Spencer Hey

Randomized controlled trial 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, 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. Semi-structured interviews with key stakeholders, across multiple jurisdictions, identified based on their known experience and/or expertise with pragmatic trials. 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.

ObjectivesTo 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.MethodsSurvey of primary trial reports, published 2014–2019, identified using an electronic search filter for pragmatic trials implemented in MEDLINE, and registered in ClinicalTrials.gov.ResultsAmong 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).DiscussionNot 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.

Key messages The research environment has changed since clinical equipoise was first proposed 30 years ago New trial designs—such as umbrella and basket trials, adaptive platform trials, and cluster randomised trials—raise new ethical challenges for evaluating the state of scientific uncertainty and communicating about risks with patients and participants Clinical equipoise needs to evolve We propose the design of specific guidelines to provide ethics committees and trialists with instructions for how to evaluate equipoise in the context of new designs and biomarkers and how to optimise communication with participants.

In the first half of this dissertation, I develop a heuristic methodology for analyzing scientific solutions to the problem of underdetermination. Heuristics are rough-and-ready procedures used by scientists to construct models, design experiments, interpret evidence, etc. But as powerful as they are, heuristics are also error-prone. Therefore, I argue that they key to prudently using a heuristic is the articulation of meta-heuristics---guidelines to the kinds of problems for which a heuristic is well- or ill-suited. Given that heuristics will introduce certain errors into our scientific investigations, I emphasize the importance of a particular category of meta-heuristics involving the search for robust evidence. Robustness is understood to be the epistemic virtue bestowed by agreement amongst multiple modes of determination. The more modes we have at our disposal, and the more these confirm the same result, the more confident can we be that a result is not a mere artifact of some heuristic simplification. Through an analysis of case-studies in the philosophy of biology and clinical trials, I develop a principled method for modeling and evaluating heuristics and robustness claims in a qualitative problem space. The second half of the dissertation deploys the heuristic methodology to address ethical and epistemological issues in the science of clinical trials. To that end, I develop a network model for the problem space of clinical research, capable of representing the various kinds of experiments, epistemic relationships, and ethical justifications intrinsic to the domain. I then apply this model to ongoing research with the antibacterial agent, moxifloxacin, for the treatment of tuberculosis, tracking its development from initially successful and promising in vitro and animal studies to its disappointing and discordant performance across five human efficacy trials. Given this failure to find a robust result with moxifloxacin across animal and human studies, what should researchers now do? While my final analysis of this case does not definitively answer that question, I demonstrate how my methodology, unlike a statistical meta-analysis, helps to clarify the directions for further research.

The high price of drugs is receiving due consideration from ethicists, policymakers, and legislators. However, much of this attention has focused on the difference between the cost of drug development and company profits and the possible laws and regulations that could limit a drug’s price once it reaches market. By contrast, little attention has been paid to the ethical implications of high drug prices for the research subjects whose bodies were essential to the drug’s development. Indeed, the future price of a drug is routinely ignored and treated as unknowable during the ethical evaluation of the clinical trials that support its development. In this paper, I will argue that ignoring the future price of a drug during the research process is in tension with all three of the major principles of research ethics: it fails to show respect for the research participants, undermines the quality of risk/benefit judgements made by ethical review committees, and makes it impossible to judge future patient access and assess justice.

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. Given that there are limited human and material resources available for testing experimental therapeutics, this theory- and explanation-driven strategy of drug development seems to make good sense: it narrows the number of plausible drug candidates to be put through rigorous and expensive testing; it potentially improves the success rate of clinical translation; and it provides some epistemological basis to extrapolate evidence from one domain to another and potentially minimize risks to patient-subjects.Yet...

Ethics guidelines and commentary suggest that a central function of research ethics committees is to assess the scientific merit of the protocols they review. However, some commentators object to this role, and evidence suggests that the assessment of scientific merit is a significant source of confusion and animosity between ethics committees and clinical investigators. In this essay, we argue that ethics committees should assess the scientific value and validity of research protocols and that new decision-making tools are needed to help them do so in a systematic, transparent, and reliable way. We present a novel ethical framework that can assist in this task.

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.

The ethics of the Flexibility In duty hour Requirements for Surgical Trainees 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 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?

What makes a high-quality biomarker experiment? The success of personalized medicine hinges on the answer to this question. Unfortunately, as many commentators have now emphasized, the quality of most biomarker experiments to date has been quite low. Although the technical side of this problem has received considerable attention, the philosophical issues remain largely unexplored. In this paper, I argue that understanding what constitutes a high-quality biomarker experiment requires some fundamental shifts in how we think about the epistemology, ontology, and methodology of clinical translation.

