Jacob Stegenga (University of Cambridge)
The best methods that clinical scientists employ to test medical interventions, including the randomised trial and meta-analysis, often said to be the pinnacle of research methods in medicine, are, in practice, not nearly as good as they are often made out to be. Moreover, scientists have begun to recognize the complexity of many pathophysiological mechanisms. If we attend to the extent of bias in medical research, the thin theoretical basis of many interventions, the malleability of empirical methods in medicine, and if we employ our best inductive framework, then our confidence in medical interventions ought to be low.

Jonathan Fuller (University of Toronto)
Much skepticism about contemporary medical evidence concerns its relevance for individual patients. Evidence-based medicine's (EBM's) theory of evidence has an epidemiologic orientation, focusing on epidemiological, population-level outcomes. It also has an ontic orientation, concerned ultimately with measuring these outcomes. It fails to address questions like: how strongly should the physician believe that the treatment will prevent/cause this patient's death? I propose a rival Personal Evidential Support Theory (PEST) in which medical evidence confirms (supports) or disconfirms 'personal' patient-relevant hypotheses. I compare PEST to EBM's theory through the case of cholesterol-lowering therapy and argue that PEST partly overcomes EBM's relevance crisis.

Nancy Cartwright (University of California, San Diego)
Orthodox medical opinion is sceptical about methodology for singular causal claims. It is widely maintained that we cannot establish causation in the single case; and, if we could, this would be fairly useless because such claims would not be generalizable. Nor can singular causal claims allow us to estimate effect sizes measuring how well on average one treatment performs compared with another. This talk will dispute this scepticism, and counter with a scepticism of my own: Neither can the favoured methods provide 'generalizable' effect sizes.

Mark Tonelli (University of Washington) with Jon Williamson (University of Kent)

Over the last two decades, medical epistemology has been largely focused on epidemiologic information derived from various forms of clinical research and from statistical manipulations of empirical data. With this prioritization, skepticism regarding the value of other kinds of medical knowledge, in particular knowledge of mechanisms, has risen disproportionally. This lopsided skepticism is most evident in the ‘hierarchies of evidence’ promulgated by proponents of evidence-based medicine. Some philosophical attention has been paid to the role of mechanism in medicine, particularly as it relates to determination of causality and, most recently, the potential value for clinical guideline development. The role of mechanism and mechanistic reasoning in clinical practice has been relatively unexamined. We argue that mechanistic understanding and pathophysiologic reasoning remain an integral part of clinical practice, crucial for evaluating reports of clinical research, arriving at diagnostic and treatment decisions, and assessing treatment effects. Some account of biologic plausibility in the form of a putative mechanism of action accompanies virtually every clinical trial describing a new intervention. This mechanistic description may provide support for making a causal inference regarding a positive statistical association and can also be viewed as a component of the background knowledge that clinicians bring to a Bayesian assessment of new information.  A lack of a convincing mechanism linking treatment to effect leads to clinicians discounting such an association.  In coming to diagnostic and therapeutic decisions regarding patients, clinicians use mechanistic reasoning to extrapolate from population-level research. Pathophysiologic rationale is necessary for both analogical reasoning from “average” patients and for extrapolating from reference classes determined by population-level research. Finally, mechanistic reasoning is crucial for assessing whether a medical intervention is working as anticipated in particular individuals. When not, changes in treatment strategy are usually necessary, changes that will also be guided by pathophysiologic reasoning. The use of mechanistic reasoning in clinical practice is ubiquitous and epistemically justified. The high degree of skepticism toward appeals to mechanism in practice is inappropriate, particularly as understanding of mechanisms in medicine continues to improve.  Reasoning about and from mechanism will remain a crucial skill of clinicians aiming to optimize the care of individual patients.   

Kathryn Tabb (Columbia University)
The Precision Medicine Initiative introduced by the Obama administration in 2015 has been heralded as a paradigm shift in medicine. Here I make both historical and philosophical arguments against the virtue of medical precision, and in favor of a competing virtue that I call "medical skepticism." Medical skepticism originated in Pyrrhonian philosophy, and I discuss its rediscovery in the early modern period, when physicians argued against physiological explanations in favor of reliable correlations between diagnoses and interventions. I conclude that this history can help bring the contingency of the current vogue for precision into view, and provide an intriguing alternative.