The judgements that evidence‐based medicine adopts

Abstract

In "The evidence that evidence-based medicine omits", Brendan Clarke and colleagues argue that when establishing causal facts in medicine, evidence of mechanisms ought to be included alongside evidence of correlations. One of the reasons they provide is that correlations can be spurious and generated by unknown confounding variables. A causal mechanism can provide a plausible explanation for the correlation, and the absence of such an explanation is an indication that the correlation is not causal. Evidence-based medicine (EBM) proponents remain sceptical about this argument, one problem being that the formulation of a mechanism requires judgements that are external to the evaluation of data and experimental designs-for instance judgements of plausibility against, or derivability from, background knowledge. Because background knowledge is always incomplete and therefore unreliable, EBM proponents maintain that the plausibility of a hypothesis should be evaluated mainly by the quality of population data that yielded it. Here, I use the example of oestrogen replacement therapy's effect on coronary heart disease, an example that is often quoted in defence of the epistemic advantage of randomized controlled trials, to show that the evaluation of the most reliable study design necessarily implies the adoption of judgements that are external to the specific evidence of correlation. The exclusion of evidence of mechanism, therefore, is not effective in bypassing paradigm-dependent judgements, which are external to specific evidence. Because such judgements cannot be excluded by evidence evaluation, they can only be kept under scrutiny, or adopted uncritically. I propose that the latter option can hinder the maintenance of an active critical inquiry, as well as the analysis of experts' disagreement.

Causal Evidence and Dispositions in Medicine and Public Health

“…This reasoning is built on the assumption that it is possible to make good medical research, aimed to answer the 'whether' and 'how often' questions, without the knowledge of 'how' and 'why'. Such an assumption has been extensively addressed and challenged [2,10,13]. Theoretical understanding of medical observations and correlations is necessary to plan research, design experiments, interpret results, evaluate and weight experimental designs, and to use research findings in clinical decision making.…”

“…A trade-off that de-prioritises theory building and understanding of phenomena, therefore, would ultimately result in an overall decrease in quality of medical research in general, and in an inefficient use of resources. Thus, the correct use of tools such as statistical significance, analysis of frequencies and statistical models ultimately depends on our theoretical understanding of human physiology, pathology, health and illness (see [13] for a detailed argument). We have here tried to show why such knowledge cannot be obtained by using one single methodological approach, but that different methods are useful for picking out different aspects of causality in medicine and public health.…”

“…Although the formal approach is still dominant, there is increasing awareness among scientists that the evaluation of causal hypotheses cannot be restricted to purely statistical standards [12,13]. In a recent commentary in BMJ Evidence Based Medicine, a large group of clinicians, medical researchers and philosophers made a common appeal to evidence-based medicine to expand its notion of 'evidence':…”

Medical scientists and philosophers worldwide appeal toEBMto expand the notion of ‘evidence’

“…The rapid dominance of evidence-based medicine has sparked a philosophical debate concerning the concept of evidence. We urge that evidence-based medicine, if it is to be practised in accordance with its own mandate, should also acknowledge the importance of understanding causal mechanisms 1–7. The undersigned include 42 clinicians and philosophers from interdisciplinary research networks working specifically on questions related to causation in medicine worldwide.…”

“…It also means being explicit about what kind of causal knowledge can be gained through various research methods. The possibility that mechanistic and other types of evidence can be used to add value or initiate a causal claim should not be ignored 3–7 14 15. This appeal for a broader approach to evidence is also important to patients, who need clear information on the benefits and harms of medicines 16…”