Harms of medical interventions are systematically underestimated in clinical research. Numerous factors—conceptual, methodological, and social—contribute to this underestimation. I articulate the depth of such underestimation by describing these factors at the various stages of clinical research. Before any evidence is gathered, the ways harms are operationalized in clinical research contributes to their underestimation. Medical interventions are first tested in phase 1 ‘first in human’ trials, but evidence from these trials is rarely published, despite the fact that such trials provide the (...) foundation for assessing the harm profile of medical interventions. If a medical intervention is deemed safe in a phase 1 trial, it is tested in larger phase 2 and 3 clinical trials. One way to think about the problem of underestimating harms is in terms of the statistical ‘power’ of a clinical trial—the ability of a trial to detect a difference of a certain effect size between the experimental group and the control group. Power is normally thought to be pertinent to detecting benefits of medical interventions. It is important, though, to distinguish between the ability of a trial to detect benefits and the ability of a trial to detect harms. I refer to the former as power-B and the latter as power-H. I identify several factors that maximize power-B by sacrificing powerH in phase 3 clinical trials. If a medical intervention is approved for general use, it is evaluated by phase 4 post-market surveillance. Phase 4 surveillance of harms further contributes to underestimating the harm profile of medical interventions. At every stage of clinical research the hunt for harms is shrouded in secrecy, which further contributes to the underestimation of the harm profiles of medical interventions. (shrink)

The problem of collecting, analyzing and evaluating evidence on adverse drug reactions (ADRs) is an example of the more general class of epistemological problems related to scientific inference and prediction, as well as a central problem of the health-care practice. Philosophical discussions have critically analysed the methodological pitfalls and epistemological implications of evidence assessment in medicine, however they have mainly focused on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special (...) attention to the privileged role assigned to randomized controlled trials in Evidence Based Medicine. Regardless of whether the RCT’s privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference of intended and unintended effects, in that the unknowns at stake are heterogonous in the two contexts. This point has been emphasized by epidemiologists in the last decade. Their main focus is methodological, and regards the fact that bias and confounding do not affect studies on intended and unintended effects in the same way. However, deeper concerns ground the intuition for such a distinction; these are related to the constraints which we impose on evidence and their epistemological justification. My thesis is that such constraints ought to be understood to be different in the case of evidence for risk vs. benefit assessment. I present the recent debate on the causal association between acetaminophen and asthma in order to illustrate the point at issue. (shrink)

Philosophical discussions have critically analysed the methodological pitfalls and epistemological implications of evidence assessment in medicine, however they have mainly focused on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special attention to the privileged role assigned to randomized controlled trials (RCTs) in evidence based medicine. Regardless of whether the RCT’s privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference of intended and unintended (...) effects, in that the unknowns at stake are heterogonous in the two contexts. However, although “lower level” evidence is increasingly acknowledged to be a valid source of information contributory to assessing the risk profile of medications on theoretical or empirical grounds, current practices have difficulty in assigning a precise epistemic status to this kind of evidence because they are more or less implicitly parasitic on the (statistical) methods developed to test drug efficacy. My thesis is that (1) “lower level” evidence is justified on distinct grounds and at different conditions depending on the different epistemologies which one wishes to endorse, in that each impose different constraints on the methods we adopt to collect and evaluate evidence; (2) such constraints ought to be understood to be different in the case of evidence for risk versus benefit assessment for a series of reasons which I will illustrate on the basis of the recent debate on the causal association between acetaminophen (a.k.a. paracetamol) and asthma. (shrink)

I propose an amendment of Lewis's counterfactual analysis of causation, designed to overcome some difficulties concerning redundant causation.

