Medicine Between The Lines

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In what follows, we develop this point by looking closely at how dysfunction is conceptualized in the accounts of Boorse and Wakefield. That is, the function of a cell, organ, or system is its species-typical contribution to a biological goal. Thus, a normally functioning heart in a year-old woman pumps blood at or above the average efficiency for her reference class i.

Dysfunction, then, occurs when functional efficiency falls some distance below the population mean Boorse, , Boorse addresses the line-drawing problem by appealing to the statistical frequency of a dysfunction, stipulating that abnormal function is that falling more than a certain distance below the population mean. He goes on to say:.

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The precise line between health and disease is usually academic, since most diseases involve functional deficits that are unusual by any reasonable standard. Boorse, , Boorse thus recognizes that biological functions have continuous distributions and that pathological states can have vague boundaries. But despite these observations, he claims that in most, or almost all, cases there will be an obvious level of dysfunction that marks out disease from health Boorse, , It is, however, unclear as to what feature some level of dysfunction should have that makes it pathological rather than normal, especially if a statistical definition of abnormality is recognized to be arbitrary.

In contrast, we think that many more cases pose this problem than are typically assumed, as we seek to show in section three. Even paradigmatically all-or-nothing diseases like cancer or infections may sometimes have a vague boundary with health. Schwartz , — argues that statistical frequency cannot be used to solve the line-drawing problem, as disease might be quite common in a population, or it might be very rare or absent in a population.

Where disease is common, this approach to drawing the line will imply that those we would intuitively recognize as diseased actually are not; where it is rare, the approach would imply that people we would normally think of as healthy are diseased. The frequency approach has implications that do not match our usual uses of these terms.

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If statistical frequency is determinative in the way Boorse seems to suggest, then whether or not I have a disease depends on facts about other people, rather than just on facts about my own condition. The appeal to natural selection seems to provide little guidance regarding the level of functionality at which we should say that a bodily system, organ, tissue, or cell is no longer performing in the way for which it was selected. Schwartz argues that appealing to natural selection cannot help us determine a level of function to be considered healthy because what is selected for or against depends, not just on how well a particular organ functions, but also on other variations existing in the population, and how these compare Schwartz, , — However, because the HDA also has a value criterion, Wakefield does not require the notion of dysfunction to bear the whole weight of defining disease.

Thus, both the BST and the HDA seem to require a way to determine decisively when dysfunction occurs, in order to demarcate between health and disease. This will be determined statistically for Boorse, or via appeal to natural selection for Wakefield. Nevertheless, there are problems with drawing this line by appeal either to statistics or natural selection.

Schwartz thus acknowledges that his solution is also subject to problems concerning line-drawing, suggesting this may be insoluble. More importantly for our purposes, he does not attribute the line-drawing problem to the attempt to base a categorical definition on a continuous variable or consider it to threaten the binary characterization of health and disease.

All of these authors, Boorse, Wakefield, and Schwartz, hold that disease is either present or absent, denoted by the presence or absence of dysfunction with or without additional criteria. Although there is some admission that it is challenging to identify the level of dysfunction that marks the boundary of disease, this issue is largely disregarded on the assumption that, by and large, dysfunction can be readily identified in contrast to adequate or healthy functioning in the majority of cases. Yet, views about the categorical nature of disease rely on the robustness of this assumption.

In the next section, we examine dysfunction across three disease types to establish that, in a range of conditions, function and dysfunction occur on a spectrum. Insofar as the line-drawing problem has been discussed, this has largely been with regard to disorders that are defined in terms of explicit thresholds on continuous biological variables Schwartz, , The boundaries defining these conditions have shifted over time, generally to create more inclusive disease categories Moynihan et al.

The changing nature of these thresholds suggests that there is no incontrovertible point at which function switches to dysfunction. There is often continuity, with severe disease at higher levels of the relevant variable indicated by increasing mortality and morbidity at, e. For each condition, the threshold could plausibly be higher or lower by at least one increment of the relevant measure without greatly altering the nature of the disease e.

The increments that separate having a disease and not having it are so small that the exact position of the line demarcating disease from non-disease—the diagnostic threshold—seems arbitrary. These conditions appear to be matters of degree, tracking the trajectory from function to dysfunction; from health to disease.

The lack of a clear boundary is also indicated by the way that these conditions morph seamlessly into risk factors pre-hypertension, pre-diabetes, overweight, etc. Thus, it seems implausible to claim that the presence of dysfunction can distinguish between health and disease regarding these disorders defined in terms of continuous variables and their associated risks. The preceding conditions might be considered fairly obvious examples in terms of criticizing dysfunction-requiring accounts, because they are diseases that are defined in relation to variables occurring on a standard distribution curve.

