Abstract
Clinical equipoise (CE) has been proposed as an ethical principle relating uncertainty and moral leeway in clinical research. Although CE has traditionally been indicated as a necessary condition for a morally justified introduction of a new RCT, questions related to the interpretation of this principle remain woefully open. Recent proposals to rehabilitate CE have divided the bioethical community on its ethical merits. This paper presents a new argument that brings out the epistemological difficulties we encounter in justifying CE as a principle to connect uncertainty and moral leeway in clinical ethics. The argument proposes, first, that the methodology of hypothetical retrospection (HR) is applicable to the RCT design and that it can accommodate uncertainty. As currently understood, however, HR should give up its reliance on the assumption of uncertainty transduction, because the latter assumes the principle of indifference, which does not accommodate uncertainty in the right way. The same principle is then seen to distort also the received interpretations of CE.
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Notes
Stanev (2015) shows that the current practice in adopting early stopping rules may be due to mistaken interpretations of the relevant statistical results that have their roots in uncritical acceptance of error statistics underlying the decisions to implement these rules.
In the light of this issue, IE might be better expressed using alternative methods, such as confidence intervals or non-additive probabilities, rather than standard probability measures.
Freedman (1987b) clarified that beyond scientific validity, an important requirement for medical ethics is the clinical value of a hypothesis. It is specifically on the clinical value that there may be disagreement in the community of experts as indicated by CE.
For a classical analysis of bounded rationality in which the rationality of decisions is shaped by the limitations of time, information and other contextual factors see, for instance, Tversky and Kahneman (1981). Their view, which is “heuristics as errors” in reasoning, takes optimal and analytic procedures to be supplanted in human economizing decisions by suboptimal but fast procedures of reasoning that achieve practical goals with less expenditure on time, money and cognitive effort. For a critical analysis of this paradigm, see (Gigerenzer et al. 1991), among others.
The confusion of “conditions of risk” with “conditions of severe uncertainty” is called the “Tuxedo Fallacy” (see e.g. Hansson 2009).
Even such continued and completed trials are unlikely to achieve the desired sufficiency of evidence, or evidence that is stronger than the initial evidence from early phases of a trial. Such a phenomenon adds to the reasons why systematic reviews and meta-analyses are also required in order for a research to achieve the evidential status concerning it effect sizes and the respective clinical conditions, hospital practices and proposed treatments. The well-known demand for meta-analyses is due to the problems of triangulations of different sources of evidence and to the persistent lack of replicability of findings on specific clinical questions. This, in turn, is a symptom of underlying biases involved at all stages of experimentation and publication of results (Ioannidis 2005). Our paper could be read as adding to this observation the further consequence that even the multi-site, fixed-effect meta-analyses may not solve the problem of the reliability of evidence, whenever the only mode of variance between the trials is within-studies. We thank the reviewer for raising this important point. What the precise implications of these epistemological considerations are to the validity of random-effect meta-analyses we leave for further investigation.
This follows from such designs being biased towards a likelihood that the effect sizes of those trials between competing research teams working on the same problem are exaggerated by those who are the first to report their positive findings. This is an instant of the bias known as the Winner’s Curse.
The logical model for such hypothetical retrospections is a branching-time model.
Exitus may or may not be ruled out, depending on the patients’ desires, wishes, wills and testimonies, severity of conditions and the gravity of suffering, among others.
Common examples of the failure of UT can be drawn from game theory. Let us mention two: (1) games that use the “burning bridges” strategies: they involve actions that intentionally limit the range of one’s own options in order to signal a credible commitment to the opponent and in which way to avoid a conflict, and (2) games in which the epistemic states of the agents are also taken into account in the decisions (see, Chiffi and Pietarinen 2017).
Typically those in which it is unlikely that some unforeseen clinical conditions may crop up, such as those aimed at corroboration of another large study that already has investigated the same clinical question. But even in these cases the effect sizes may vary as the patient populations, cultures and clinical practices are far from identical.
For a discussion of another essential problem of RCTs, i.e. their external validity, see (Cartwright 2007).
There is also the important wider question is whether even the random-effect meta-analyses can be free from appeals to the PoI under residual fundamental uncertainty.
There are some wider theoretical issues lurking at the back of these arguments. We mention two. First, any uncritical or unrecognized presupposition of the PoI and the related confounding of risk-laden situations with fundamental uncertainty is likely to have a negative impact on what the positive predictive values of large experimental studies are. This adds grist to Ionnadis’s mill (Ioannidis 2005). Second, the practice of current clinical research is mainly frequentist. Would a Bayesian perspective on the design of RCTs be more suitable in handling (some variants of) CE, so much so that it could turn it into an epistemic, quantifiable component obtained by prior elicitation of a Bayesian assessment of evidence? For instance, the notion of “admissibility of treatments” in a Bayesian trial may determine the restriction of possible treatments to a certain subgroup of subjects in order to ensure that a specific patient is not administered an inferior treatment (as judged by a committee of experts) merely for the reason that it would facilitate the completion of a trial (see Sedransk 1996). On the other hand, there are concerns on the epistemological and ethical validity and limits to such Bayesian approaches (see e.g. Teira 2010).
On the analysis of the role of uncertainty and future scenarios for clinical reasoning, see (Chiffi and Zanotti 2017b).
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Acknowledgements
Supported by the Estonian Research Council (“Abduction in the Age of Fundamental Uncertainty”, PUT 1305). Earlier version of this paper has been presented at Biom Conference in Pistoia, Le humanitas in ambito biomedico. We thank Cristina Amoretti, Mattia Andreoletti, Marco Annoni, Paola Berchialla, Federico Boem, Giovanni Boniolo, Raffaella Campaner, Pierdaniele Giaretta, Alessandro Pagnini and Federica Russo for their suggestions. We thank the two referees for their insightful and substantial remarks on the earlier version of the present paper.
Funding
Estonian Research Council, Research Grant, Abduction in the age of fundamental uncertainty (PUT 1305).
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Chiffi, D., Pietarinen, AV. Clinical Equipoise and Moral Leeway: An Epistemological Stance. Topoi 38, 447–456 (2019). https://doi.org/10.1007/s11245-017-9529-x
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DOI: https://doi.org/10.1007/s11245-017-9529-x