Definition and application of performance specifications for measurement uncertainty of 23 common laboratory tests: linking theory to daily practice.

Laboratories should estimate and validate [using analytical performance specifications (APS)] the measurement uncertainty (MU) of performed tests. It is therefore essential to appropriately define APS for MU, but also to provide a perspective on suitability of the practical application of these APS. In this study, 23 commonly ordered measurands were allocated to the models defined during the 2014 EFLM Strategic Conference to derive APS for MU. Then, we checked if the performance of commercial measuring systems used in our laboratory may achieve them. Most measurands (serum alkaline phosphatase, aspartate aminotransferase, creatine kinase, γ-glutamyltransferase, lactate dehydrogenase, pancreatic amylase, total proteins, immunoglobulin G, A, M, magnesium, urate, and prostate-specific antigen, plasma homocysteine, and blood red and white cells) were allocated to the biological variation (BV) model and desirable APS were defined accordingly (2.65%, 4.75%, 7.25%, 4.45%, 2.60%, 3.15%, 1.30%, 2.20%, 2.50%, 2.95%, 1.44%, 4.16%, 3.40%, 3.52%, 1.55%, and 5.65%, respectively). Desirable APS for serum total cholesterol (3.00%) and urine albumin (9.00%) were derived using outcome-based model. Lacking outcome-based information, serum albumin, high-density lipoprotein cholesterol, triglycerides, and blood platelets were temporarily reallocated to BV model, the corresponding desirable APS being 1.25%, 2.84%, 9.90%, and 4.85%, respectively. A mix between the two previous models was employed for serum digoxin, with a 6.00% desirable APS. In daily practice by using our laboratory systems, 16 tests fulfilled desirable and five minimum APS, while two (serum albumin and plasma homocysteine) exceeded goals, needing improvements.

Harmonization Status of Serum Ferritin Measurements and Implications for Use as Marker of Iron-Related Disorders.

BACKGROUND: Serum ferritin is considered a suitable biomarker of iron-related disorders. However, data about the comparability of results among commercial measuring systems (MSs) are contradictory. We performed an intercomparison study aimed at verifying the current interassay variability and its impact on clinical application of the test. Obtaining this information is vital because manufacturers continue to claim calibration alignment to different WHO preparations, which are not related to each other in terms of traceability. METHODS: Four widely used MSs were evaluated. The interassay agreement was verified using 39 human serum pools. The recovery of WHO International Standard (IS) 94/572 (the only reference material available at the time of the study) was evaluated, after assessing the material commutability. Finally, an approach for harmonizing ferritin results was proposed. RESULTS: Highly significant differences (P < 0.00001) among ferritin concentrations assayed by different MSs were detected and the interassay CV (median 22.9%; interquartile range 21.8-25.5) overlapped the desirable intermethod bias (24.6%). IS 94/572 was commutable for use only with Access and Centaur, with Access being the only MS correctly recovering its assigned value. Accordingly, we used regression data against Access to recalibrate MSs, indirectly aligning them to IS 94/572, with a substantial improvement in degree of harmonization and traceability to higher-order reference. CONCLUSIONS: The harmonization among evaluated ferritin MSs is far from optimal, with the implementation of traceability to different WHO ISs being a factor of confusion. A recalibration approach, however, would permit measurement harmonization, allowing the use of common decision thresholds.

A step towards optimal efficiency of HbA1c measurement as a first-line laboratory test: the TOP-HOLE (Towards OPtimal glycoHemOgLobin tEsting) project.

OBJECTIVES: The TOP-HOLE (Towards OPtimal glycoHemOgLobin tEsting) project aimed to validate the HbA1c enzymatic method on the Abbott Alinity c platform and to implement the HbA1c testing process on the total laboratory automation (TLA) system of our institution. METHODS: Three different measuring systems were employed: Architect c4000 stand-alone (s-a), Alinity c s-a, and Alinity c TLA. Eight frozen whole blood samples, IFCC value-assigned, were used for checking trueness. A comparison study testing transferability of HbA1c results from Architect to Alinity was also performed. The alignment of Alinity TLA vs. s-a was verified and the measurement uncertainty (MU) estimated according to ISO 20914:2019. Turnaround time (TAT) and full time equivalent (FTE) were used as efficiency indicators. RESULTS: For HbA1c concentrations covering cut-offs adopted in clinical setting, the bias for both Architect and Alinity s-a was negligible. When compared with Architect, Alinity showed a mean positive bias of 0.54 mmol/mol, corresponding to a mean difference of 0.87%. A perfect alignment of Alinity TLA to the Alinity s-a was shown, and a MU of 1.58% was obtained, widely fulfilling the desirable 3.0% goal. After the full automation of HbA1c testing, 90% of results were released with a maximum TAT of 1 h, 0.30 FTE resource was also saved. CONCLUSIONS: The traceability of Alinity HbA1c enzymatic assay to the IFCC reference system was correctly implemented. We successfully completed the integration of the HbA1c testing on our TLA system, without worsening the optimal analytical performance. The shift of HbA1c testing from s-a mode to TLA significantly decreased TAT.

Pancreatic lipase: why laboratory community does not take enough care of this clinically important test?