This feature immediately raises the question as to where to draw the line between healthy and pathological, given the lack of disjunctions. The lack of a clear demarcation is reflected in the actions of the expert committees that determine the boundaries of these diseases, as they explicitly take account of practical considerations rather than claiming to identify the point where pathology starts. This may be a purely pragmatic approach, but it seems to support the view that there is no clear boundary to find.

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The identification of cancer used to be relatively straightforward. Prior to the advent of screening programs, most cancers were diagnosed because patients noticed something wrong. People presented with symptoms related to the abnormal growth of cells or tissues, such as a hard lump in a breast, back pain from multiple myeloma, or headaches and blurred vision from a brain tumor.

Lesions were often clinically visible or palpable, or detectable with relatively unsophisticated tests. The categorical nature of disease was seemingly evident in these cases: patients either had, or did not have, cancer. There were fewer grey areas, because any abnormal cell growth had declared itself malignant by the time the patient noticed something wrong and offered him or herself for diagnosis. However, changes in our understanding of cancer, and in our technologies for identifying changes in cell growth and predispositions to such changes, have seriously undermined the diagnosis of cancer.

The abnormality of function evident with invasive cancerous growth and distant spread is no longer so distinct with the early identification of atypical or dysplastic growth. Now, it can be challenging to declare any particular cell or cells abnormal or malignant, because there are many stages in between where function starts to go awry in almost imperceptible ways.

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The classification of neoplasms or tumors is complex. Initial classifications were topological. Tumors were largely defined in relation to their anatomical location: breast, prostate, lung, and so forth Muir and Percy, This was rapidly supplemented with morphologic or histologic criteria relating to the appearance and architecture of cells within the tumor, and criteria relating to behavior. Tumors with characteristic architecture and malignant i. Cancer cells grow in a disorderly, chaotic manner, unresponsive to local requirements or regulation, leading to invasion of local tissues and spread to other parts of the body known as metastases.

This tripartite classification topology, morphology, behavior was disrupted by the advent of genetics, with the first cancer-specific genetic abnormality reported in Brandal, Teixeira, and Heim, Currently, it is thought that genetic aberrations are the central pathogenic event in neoplastic transformation the somatic mutation theory of cancer.

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Various genetic alterations in cell physiology have been identified that collectively produce cancerous cells characterized by a lack of the usual growth-regulatory mechanisms Soto and Sonnenschein, Cancer develops and progresses by gradually acquiring new mutations and other changes that allow cancer cells to expand and migrate Greaves and Maley, The main point is that as our understanding of cancer becomes more sophisticated, it becomes increasingly difficult to pinpoint the relevant dysfunction, and hence determine where any line should be drawn between the presence or absence of cancer.

This may or may not provide us with a categorical definition, depending on how possible it is to establish local invasion and metastatic spread. On the other hand, if we rely on genetic markers to identify dysfunction at the level of the deregulated cell growth pathways, we may not track cancer, as not all cells with the relevant genetic markers will proceed to malignant growth. Whether we take a morphologic or genetic approach to defining cancer, it seems that cancerous growth occurs on a spectrum of deregulation. There may be cells with genetic markers but no subsequent abnormalities in growth, abnormal but nonmalignant cell growth, malignant-looking tumors that do not metastasize, all the way through to cancer with distant metastases.

For at least some neoplasms e. Like the chronic diseases discussed earlier, it is difficult to find a demarcation between normal function and dysfunction. At one end of the scale, cancers are unmistakably present, but at the other there are atypical cells that may or may not proceed on a malignant trajectory. Additionally, we cannot pinpoint any one mutation among the many acquired by the clonal cells that necessarily determines a malignant trajectory, and hence the presence of cancer.

A Boorsian might respond by claiming that the disease cancer begins at a particular point, for example, with the very first abnormal cell growth, that is, mild dysplasia. Interestingly, this claim seems arbitrary in that whatever dysfunction occurs at a histological level is a reflection of sub-cellular dysfunction, where genetically-programmed cellular processes go awry.

Searching for the dysfunction that marks health from disease in the case of cancer triggers an infinite regress down to molecular variations, none of which might be the sole cancer-causing dysfunction. It seems there may be no specific dysfunction that picks out cancer. Not all genetic mutations lead to abnormal cell growth; not all cases of atypia progress to dysplasia, and so forth.

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Any dysfunction that we take to be pathognomic of cancer is going to be arbitrary, because some other part- or process-dysfunction could equally well be selected. Our third example involves diseases caused by infectious agents. The presence of diseases like the measles, small pox, syphilis, meningitis, septicaemia, and so forth seems incontrovertible.

There are typical signs and symptoms; there may be positive identification of the relevant organism, rises in relevant immune titers may provide serologic evidence, responses to treatment may be characteristic, and so forth.