Many philosophers and medical scientists assume thatdisease categories or entities used to classify concrete cases ofdisease, are often defined by disease mechanisms or causalprocesses. Others suggest that diseases should always be definedin this manner. This paper discusses these standpoints criticallyand concludes that they are untenable, not only when `diseasemechanism' refers to an objective mechanism, but also when`mechanism' refers to a pragmatically demarcated part of thetotal ``objective'' causal structure of diseases. As an alternativeto principles that use the concept of disease mechanism (...) oranalogous concepts, a pragmatic approach is suggested anddescribed. This approach has been suggested before, but inproblematic or inadequate versions. This paper proposes a versioncompiled of two ``pragmatic principles'' and shows that they aremuch more adequate than the principle of disease mechanism. Withreference to a case study of a still ongoing internationaldiscussion of various candidates for a classification system formalignant lymphomas, including REAL (Revised European–AmericanClassification of Lymphoid Neoplasms) in which the concept ofdisease mechanism or analogous concepts plays a very small part,it is shown just how pivotal these two pragmatic principles canbe in actual discussions of definitions of diseases. Finally, itis pointed out that with regard to modern philosophy of languageit may, at least in some cases, be problematic to distinguishbetween the two pragmatic principles as they stand. (shrink)

There is a profound paradox in modern medical knowledge production: The more we know, the more we know that we (still) do not know. Nowhere is this more visible than in diagnostics and early detection of disease. As we identify ever more markers, predictors, precursors, and risk factors of disease ever earlier, we realize that we need knowledge about whether they develop into something experienced by the person and threatening to the person’s health. This study investigates how advancements in science (...) and technology alter one type of uncertainty, i.e., temporal uncertainty of disease diagnosis. As diagnosis is related to anamnesis and prognosis it identifies how uncertainties in all these fields are interconnected. In particular, the study finds that uncertainty in disease diagnosis has become more subject to prognostic uncertainty because diagnosis is more connected to technologically detected indicators and less closely connected to manifest and experienced disease. These temporal uncertainties pose basic epistemological and ethical challenges as they can result in overdiagnosis, overtreatment, unnecessary anxiety and fear, useless and even harmful diagnostic odysseys, as well as vast opportunity costs. The point is not to stop our quest for knowledge about disease but to encourage real diagnostic improvements that help more people in ever better manner as early as possible. To do so, we need to pay careful attention to specific types of temporal uncertainty in modern diagnostics. (shrink)

Elselijn Kingma argues that Christopher Boorse’s biostatistical theory does not show how the reference classes it uses—namely, age groups of a sex of a species—are objective and naturalistic. Boorse has replied that this objection is of no concern, because there are no examples of clinicians’ choosing to use reference classes other than the ones he suggests. Boorse argues that clinicians use the reference classes they do because these reflect the natural classes of organisms to which their patients belong. Drawing on (...) a thorough exploration of how the disease osteoporosis is defined in adults, I argue that clinicians do indeed make choices about which reference classes to use in diagnosis. Clinicians use young adult reference classes to diagnose osteoporosis in elderly patients. They also use young female reference classes to diagnose osteoporosis in elderly males. Clinicians adjust their reference classes so that the diagnosis of osteoporosis reflects a person’s risk of sustaining a fragility fracture. The ethical intuition that people with the same risk of fracture should receive the same diagnosis overwhelms the naturalistic intuition that reference classes should reflect natural classes of organisms of uniform functional design. Clinicians construct a variety of reference class types, including pathological reference classes and epidemiological population-specific reference classes, to serve this ethical intuition. I show how clinicians use several reference classes at once so that they can more accurately predict risk of fracture. Ultimately, the reference classes chosen and used in medical practice are quite different from those proposed in naturalistic philosophy of medicine. (shrink)

The measurement of diagnostic accuracy is an important aspect of the evaluation of diagnostic tests. Sometimes, medical researchers try to discover the set of observations that are most accurate of all by directly inspecting diseased and not-diseased patients. This method is perhaps intuitively appealing, as it seems a straightforward empirical way of discovering how to identify diseased patients, which amounts to trying to correlate the results of diagnostic tests with disease status. I present three examples of researchers who try to (...) produce definitive diagnostic criteria by directly inspecting diseased and not diseased patients. Despite this method’s intuitive appeal, I will argue that it is impossible to carry out. Before researchers can inspect these patients to discover definitive diagnostic criteria, they must be able to distinguish diseased and not-diseased patients; and they do not know how to do this, because this is what they are trying to discover. I suspect the intuitive appeal of directly inspecting patients makes this difficult to appreciate. To counter this difficulty, I present this problem as a manifestation of ‘Meno’s paradox’, which was described in classical antiquity, and of ‘the problem of nomic measurement’, described more recently. Considering these philosophical problems may help researchers address the methodological issues they face when evaluating diagnostic tests. (shrink)