In their essay, ‘When Clinical Trials Compete: Prioritizing Study Recruitment’, Gelinas et al describe a collective action problem that can arise if multiple trials at a single institution are all trying to recruit participants from the same patient population. Each trial may be addressing an important question, and each will need a certain number of participants to provide an informative answer. But because these trials are all recruiting from the same population, it is possible that there will not be enough participants to go around. It may turn out, then, that none successfully achieves its target sample size and all end up being uninformative or less informative than hoped. As Gelinas et al observe, these kinds of uninformative or less-informative trials are ethically problematic, since they fail to fully redeem participant risks and burdens with adequate gains in generalisable knowledge. Such trials also represent wasteful or inefficient research activities, since each necessarily has a human and material cost, but then fails to offset these costs by providing a definitive answer to the research …

One of the central goals of precision medicine is to dissolve the long-standing tension between the population-level data provided by traditional randomized controlled trials and the physician’s need to prescribe therapies for their individual patient. The RCT can tell the physician that therapy A is, on average, more effective than therapy B for a population of patients, P, but this does not tell her whether A is more effective for the particular patient, p1, in front of her. However, by leveraging the tools and insights of molecular biology, precision medicine hopes to prospectively determine which therapies will work for which patients and overcome this problem. Fundamental to the...

John Worrall and Nancy Cartwright have both argued that randomized controlled trials are “testing the wrong theory.” They claim that RCTs are designed to test inferences about the causal relationships in the study population, but this does not guarantee a justified inference about the causal relationships in the more diverse population in clinical practice. In this article I argue that the epistemology of theory testing in trials is more complicated than either Worrall’s or Cartwright’s accounts suggest. I illustrate this more complex theoretical structure with case studies in medical theory testing from Alzheimer’s research and anticancer drugs in personalized medicine

In February 2010, the World Medical Association hosted an international symposium on the ethics of placebo controls in clinical trials (WMA 2010). Despite years of debate, ethicists, clinical trialists, and policy makers remain divided over the ethical acceptability of using placebos in research when a proven, effective treatment is available. The protracted nature of this problem is due, at least in part, to a perceived conflict between the opposing demands placed on clinical research by science and ethics. A good, scientifically valid trial, it is argued, must be “assay sensitive,” and without using a placebo control, there can be no guarantee that it is. In this article, we revisit some of the claims made about ..

The concordance of results that are “robust” across multiple scientific modalities is widely considered to play a critical role in the epistemology of science. But what should we make of those cases where such multimodal evidence is discordant? Jacob Stegenga has recently argued that robustness is “worse than useless” in these cases, suggesting that “different kinds of evidence cannot be combined in a coherent way.” In this article I respond to this critique and illustrate the critical methodological role that robustness plays as an aim of scientific inquiry.

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

Many hold that the so-called golden era of antibiotic discovery has passed, leaving only a limited clinical pipeline for new antibiotics. A logical conclusion of such arguments is that we need to reform the current system of antibiotic drug research—including clinical trials and regulatory requirements—to spur activity in discovery and development. The United States Congress in the past few years has debated a number of bills to address this crisis, including the 2012 Generating Antibiotic Incentives Now Act and the 2016 21st Century Cures Act. Experts have also sought to advance antibiotic development by encouraging greater use of trials with noninferiority hypotheses, which are thought to be easier to conduct. The goal underlying these proposals is to stave off the post-antibiotic era by expanding the pharmaceutical armamentarium as quickly as possible. But although new antibiotic agents are necessary to combat the long-term threat of drug-resistant disease, we argue that these research policies, which effectively lower the bar for antibiotic approval, are ethically problematic. Rather, given broader public health considerations related to the full lifecycle of antibiotic use—including development of resistance—we should reject an overly permissive approach to new antibiotic approval and instead set the bar for regulatory approval at a point that will naturally direct research resources toward the most transformative chemical or social interventions.

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.

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.

What makes a high-quality biomarker experiment? The success of personalized medicine hinges on the answer to this question. In this paper, I argue that judgment about the quality of biomarker experiments is mediated by the problem of theoretical underdetermination. That is, the network of biological and pathophysiological theories motivating a biomarker experiment is sufficiently complicated that it often frustrates valid interpretation of the experimental results. Drawing on a case-study in biomarker diagnostic development from neurooncology, I argue that this problem of underdetermination can be overcome with greater coordination across the biomarker research trajectory. I then sketch an account for how coordination across a research trajectory can be evaluated. I ultimate conclude that what makes a high-quality biomarker experiment must be judged by the epistemic contribution it makes to this coordinated research effort.

Despite the increasing recognition that heuristics may be involved in myriad scientific activities, much about how to use them prudently remains obscure. As typically defined, heuristics are efficient rules or procedures for converting complex problems into simpler ones. But this increased efficiency and problem-solving power comes at the cost of a systematic bias. As Wimsatt showed, biased modelling heuristics can conceal errors, leading to poor decisions or inaccurate models. This liability to produce errors presents a fundamental challenge to the philosophical value of heuristic analyses. Heuristics may be powerful and efficient procedures, but their practical value for science and epistemology is significantly mitigated if we do not have a principled methodology for knowing how to use them wisely. In this essay, I extend Wimsatt’s analyses to argue that this challenge for a heuristic methodology can be met by appealing to second-order, or meta-, heuristics—that is, practical guidelines that prescribe the appropriate conditions for a first-order heuristic’s use. 1 Introduction2 Background3 Heuristics and Meta-heuristics4 A Hierarchical Model and Three Applications4.1 Decision making in emergency medicine4.2 Mathematical explanation in physics4.3 Resilience in ecological management5 Conclusion.