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Analytical performance specifications (APS) represent the criteria that specify the quality required for laboratory test information to satisfy clinical needs. In 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) considered timely to update the topic of APS by organizing a conference in Milan in which some strategic concepts were proposed. Here I summarize the essential points representing the EFLM Strategic Conference heritage and discuss the approaches that will permit us to become more concrete, including roles and main actions expected from each of involved stakeholders for contributing a quantum leap forward in the way of practicality of Milan consensus about APS. [ABSTRACT FROM AUTHOR]

In addition to the correct implementation of calibration traceability, the definition and fulfillment of maximum allowable measurement uncertainty (MAU) are essential in assuring that laboratory measurements are clinically usable. Across the entire calibration hierarchy, three major contributors to the measurement uncertainty (MU) budget are identified, starting with the higher-order reference providers, extending through the in vitro diagnostic (IVD) manufacturers and their processes for assigning calibrator values, and ending with medical laboratories generating the random variability of results reported to clinicians. To understand if it is possible to achieve MAU and, consequently, to fix the possible drawbacks, the definition of combined MU budget limits across the entire calibration hierarchy has a central role. In particular, quality specifications for MU of reference and commercial calibrator materials should be defined according to the MAU on clinical samples. All involved stakeholders (i.e., higher-order reference providers, IVD manufacturers, medical laboratories) should be prepared to improve their performance whenever the clinical application of the test is made questionable by the failure to achieve MAU. [ABSTRACT FROM AUTHOR]

To be accurate and equivalent among assays, laboratory results should be traceable to higher-order references and their quality should fulfill maximum allowable measurement uncertainty (MU) as defined to fit the intended clinical use. Accordingly, laboratory professionals should estimate and validate MU of performed tests using appropriate analytical performance specifications (APS). Current consensus supports the derivation of APS by using one of the three models established by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Strategic Conference held in Milan in 2014. It is recognized that some models are better suited for certain measurands than for others and the attention should be primarily directed towards their biological and clinical characteristics. Among others, model 3 should reflect the state of the art of the measurements that can be defined as the best analytical performance that is technically achievable. Taking serum C-reactive protein and ferritin as examples, here we describe the theoretical premises and the experimental protocol to be used to derive APS for MU when a measurand is allocated to this model. Although the model lacks a direct relationship with clinical outcomes, useful information about the in vitro diagnostic medical device performance and the average quality of provided results may be obtained. [ABSTRACT FROM AUTHOR]

* Context.--A relevant portion of coronavirus disease 2019 (COVID-19) patients develop severe disease with negative outcomes. Several biomarkers have been proposed to predict COVID-19 severity, but no definite interpretative criteria have been established to date for stratifying risk. Objective.--To evaluate 6 serum biomarkers (C-reactive protein, lactate dehydrogenase, D-dimer, albumin, ferritin, and cardiac troponin T) for predicting COVID-19 severity and to define related cutoffs able to aid clinicians in risk stratification of hospitalized patients. Design.--A retrospective study of 427 COVID-19 patients was performed. Patients were divided into groups based on their clinical outcome: nonsurvivors versus survivors and patients admitted to an intensive care unit versus others. Receiver operating characteristic curves and likelihood ratios were employed to define predictive cutoffs for evaluated markers. Results.--Marker concentrations at peak were significantly different between groups for both selected outcomes. At univariate logistic regression analysis, all parameters were significantly associated with higher odds of death and intensive care. At the multivariate analysis, high concentrations of lactate dehydrogenase and low concentrations of albumin in serum remained significantly associated with higher odds of death, whereas only low lactate dehydrogenase activities remained associated with lower odds of intensive care admission. The best cutoffs for death prediction were greater than 731 U/L for lactate dehydrogenase and 18 g/L or lower for albumin, whereas a lactate dehydrogenase activity lower than 425 U/L was associated with a negative likelihood ratio of 0.10 for intensive treatment. Conclusions.--Our study identifies which biochemistry tests represent major predictors of COVID-19 severity and defines the best cutoffs for their use. doi: 10.5858/arpa.2020-0389-SA, At the end of 2019, an outbreak of atypical pneumonia of unknown cause was detected in Wuhan, the capital of the province of Hubei, China. (1) The etiologic agent of [...]