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

Conceptual analysis of health and disease is portrayed as consisting in the confrontation of a set of criteria—a “definition”—with a set of cases, called instances of either “health” or “ disease.” Apart from logical counter-arguments, there is no other way to refute an opponent’s definition than by providing counter-cases. As resorting to intensional stipulation is not forbidden, several contenders can therefore be deemed to have succeeded. This implies that conceptual analysis alone is not likely to decide between naturalism and normativism. (...) An alternative to this approach would be to examine whether the concept of disease can be naturalized. (shrink)

Debates about the ethics and effects of placebos and whether ‘placebos’ in clinical trials of complex treatments such as acupuncture are adequate rage. Yet there is currently no widely accepted definition of the ‘placebo’. A definition of the placebo is likely to inform these controversies. Grünbaum’s characterization of placebos and placebo effects has been touted by some authors as the best attempt thus far, but has not won widespread acceptance largely because Grünbaum failed to specify what he means by a (...) therapeutic theory and because he does not stipulate a special role for expectation effects. Grünbaum claims that placebos are treatments whose ‘characteristic features’ do not have therapeutic effects on the target disorder. I show that with four modifications, Grünbaum’s definition provides a defensible account of placebos for the purpose of constructing placebo controls within clinical trials. The modifications I introduce are: adding a special role for expectations, insisting that placebo controls control for all and only the effects of the incidental treatment features, relativizing the definition of placebos to patients, and introducing harmful interventions and nocebos to the definitional scheme. I also provide guidance for classifying treatment features as characteristic or incidental. (shrink)

Philosophers of science have insisted that evidence of underlying mechanisms is required to support claims about the effects of medical interventions. Yet evidence about mechanisms does not feature on dominant evidence-based medicine “hierarchies.” After arguing that only inferences from mechanisms (“mechanistic reasoning”)—not mechanisms themselves—count as evidence, I argue for a middle ground. Mechanistic reasoning is not required to establish causation when we have high-quality controlled studies; moreover, mechanistic reasoning is more problematic than has been assumed. Yet where the problems can (...) be overcome, mechanistic reasoning can and should be used as evidence. (shrink)

The standard philosophical definition of placebos offered by Grünbaum is incompatible with Cartwright’s conception of randomized clinical trials. I offer a modified account of placebos that respects this role and clarifies why many current medical trials fail to warrant the conclusions they are typically seen as yielding. I then consider recent changes to guidelines for reporting medical trials and show that pessimism over parsing out the cause of “unblinding” is premature. Specifically, using a trial of antidepressants, I show how more (...) sophisticated statistical analyses can parse out the source of such effects and serve as an alternative to placebo control. (shrink)

Each of the antiretroviral drugs that are currently used to stop the progression of HIV infection causes its own specific side effects. Despite the expansion, multiplication, and simplification of treatment options over the past decade, side effects continue to affect people living with HIV. Yet, we see a clear disconnect between the way side effects are normalized, routinized, and framed in clinical practice and the way they are experienced by people living with HIV. This paper builds on the premise that (...) new approaches are needed to understand side effects in a manner that is more reflective of the subjective accounts of people living with HIV. Drawing on the work of Deleuze and Guattari, it offers an original application of the theory of ‘assemblage’. This theory offers a new way of theorizing side effects, and ultimately the relationship between the body and antiretroviral drugs (as technologies). Combining theory with examples derived from empirical data, we examine the multiple ways in which the body connects not only to the drugs but also to people, things, and systems. Our objective is to illustrate how this theory dares us to think differently about side effects and allows us to originally (re)think the experience of taking antiretroviral drugs. (shrink)

This paper offers a critical analysis of several accounts of the placebo effect that have been put forward. While the placebo effect is most often thought of as a control in research and as a deceptive tool in practice, a growing body of research suggests that it ought to be thought of as a powerful phenomenon in its own right. Several accounts that aim to draw boundaries around the placebo effect are evaluated in relation to current evidence and it is (...) argued that none of them adequately capture the variability and potency of the phenomenon. Two accounts, however, that point towards the underlying mechanisms of the placebo effect, are shown to offer promise in terms of developing a more comprehensive account of the placebo effect. (shrink)