Although being the recommended laboratory test to diagnose acute pancreatitis, serum pancreatic lipase (LIP) is among the poorly standardized laboratory tests, and laboratory stakeholders often appear to not take enough care of the quality of its measurements. Here we discuss some important issues that, if not correctly managed and solved, make misdiagnosis of acute pancreatitis by using serum LIP a real possibility. First, the current unavailability of a suitable higher-order reference material to be used as common calibrator should be filled up to definitively improve the inter-method bias. Second, knowledge of the analytical characteristics that may explain the defective performance of LIP assays should be deepened. IVD manufacturers should be more explicit in providing this information, including description of their internal protocol for transferring LIP values from internal references to commercial calibrators. Third, recommended models for accurately estimating measurement uncertainty and reliably defining analytical performance specifications for LIP measurements should be applied. Finally, investments considering alternative options for measuring LIP (e.g., targeted to the development of automated LIP immunoassays) should be warranted. All involved stakeholders (standardization bodies, higher-order reference providers, in vitro diagnostics manufacturers, and laboratory professionals) should contribute to fill the existing gap.

A Comprehensive Appraisal of Laboratory Biochemistry Tests as Major Predictors of COVID-19 Severity.

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.

The internal quality control in the traceability era.

To be accurate and equivalent, laboratory results should be traceable to higher-order references. Furthermore, their quality should fulfill acceptable measurement uncertainty (MU) as defined to fit the intended clinical use. With this aim, in vitro diagnostics (IVD) manufacturers should define a calibration hierarchy to assign traceable values to their system calibrators. Medical laboratories should know and verify how manufacturers have implemented the traceability of their calibrators and estimate the corresponding MU on clinical samples. Accordingly, the internal quality control (IQC) program should be redesigned to permit IVD traceability surveillance through the verification by medical laboratories that control materials, provided by the manufacturer as a part of measuring systems, are in the clinically suitable validation range (IQC component I). Separately, laboratories should also monitor the reliability of employed IVD measuring systems through the IQC component II, devoted to estimation of MU due to random effects and to obtaining MU of provided results, in order to apply prompt corrective actions if the performance is worsening when compared to appropriate analytical specifications, thus jeopardizing the clinical validity of test results.

Traceability validation of six enzyme measurements on the Abbott Alinity c analytical system.

Background Laboratory professionals should independently verify the correct implementation of metrological traceability of commercial measuring systems and determine if their performance is fit for purpose. We evaluated the trueness, uncertainty of measurements, and transferability of six clinically important enzyme measurements (alanine aminotransferase [ALT], alkaline phosphatase [ALP], aspartate aminotransferase [AST], creatine kinase [CK], γ-glutamyltransferase [γGT], and lactate dehydrogenase [LDH]) performed on the Abbott Alinity c analytical system. Methods Target values and associated uncertainties were assigned to three pools for each enzyme by using the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) reference measurement procedures (RMPs) and the pools were then measured on the Alinity system. Bias estimation and regression studies were performed, and the uncertainty associated with Alinity measurements was also estimated, using analytical performance specifications (APS) derived from biological variability of measurands as goals. Finally, to validate the transferability of the obtained results, a comparison study between two Alinity systems located in Milan, Italy, and Bydgoszcz, Poland, was carried out. Results Correct implementation of traceability to the IFCC RMPs and acceptable measurement uncertainty fulfilling desirable (ALP, AST, LDH) or optimal APS (ALT, CK, γGT) was verified for all evaluated enzymes. An optimal alignment between the two Alinity systems located in Milan and Bydgoszcz was also found for all enzyme measurements. Conclusions We confirmed that measurements of ALT, ALP, AST, CK, γGT, and LDH performed on the Alinity c analytical system are correctly standardized to the IFCC reference measurement systems and the system alignment is consistent between different platforms.

Searching for a role of procalcitonin determination in COVID-19: a study on a selected cohort of hospitalized patients.

Objectives: Procalcitonin (PCT) has been proposed for differentiating viral vs. bacterial infections. In COVID-19, some preliminary results have shown that PCT testing could act as a predictor of bacterial co-infection and be a useful marker for assessment of disease severity. Methods: We studied 83 COVID-19 hospitalized patients in whom PCT was specifically ordered by attending physicians. PCT results were evaluated according to the ability to accurately predict bacterial co-infections and death in comparison with other known biomarkers of infection and with major laboratory predictors of COVID-19 severity. Results: Thirty-three (39.8%) patients suffered an in-hospital bacterial co-infection and 44 (53.0%) patients died. In predicting bacterial co-infection, PCT showed a relatively low accuracy (area under receiver-operating characteristic [ROC] curve [AUC]: 0.757; 95% confidence interval [CI]: 0.651-0.845), with a strength for detecting the outcome not significantly different from that of white blood cell count and C-reactive protein (CRP). In predicting patient death, PCT showed an AUC of 0.815 (CI: 0.714-0.892), not better than those of other more common laboratory tests, such as blood lymphocyte percentage (AUC: 0.874, p=0.19), serum lactate dehydrogenase (AUC: 0.860, p=0.47), blood neutrophil count (AUC: 0.845, p=0.59), and serum albumin (AUC: 0.839, p=0.73). Conclusions: Procalcitonin (PCT) testing, even when appropriately ordered, did not provide a significant added value in COVID-19 patients when compared with more consolidated biomarkers of infection and poor clinical outcome. The major application of PCT in COVID-19 is its ability, associated with a negative predictive value >90%, to exclude a bacterial co-infection when a rule-out cut-off (<0.25 µg/L) is applied.