According to ISO 15189:2022, analytical performance specifications (APS) should relate to intended clinical use and impact on patient care. Therefore, we aimed to develop a web application for laboratory professionals to calculate APS based on a simulation of the impact of measurement uncertainty (MU) on the outcome using the chosen decision limits, agreement thresholds, and data of the population of interest. We developed the "APS Calculator" allowing users to upload and select data of concern, specify decision limits and agreement thresholds, and conduct simulations to determine APS for MU. The simulation involved categorizing original measurand concentrations, generating measured (simulated) results by introducing different degrees of MU, and recategorizing measured concentrations based on clinical decision limits and acceptable clinical misclassification rates. The agreements between original and simulated result categories were assessed, and values that met or exceeded user-specified agreement thresholds that set goals for the between-category agreement were considered acceptable. The application generates contour plots of agreement rates and corresponding MU values. We tested the application using National Health and Nutrition Examination Survey data, with decision limits from relevant guidelines. We determined APS for MU of six measurands (blood total hemoglobin, plasma fasting glucose, serum total and high-density lipoprotein cholesterol, triglycerides, and total folate) to demonstrate the potential of the application to generate APS. The developed data-driven web application offers a flexible tool for laboratory professionals to calculate APS for MU using their chosen decision limits and agreement thresholds, and the data of the population of interest. [ABSTRACT FROM AUTHOR]

Alanine aminotransferase (ALT) represents the first-level test to detect individuals with hepatocellular damage of any etiology. However, it has been highlighted that the lack of assay harmonization may lead to overdiagnosis and unnecessary further testing if guideline-recommended fixed cut-offs are uncritically employed. To solve the issue of ALT (dis)harmonization and improve the interpretation of its values, a series of urgent actions for documenting and validating metrological traceability of serum ALT measurements, as described in this paper, are no longer postponeable. It is time that all medical laboratory stakeholders (in vitro diagnostic manufacturers, laboratorians, external quality assessment scheme organizers) actively co-operate to implement the ALT standardization in a concerted action following well-established theoretical assumptions and applying experimental approaches described in literature. [ABSTRACT FROM AUTHOR]

Recently, Abbott Diagnostics marketed a new generation of Alinity enzyme assays, introducing a multiparametric calibrator [Consolidated Chemistry Calibrator (ConCC)] in place of or in addition to factor-based calibrations. For alkaline phosphatase (ALP), both calibration options are offered, i.e., with ConCC (ALP2) and with an experimental calibration factor (ALP2F). Both options are declared traceable to the 2011 IFCC reference measurement procedure (RMP). Before to replace the old generation (ALP1) with the new one, we decided to validate the trueness of ALP2/ALP2F. Three approaches were employed: (a) preliminary comparison on 48 native frozen serum samples with ALP1, of which traceability to RMP was previously successfully verified; (b) examination of three banked serum pools (BSP) with values assigned by RMP; (c) direct comparison with RMP on a set of 24 fresh serum samples. Bias estimation and regression studies were performed, and the standard measurement uncertainty associated with ALP measurements on clinical samples (uresult) was estimated and compared with established analytical performance specifications (APS). ConCC commutability was also assessed. A positive proportional bias was found with both ALP2 and ALP2F when compared to ALP1 and RMP. This positive bias was confirmed on BSP: in average, +13.1 % for ALP2 and +10.0 % for ALP2F, respectively. uresult were 13.28 % for ALP2 and 10.04 % for ALP2F, both not fulfilling the minimum APS of 4.0 %. Furthermore, ConCC was not commutable with clinical samples. Our results unearth problems in the correct implementation of traceability of Alinity ALP2/ALP2F, with the risk for the new assay to be unfit for clinical purposes. [ABSTRACT FROM AUTHOR]

This document discusses the measurement uncertainty (MU) of serum ferritin, a key performance indicator for laboratory measurements. The authors collected data from four commercial measuring systems and calculated the standard MU associated with clinical samples. The results showed that the Architect i2000 had the best performance in terms of MU on clinical samples. However, without an objectively defined analytical performance specification (APS), it is difficult to determine the suitability of this figure. The authors suggest using the 'state of the art-based' (SoA) APS model to temporarily define APS for MU. The data from this study can help provide information for defining APS for clinical sample measurements. The authors conclude that the practical application of the traceability concept and the procedural implementation of calibration traceability are often poorly managed, and comparative information like this study should be used to improve the analytical quality of measuring systems. [Extracted from the article]