Phase I clinical trials are the first stage of testing new pharmaceuticals in humans. The majority of these studies are conducted under controlled, inpatient conditions using healthy volunteers who are paid for their participation. This article draws on an ethnographic study of six phase I clinics in the United States, including 268 semistructured interviews with research staff and healthy volunteers. In it, I argue that an institutional banalization of risk structures the perceptions of research staff and healthy volunteers participating in (...) the studies. For research staff, there are three mechanisms by which risk becomes banal: a perceived homogeneity of studies, Fordist work regimes, and data-centric discourse. For healthy volunteers, repeat study participation contributes to the institutional banalization of risk both through the process of desensitization to risk and the formation of trust in the clinics. I argue that the institutional banalization of risk also renders invisible ethical concerns about exploitation of underprivileged groups in pharmaceutical research. (shrink)

Mechanisms are now taken widely in philosophy of science to provide one of modern science’s basic explanatory devices. This has raised lively debate concerning the relationship between mechanisms, laws and explanation. This paper focuses on cases where a mechanism gives rise to a ceteris paribus law, addressing two inter-related questions: What kind of explanation is involved? and What is going on in the world when mechanism M affords behavior B described in a ceteris paribus law? We explore various answers offered (...) by ‘new mechanists’ and others before setting out and explaining our own answers: mechanistic explanations are a species of oldfashioned covering-law explanation and this often accounts in part for their explanatory power; and B is what it takes for some set of principles that govern the features of M’s parts in their arrangement in M all to be instanced together. (shrink)

In the field of placebo studies residual disagreement about the terminology ‘placebo’ and ‘placebo effect’ still persists. We differentiate between the conceptualization of placebos in clinical trials; and placebo effects understood as a psychobiological phenomenon. With respect to the latter, we argue that a scientific ‘placebo paradigm’ has emerged, indicating that—at least among placebo scientists—there exists relatively stable consensus about how to conceive of placebo effects. We claim that existence of a placebo paradigm does not protect concepts from revision; nonetheless, (...) we argue that scientific progress is dependent on, and guided by relative conceptual stability. Therefore, to mount persuasive arguments for conceptual revision in respect of ‘placebo effects’ we argue, critics either need to defend the claim that a placebo paradigm is not underway, or that there are major scientific failings in respect of it. With these considerations in mind we examine three alternative proposals for conceptual reform: Grünbaum/Howick’s relativity models of placebo concepts; Moerman/Brody’s meaning response; and Nunn/Turner’s proposal for conceptual eliminativism. We derive two conclusions from this evaluation. First, we conclude that no convincing arguments have so far been presented for conceptual overhaul of ‘placebo effects.’ Notwithstanding this analysis, we conclude that refinement of this concept is likely. Second, we agree with Turner and Nunn that the term ‘placebo’ in the context of randomized controlled trials remains a source of confusion for many researchers, risking the design and scientific integrity of clinical findings. Therefore, in these contexts, replacing the term ‘placebo’ with ‘control’ is justified. (shrink)

Drug regulation is fraught with inductive risk. Regulators must make a prediction about whether or not an experimental pharmaceutical will be effective and relatively safe when used by typical patients, and such predictions are based on a complex, indeterminate, and incomplete evidential basis. Such inductive risk has important practical consequences. If regulators reject an experimental drug when it in fact has a favourable benefit/harm profile, then a valuable intervention is denied to the public and a company’s material interests are needlessly (...) thwarted. Conversely, if regulators approve an experimental drug when it in fact has an unfavourable benefit/harm profile, then resources are wasted, people are needlessly harmed, and other potentially more effective treatments are underutilized. Given that such regulatory decisions have these practical consequences, non-epistemic values about the relative importance of these consequences impact the way such regulatory decisions are made (similar to the analysis of laboratory studies on the toxic effects of dioxins presented in Douglas [2000]). To balance the competing demands of the pertinent non-epistemic values, regulators must perform what I call an “inductive risk calculus.” At least in the American context this inductive risk calculus is not well-managed. (shrink)