Abstract
Definition and fullfillment of analytical performance specifications (APS) for measurement uncertainty (MU) allow to make laboratory determinations clinically usable. The 2014 Milan Strategic Conference have proposed models to objectively derive APS based on: (a)the effect of analytical performance on clinical outcome; (b)biological variation components; and (3) the state of the art of the measurement, defined as the highest level of analytical performance technically achievable. Using these models appropriately, we present here a proposal for defining APS for standard MU for some common biochemical measurands. We allocated a group of 13 measurands selected among the most commonly laboratory requested tests to each of the three Milan models on the basis of their biological and clinical characteristics. Both minimum and desirable levels of quality of APS for standard MU of clinical samples were defined by using information obtained from available studies. Blood total hemoglobin, plasma glucose, blood glycated hemoglobin, and serum 25-hydroxyvitamin D3 were allocated to the model 1 and the corresponding desirable APS were 2.80, 2.00, 3.00, and 10.0%, respectively. Plasma potassium, sodium, chloride, total calcium, alanine aminotransferase, creatinine, urea, and total bilirubin were allocated to the model 2 and the corresponding desirable APS were 1.96, 0.27, 0.49, 0.91, 4.65, 2.20, 7.05, and 10.5%, respectively. For C-reactive protein, allocated to the model 3, a desirable MU of 3.76% was defined. APS for MU of clinical samples derived in this study are essential to objectively evaluate the reliability of results provided by medical laboratories.
Highlights
The main scope of laboratory medicine is to provide useful information for correct clinical decision-making in order to significantly contribute to the quality of health care [1]
To make laboratory determinations clinically usable and to ensure that the measurement variability does not gain the upper hand obscuring the clinical information supplied by the test results, it is essential to estimate the measurement uncertainty (MU) of results produced by procedures intended to measure biological measurands, and to verify that the estimated MU is within objectively defined analytical performance specifications (APS) [2]
APS for MU of clinical samples were defined as follows: (a) for measurands belonging to the model 1, we searched peer-reviewed literature for outcome studies dealing with the main clinical use of the measurand and evaluating the impact of random analytical variability on clinical outcomes; (b) for measurands belonging to the model 2, we retrieved from the EFLM biological variation (BV) database [18] the publications rated as ‘A’, indicating full compliance to the 14 BV data critical appraisal checklist quality items (BIVAC-QI) [19]
Summary
The main scope of laboratory medicine is to provide useful information for correct clinical decision-making in order to significantly contribute to the quality of health care [1]. MU at the level of clinical samples should be the combination of all uncertainty contributions accumulated across the entire traceability chain, starting with MU of reference materials, extending through the in vitro diagnostic (IVD) manufacturers and their process for assignment of calibrator values and MU, and ending with the random variability of measuring systems. Very important to the scope of the present paper, the ISO Technical Specification 20914 dealing with the MU estimation emphasizes that the magnitude of MU should be suitable for a result to be used in a medical decision [3].
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