Avtor/Urednik		Martinello, Flávia; Snoj, Nada; Skitek, Milan; Jerin, Aleš
Naslov		The top-down approach to measurement uncertainty: which formula should we use in laboratory medicine?
Tip		članek
Vol. in št.		Letnik 30, št. 2
Leto izdaje		2020
Obseg		str. [1-9 str.]
ISSN		1846-7482 - Biochemia medica : casopis Hrvatskoga drustva medicinskih biokemicara / HDMB
Jezik		eng
Abstrakt		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.
Deskriptorji		Laboratorijska medicina
Proste vsebinske oznake		measurement uncertainty bias uncertainty total error quality control