Analytical robustness of nine common assays: Frequency of outliers and extreme differences identified by a large number of duplicate measurements

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Abstract

Introduction: Duplicate measurements can be used to describe the performance and analytical robustness of assays and to identify outliers. We performed about 235,000 duplicate measurements of nine routinely measured quantities and evaluated the observed differences between the replicates to develop new markers for analytical performance and robustness. Materials and methods: Catalytic activity concentrations of aspartate aminotransferase (AST), alanine aminotransferase (ALT), and concentrations of calcium, cholesterol, creatinine, C-reactive protein (CRP), lactate, triglycerides and thyroid-stimulating hormone (TSH) in 237,261 patient plasma samples were measured in replicates using routine methods. The performance of duplicate measurements was evaluated in scatterplots with a variable and symmetrical zone of acceptance (A-zone) around the equal line. Two quality markers were established: 1) AZ95: the width of an A-zone at which 95 % of all duplicate measurements were within this zone; and 2) OPM (outliers per mille): the relative number of outliers if an Azone width of 5 % was applied. Results: The AZ95 ranges from 3.2% for calcium to 11.5% for CRP and the OPM from 5 (calcium) to 250 (creatinine). Calcium, TSH and cholesterol have an AZ95 of less than 5% and an OPM of less than 50. Conclusions: Duplicate measurements of a large number of patient samples identify even low frequencies of extreme differences and thereof defined outliers. We suggest two additional quality markers, AZ95 and OPM, to complement description of assay performance and robustness. This approach can aid the selection process of measurement procedures in view of clinical needs.

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APA

Neubig, S., Grotevendt, A., Kallner, A., Nauck, M., & Petersmann, A. (2017). Analytical robustness of nine common assays: Frequency of outliers and extreme differences identified by a large number of duplicate measurements. Biochemia Medica, 27(1), 192–198. https://doi.org/10.11613/BM.2017.021

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