Diagnostic layering: Patient accounts of breast cancer classification in the molecular era

Abstract

Social scientific work has considered the promise of genomic medicine to transform healthcare by personalising treatment. However, little qualitative research attends to already well-established molecular techniques in routine care. In this article we consider women's experiences of routine breast cancer diagnosis in the UK NHS. We attend to patient accounts of the techniques used to subtype breast cancer and guide individual treatment. We introduce the concept of ‘diagnostic layering’ to make sense of how the range of clinical techniques used to classify breast cancer shape patient experiences of diagnosis. The process of diagnostic layering, whereby various levels of diagnostic information are received by patients over time, can render diagnosis as incomplete and subject to change. In the example of early breast cancer, progressive layers of diagnostic information are closely tied to chemotherapy recommendations. In recent years a genomic test, gene expression profiling, has become introduced into routine care. Because gene expression profiling could indicate a treatment recommendation where standard tools had failed, the technique could represent a ‘final layer’ of diagnosis for some patients. However, the test could also invalidate previous understandings of the cancer, require additional interpretation and further prolong the diagnostic process. This research contributes to the sociology of diagnosis by outlining how practices of cancer subtyping shape patient experiences of breast cancer. We add to social scientific work attending to the complexities of molecular and genomic techniques by considering the blurring of diagnostic and therapeutic activities from a patient perspective.

Unsettling the treatment imperative? Chemotherapy decision‐making in the wake of genomic techniques

“…I said, right, I'll pay for this test if necessary, to make me make the right decision.Here, Alice links the specificity of gene expression profiling to certainty. For many patients (though not all), Oncotype DX was portrayed as a final ‘layer’ of diagnostic information because it resolved ambiguities generated by established tools (Ross et al., 2021). Felicity had faced particular treatment uncertainty, having undergone hormone therapy to reduce the size of the tumour prior to surgery.…”

“…This analytical work complemented and extended our existing work on gene expression profiling. Other publications have focussed on experiences of the technique as shared and discussed in online interactions (Ross et al., 2019), patient experiences of breast cancer diagnosis (Ross et al., 2021) and representations of gene expression profiling in policy and practice (Kerr et al., 2021).…”

Detecting value(s): Digital biomarkers for Alzheimer’s disease and the valuation of new diagnostic technologies

“…Most significantly, 'naming the disease' can no longer (if it ever was) be considered synonimous with certainty and closure, as the temporal and spatial fracturing of diagnosis around practices of medical surveillance makes it increasingly open to constant renegotiation and uncertainty (cf. Ross et al, 2021).…”

Regulating diagnosis—Molecular and regulatory sub‐stratifications of lung cancer treatment

“…The analysis (a) unfolds the uncertainties related to the delineation of diagnostic categories that are based on the PD-L1 biomarker and demonstrates how this uncertainty can be utilised in regulatory settings to delineate diagnostic categories and protect national health budgets and (b) discusses the implications of diagnostic authority being pushed from the clinic 'up' into the regulatory system, where recommendations about access to treatment are made and 'out' into the pathology laboratory, where patients are categorised on the basis of molecular tests. Drawing on work on the uncertainties of precision medicine (Green et al, 2022;Kerr et al, 2019;Kuiper et al, 2022;Timmermans and Tietbohl, 2016), the paper's contribution to the sociology of diagnosis (Jutel, 2009(Jutel, , 2011Ross et al, 2021) is an empirical exploration of the ways in which commercial, national economic and clinical interests intersect as precision medicine passes through national health technology assessment agencies and into standard care in the clinic. Thereby, the study sheds empirical light on issues raised by existing studies on precision medicine in a regulatory context, such as Cambrosio et al (2021), Green et al (2022) and Wadmann and Hauge (2021), illuminating the entanglements between molecular, diagnostic categorisation and resource allocation.…”