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)

When appraising research papers, how much understanding is enough? More specifically, in deciding whether research results can inform practice, do appraisers need to substantively understand how findings are derived or is it sufficient simply to grasp that suitable analytic techniques were chosen and used by researchers? The degree or depth of understanding that research appraisers need to attain before findings can legitimately/sensibly inform practice is underexplored. In this paper it is argued that, where knowledge/justified beliefs derived from research evidence prompt (...) actions that materially affect patient care, appraisers have an epistemic duty to demand high (maximal) rather than low (minimal) levels of understanding regards finding derivation (i.e. appraisers have a duty to seek a superior epistemic situation). If this argument holds assumptions about appraiser competence/ability and the feasibility of current UK conceptions of evidence based practice are destabilized. (shrink)

The standardised randomised clinical trial (RCT) has been exceedingly popular in medical research, economics, and practical policy making. Recently, RCTs have faced criticism. First, it has been argued by John Worrall that we cannot be certain that our sample is not atypical with regard to possible confounding factors. I will argue that at least in the case of medical research, we know enough about the relevant causal mechanisms to be justified to ignore a number of factors we have good reason (...) not to expect to be disruptive. I will also argue against an argument provided by Nancy Cartwright and Eileen Munro that RCTs should not be taken to deductively infer probabilistic causal claims, but ampliatively. The paper will end on a discussion of evidence hierarchies and a defence of the stance of evidence-based medicine that RCTs are the best available method to assess a treatment’s efficacy. (shrink)