Thank you Jonathan!
I appreciate your considerable work in this area. These are old, but nonetheless valid arguments. My post was ostensibly to gain examples of analytical interference, though I was more interested in gauging the current opinion on assay performance. I have received a number of replies to my posting, and this topic indeed polarises opinion.
Before I continue, I would like to clarify that I sit firmly in the ‘purist’ camp. However, in reality, it will be a long time before the day comes when the extensive (and growing) repertoire of biochemical measurement procedures available in diagnostic laboratories are ALL appropriately standardised and traceable to commutable matrix reference materials, and moreover, are completely impervious to analytical interferents. Until such time, biochemists must be cognisant of the various interferences that may be encountered in day-to-day practice. Critically, any clues that may be gleaned from these interferences that allude to the underlying pathology and/or inform subsequent investigations, to my mind, may be considered (though contentiously) perhaps not a ‘beneficial interference’, but in the right hands, a ‘utilisable’ interference (a question of semantics really).
There are a number of examples where analytical interference could be considered as aiding clinical investigations; 1) interference in Jaffe method due to ketoacidosis, 2) cross-reactivity of other adrenal/ovarian steroids in testosterone immunoassay in the setting of adrenal carcinoma, 3) unmasking of paraproteinaemia due to interference in various assays, including interference in LIH indices (see, Monk, C, et al, A monoclonal protein identified by an anomalous lipaemia index. Ann Clin Biochem, 2009;46:250-2), and 4) toward diagnosis of familial dysalbuminaemic hyperthyroxinaemia (FDH): “Assays that rely on the competition of a T4 analog with unbound T4 in the sample can give spuriously high results in FDH patients, because albumin binding of the T4 analog is enhanced by the FDH mutation” (Cartwright D, et al. Familial dysalbuminaemic hyperthyroxinaemia: a persistent diagnostic challenge. Clin Chem. 2009:55;1044-6). You could even consider the ‘dirtier’ immunoassay for urinary free cortisol as a more diagnostically sensitive measurement procedure (due to x-reactivity with structurally homologous steroid metabolites) in comparison to its more analytically specific LC-MS/MS counterpart.
The argument of utilisable interference is particularly applicable to scenarios where analytically specific measurement procedures for specific measurands are limited in their availability (e.g. may be confined to the research laboratory). One example is the assay for ACTH: “To ensure that patients with the ectopic ACTH syndrome are flagged up by an ACTH assay, it is important there is a high degree of cross-reactivity of the ACTH precursors in the ACTH assay or that a separate specific assay for ACTH precursors is available” (White, A & Gibson, S. ACTH precursors: biological significance and clinical relevance. Clin Endocrinol. 1998;48:251-5). Currently, to my knowledge there is only 1 research laboratory in the UK that measures plasma pro-opiomelanocortin.
Jonathan’s assertion that “traceability is lost if the measurement procedure responds to components which are not identical to the measurand”, very true, yet this statement alone renders the technique of immunoassay unfit for purpose from the purist’s perspective (even before we consider confounding anti-reagent antibodies). For an excellent review on immunoassay interference, see Sturgeon CM, and Viljoen A. Analytical error and interference in immunoassays: minimising risk. Ann Clin Biochem. 2011:48;418-32.
From an educational perspective, it is essential that clinical biochemists in the early stages of their careers (myself included) gain a thorough appreciation of assay interference in its varied and often insidious guises. If anyone is still reading this rebuttal, laboratory medicine should indeed be founded on good science, but much work remains to be done.
Phil.
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