Introduction: By quantifying the measurement uncertainty (MU), both the laboratory and the physician can have an objective estimate of the results' quality. There is significant flexibility on how to determine the MU in laboratory medicine and different approaches have been proposed by Nordtest, Eurolab and Cofrac to obtain the data and apply them in formulas. The purpose of this study is to compare three different top-down approaches for the estimation of the MU and to suggest which of these approaches could be the most suitable choice for routine use in clinical laboratories.
Materials And Methods: Imprecision and bias of the methods were considered as components of the MU. The bias was obtained from certified reference calibrators (CRC), proficiency tests (PT), and inter-laboratory internal quality control scheme (IQCS) programs. The bias uncertainty, the combined and the expanded uncertainty were estimated using the Nordtest, Eurolab and Cofrac approaches.
Results: Using different approaches, the expanded uncertainty estimates ranged from 18.9-40.4%, 18.2-22.8%, 9.3-20.9%, and 7.1-18.6% for cancer antigen (CA) 19-9, testosterone, alkaline phosphatase (ALP), and creatinine, respectively. Permissible values for MU and total error ranged from 16.0-46.1%, 13.1-21.6%, 10.7-26.2%, and 7.5-17.3%, respectively.
Conclusion: The bias was highest using PT, followed by CRC and IQCS data, which were similar. The Cofrac approach showed the highest uncertainties, followed by Eurolab and Nordtest. However, the Eurolab approach requires additional measurements to obtain uncertainty data. In summary, the Nordtest approach using IQCS data was therefore found to be the most practical formula.
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http://dx.doi.org/10.11613/BM.2020.020101 | DOI Listing |
A second edition of the Eurachem guide, Measurement uncertainty arising from sampling (UfS),1 has recently been published (Fig. 1), in collaboration with CITAC, Eurolab, Nordtest and the Royal Society of Chemistry's Analytical Methods Committee. This Technical Brief aims to explain how this new second edition differs significantly from the first edition that was published in 2007.
View Article and Find Full Text PDFBiochem Med (Zagreb)
June 2020
Institute of Clinical Chemistry and Biochemistry, University Medical Centre Ljubljana, Ljubljana, Slovenia.
Introduction: By quantifying the measurement uncertainty (MU), both the laboratory and the physician can have an objective estimate of the results' quality. There is significant flexibility on how to determine the MU in laboratory medicine and different approaches have been proposed by Nordtest, Eurolab and Cofrac to obtain the data and apply them in formulas. The purpose of this study is to compare three different top-down approaches for the estimation of the MU and to suggest which of these approaches could be the most suitable choice for routine use in clinical laboratories.
View Article and Find Full Text PDFJ Agric Food Chem
July 2011
Universidad de Almeria, 04120 Almeria, Spain.
Practical "top-down" approaches appear to be the most suitable for the evaluation of measurement uncertainty in pesticide residue testing laboratories, where analytical procedures are routinely applied to a large number of pesticide/food combinations. The opposite approach, "bottom-up" evaluation of measurement uncertainty, leads to great difficulties in evaluating all of the pesticides in a consistent way. Among the top-down approaches, there are two main ways in which measurement uncertainty can be estimated: One is based on default values, which are based on previous extensive interlaboratory experience and the proven accuracy of the laboratory; these include the Horwitz equation or the fit-for-purpose relative standard deviation (FFP-RSD).
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