo controls in clinical trials when there already exists a proven effective treatment. Several critics of clinical equipoise have put forward alleged counter-examples to this restriction-describing instances of ethical placebo-controlled trials that apparently violate clinical equipoise. In this essay, we respond to these examples and show that clinical equipoise is not as restrictive of placebos as these authors assume. We argue that a subtler appreciation for clinical equipoise-in particular the distinction between de facto and de jure interpretations of the concept-allows the concept to explain when and why a placebo control may be necessary to answer a question of clinical importance.

Are outcome-adaptive allocation trials ethical?

Randomization is firmly established as a cornerstone of clinical trial methodology. Yet, the ethics of randomization continues to generate controversy. The default, and most efficient, allocation scheme randomizes patients equally (1:1) across all arms of study. However, many randomized trials are using outcome-adaptive allocation schemes, which dynamically adjust the allocation ratio in favor of the better performing treatment arm. Advocates of outcome-adaptive allocation contend that it better accommodates clinical equipoise and promotes informed consent, since such trials limit patient-subject exposure to sub-optimal care. In this essay, we argue that this purported ethical advantage of outcome-adaptive allocation does not stand up to careful scrutiny in the setting of two-armed studies and/or early-phase research.

Ethics and epistemology of accurate prediction in clinical research.

All major research ethics policies assert that the ethical review of clinical trial protocols should include a systematic assessment of risks and benefits. But despite this policy, protocols do not typically contain explicit probability statements about the likely risks or benefits involved in the proposed research. In this essay, I articulate a range of ethical and epistemic advantages that explicit forecasting would offer to the health research enterprise. I then consider how some particular confidence levels may come into conflict with the principles of ethical research.

The risk-escalation model: a principled design strategy for early-phase trials.

Should first-in-human trials be designed to maximize the prospect of therapeutic benefit for volunteers, prioritize avoidance of unintended harms, or aim for some happy medium between the two? Perennial controversies surrounding initiation and design of early-phase trials hinge on how this question is resolved. In this paper, we build on the premise that the task of early-phase testing is to optimize various components of a potential therapy so that later, confirmatory trials have the maximal probability of informing drug development and clinical care. We then explore three strategies that investigators might use to manage trial risks while optimizing a therapy, using cell therapy for Amyotrophic Lateral Sclerosis (ALS) as an example. We argue that an iterative application of maximin strategies over successive cohorts and trials, which we call the "risk-escalation model," establishes a moral principle that should guide decision-making in early-phase trials.

Algorithmic identification of persons with dementia for research recruitment: ethical considerations.

Underdiagnosis, misdiagnosis, and patterns of social inequality that translate into unequal access to health systems all pose barriers to identifying and recruiting diverse and representative populations into research on Alzheimer's disease and Alzheimer's disease related dementias. In response, some have turned to algorithms to identify patients living with dementia using information that is associated with this condition but that is not as specific as a diagnosis. This paper explains six ethical issues associated with the use of such algorithms including the generation of new, sensitive, identifiable medical information for research purposes without participant consent, issues of justice and equity, risk, and ethical communication. It concludes with a discussion of strategies for addressing these issues and prompting valuable research.

Assay sensitivity and the epistemic contexts of clinical trials.

This article examines the concept of assay sensitivity in clinical research. Defined as the ability of a clinical trial to distinguish between an effective and ineffective treatment, the need for assay sensitivity has been taken to support the claim that placebos are methodologically superior to active control treatments. The demands of doing good clinical science must trump the physician-researcher's ethical duty to provide all trial participants with nothing less than competent medical care. We argue that this supposed implication of assay sensitivity rests on (1) collapsing the distinction between biological efficacy and clinical effectiveness, and (2) conflating the epistemic contexts of a trial-as-designed and a trial-as-executed. Once these errors are corrected, it becomes clear that placebos grant no epistemological advantage over active controls, and there is therefore no longer a tension between the epistemic and ethical demands of research. We suggest that the legitimate worries behind assay sensitivity can be better understood as the need for researchers to articulate their experimental heuristics and to demonstrate a robust pattern of evidence across a series of trials.

Digital Health Technologies in Clinical Trials: An Ontology-Driven Analysis to Inform Digital Sustainability Policies.

BACKGROUND: Digital health technologies (DHTs) can facilitate the execution of de-centralized trials that can offer opportunities to reduce the burden on participants, collect outcome data in a real-world setting, and potentially make trial populations more diverse and inclusive. However, DHTs can also be a significant source of electronic waste (e-waste). In recognition of the potential health and environmental impact from DHT use in trials, private and public institutions have recently launched initiatives to help measure and manage this e-waste. But in order to develop sound e-waste management policies, it will be necessary to first estimate the current volume of e-waste that results from the use of DHTs in trials. MATERIALS AND METHODS: A Web Ontology Language (OWL)-compliant ontology of DHTs was created using a list of 500 DHT device names derived from a mixture of public and private sources. The U.S. clinical trials registry, ClinicalTrials.gov, was then queried to identify and classify trials using any of the devices in the ontology. The ClinicalTrials.gov records from this search were then analyzed to characterize the volume and properties of trials using DHTs, as well as estimating the total volume of individual DHT units that have been provisioned (or are planned to be provisioned) for clinical research. RESULTS: Our ontology-driven search identified 2326 unique clinical trials with a reported "actual" enrollment of 200,947 participants and a "planned" enrollment of an additional 4,094,748 participants. The most-used class of DHTs in our ontology was "wearables," (1852 trials), largely driven by the use of smart watches and other wrist-worn sensors (estimated to involve 149,391 provisioned devices). The most-used subtype of DHTs in trials was "subcutaneous" devices (367 trials), driven by the prevalent use and testing of glucose monitors (estimated to involve 17,666 provisioned devices). CONCLUSION: Thousands of trials, involving hundreds of thousands of devices, have already been completed, and many more trials (potentially involving millions more devices) are planned. Despite the great opportunities that are afforded by DHTs to the clinical trial enterprise, if the industry lacks the ability to track DHT use with sufficient resolution, the result is likely to be a great deal of e-waste. A new ontology of DHTs, combined with rigorous data science methods like those described in this paper, can be used to provide better information across the industry, and in turn, help create a more sustainable and equitable clinical trials enterprise.