Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in (...) explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM. (shrink)

Medical classification systems aim to provide a manageable taxonomy for sorting diagnoses into their proper classes. The question, this paper wants to critically examine, is how to correctly systematise diseases within classification systems that are applied in a variety of different settings. ICD and DSM , the two major classification systems in medicine and psychiatry, will be the main subjects of this paper; however, the arguments are not restricted to these classification systems but point out general methodological and epistemological challenges (...) of classifying diseases for differing purposes. Deciding what qualifies as a disease to be included into a classification system as well as choosing a specific validator for correctly systematising diseases is complicated because the broad applicability of medical classification systems simultaneously appears as aim and challenge. Drawing upon the case study of classifying Alzheimer’s disease, this paper will address three dilemmas in designing ‘good’ medical classification systems. They are due to general epistemological problems of medicine, such as the relationship between individual manifestations of diseases and the necessity of building groups in order to scientifically elucidate causes of diseases. Moreover, they involve pragmatic issues of designing usable classifications that allow for easily discriminating between classes of diseases, restricting, however, the completeness of disease representations. This paper wants to trace how the choice of certain validators is unavoidably value-laden and deeply intertwined with epistemological assumptions of how different uses relate to each other, resulting either in a prioritisation of (constrained) coherence or of (vague) pluralistic connectibility. (shrink)