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Patient-specific devices and population-level evidence: evaluating therapeutic interventions with inherent variation

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Abstract

Designing and manufacturing medical devices for specific patients is becoming increasingly feasible with developments in 3D printing and 3D imaging software. This raises the question of how patient-specific devices can be evaluated, since our ‘gold standard’ method for evaluation, the randomised controlled trial (RCT), requires that an intervention is standardised across a number of individuals in an experimental group. I distinguish several senses of patient-specific device, and focus the discussion on understanding the problem of variations between instances of an intervention for RCT evaluation. I argue that, despite initial appearances, it is theoretically possible to use RCTs to evaluate some patient-specific medical devices. However, the argument reveals significant difficulties for ensuring the validity of such trials, with implications for how we should think about methods of evidence gathering and regulatory approaches for these technologies.

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Notes

  1. Patient-specific medical devices can be considered part of recent trends toward ‘personalised medicine’, which seeks to provide treatments targeted for specific patients. ‘Personalised medicine’ most often refers to methods for identifying which pharmacological treatments are likely to work for specific patients by developing drug efficacy data for sub-populations, and methods for identifying which sub-populations specific patients belong to (e.g., genetic tests), such that it relies upon stratified population-level evidence. The personalisation discussed here is somewhat different, referring rather to adapting treatments (surgical or pharmaceutical) to suit the needs of particular patients, or designing treatments for particular patients from scratch (which is not generally feasible for pharmaceutical treatments, but would include bespoke surgeries and prosthetics).

  2. Regulatory systems currently allow patient-specific devices to bypass regulatory controls under some conditions (see, e.g., FDA 2014; TGA n.d.). These exemptions typically limit their use to small numbers of people (e.g., less than 5 units per year for the FDA), and more regulatory controls will be appropriate if use is to be scaled up.

  3. Greater use of custom manufacture may also require changes to other kinds of regulatory control, such as different approaches to quality assurance in manufacturing, although I shall not discuss this issue.

  4. Variation in interventions is of course not limited to patient-specific devices, so this argument has relevance for discussions of the use of RCTs in other areas where standardisation is difficult or problematic, such as surgery and complex interventions.

  5. I do not consider diagnostic devices.

  6. This term and the distinction with custom-made devices are borrowed from Australia’s Therapeutic Goods Administration (TGA n.d.).

  7. The custom-made/bespoke distinction and terms are from Chadwick (2014).

  8. There are also likely to be various practical barriers, e.g., less available funding [as in surgical trials (Garas et al. 2012)]. In order to focus on the theoretical tension between RCT evidence and custom-made devices, I leave these practical barriers aside.

  9. For further discussion of the barriers discussed in the following three paragraphs, as well as other barriers, see, e.g., Cook (2009), Garas et al. (2012), Lassen et al. (2012), Meshikhes (2015), Stirrat (2004). Some intersections between my argument and literature on complex interventions is noted below.

  10. For more detail, and discussion of other differences, see Schwartz and Lellouch (1967); Thorpe et al. (2009); Hey (2015); Nieuwenhuis (2016).

  11. Another way of seeing this is to consider that explanatory trials seek to ensure that the contextual factors surrounding an intervention are the same in the experimental and control groups, and this is possible for RCTs of custom-made devices as long as the variations between these devices are considered part of the intervention, rather than part of the context of the intervention (Schwartz and Lellouch 1967, p. 638). How interventions are defined is discussed further in the section “Variation within the definition of ‘the same’ intervention”.

  12. An example is pill-case colour, which has been shown to sometimes influence outcomes in pharmaceutical trials (de Craen et al. 1996). Variations of pill-case colour within a trial might seem innocuous, but could influence results.

  13. This is a controversial claim amongst philosophers concerned with the nature of causation, but I shall not seek to deal with this here. Cartwright’s analysis can be regarded as useful in understanding the significance of inherent variation even if we resist its metaphysical commitments.

  14. Though further research is needed, current research suggests that for patients with over-expressed PDGFRB or mutated NRAS, vemurafenib’s causal capacity (which is thought to involve blocking how the cancer grows and maintains itself) is triggered, but this effect is negated by other mechanisms (as over-expressed PDGRFB or mutated NRAS mean the cancer has other routes by which to grow and maintains itself). In the case of patients whose stromal cells secrete hepatocyte growth factor, it would appear that vemurafenib’s capacity to block cancer growth and maintenance is itself prevented from occurring (see Nazarian et al. 2010; Straussman et al. 2012; Wilson et al. 2012).

  15. This view would imply that in explanatory trials, no variations should be acceptable without strong reasons to think they are causally innocuous. In pragmatic trials, some variations would still be acceptable since this view is consistent with thinking that the causal contribution of a varied intervention could remain similar across its various instances, albeit not the same. The causal capacity of, for instance, taking the same drug every day at the same time might be similar to that of taking the same drug most days at slightly different times. The point at which variations made internal validity so low that the trial results tell us nothing at all would, again, often be very difficult to assess.

  16. A similar view is found in the work of Schwartz and Lellouch (1967), as discussed below. Something like this view is also implicated in discussions of intervention ‘fidelity’ or ‘integrity’, that is, the extent to which an intervention is carried our according to a defined protocol, primarily discussed in relation to complex interventions. Though discussions of fidelity are partly concerned with how to ensure a treatment known to be effective is implemented as planned, some of this literature recognises that resolving issues related to variation will involve identifying a clear definition of an intervention, and identifying what aspects of an intervention are causally implicated in the desired outcomes (see, e.g., Gearing et al. 2011, p. 82; Medical Research Council 2008; Moncher and Prinz 1991, p. 250). However, exactly why variations are tied to these matters is not made explicit in this literature.

  17. Hawe et al. (2004) offer a view of complex interventions which is consistent with this account. As they put it, “[r]ather than defining the components of the intervention as standard—for example, the information kit, the counselling intervention, the workshops—what should be defined as standard are the steps in the change process that the elements are purporting to facilitate or the key functions that they are meant to have” (2004, p. 1562). What Hawe and colleagues refer to as the ‘change process’ or ‘function’ of the intervention, I take it, maps onto what I have called the causal contribution of the intervention, though these authors do not elaborate on the conceptual basis for their view.

  18. Thank you to an anonymous reviewer for pointing this out.

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Acknowledgements

My thanks to Robert Sparrow, Wendy Rogers, David Wotton, Tajanka Mladenovska, and the anonymous referees for this journal, for their comments on previous drafts. The funding was provided by Australian Research Council (Grant No. CE140100012)

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Correspondence to Mary Jean Walker.

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Walker, M.J. Patient-specific devices and population-level evidence: evaluating therapeutic interventions with inherent variation. Med Health Care and Philos 21, 335–345 (2018). https://doi.org/10.1007/s11019-017-9807-9

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