Quality management in clinical application of mass spectrometry measurement systems.

Clin Biochem

Risch Laboratory Group, Schaan, Principality of Liechtenstein.

Published: September 2016

Thanks to highly specific analyte detection and potentially complete compensation for matrix variables based on the principle of stable isotope derivative internal standardisation, mass spectrometry methods allow the development of diagnostic tests of outstanding analytical quality. However, these features per se do not guarantee reliability of tests. A wide range of factors can introduce analytical errors and inaccuracy due to the extreme complexity of the methods involved. Furthermore, it can be expected that the application patterns of MS methods in diagnostic laboratories will change substantially during the coming years - with presumably less specialised laboratories implementing mass spectrometry. Introduction of highly automated test solutions by manufacturers will require some trade-off between operation convenience, sample throughput and analytical performance. Structured and careful quality and risk management is therefore crucial to translate the analytical power of mass spectrometry into actionable and reliable results for individual patients' care and to maintain the degree of reliability that is expected from MS methods in clinical pathology. This reflection review discusses whether particular quality assurance tools have to be applied for MS-based diagnostic tests and whether these tools are different from those applied for optical- and affinity-based standard tests. Both pre-implementation strategies and surveillance of assays with assessment of metadata in routine testing are addressed. The release of the CLSI guideline C62-A in 2014 was a substantial achievement in this context because it addresses a wide spectrum of relevant issues in quality assurance of mass spectrometry-based clinical tests. However, the translation of this best practice document into individual laboratory settings is likely to be heterogeneous.

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http://dx.doi.org/10.1016/j.clinbiochem.2016.07.005DOI Listing

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