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Author: search.filters.author.Jonker, NielsSubject: search.filters.subject.analytical performance specification

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    The European Biological Variation Study (EuBIVAS): a summary report
    (WALTER DE GRUYTER GMBH, 2022-01-01) Carobene, Anna; Aarsand, Aasne K.; Bartlett, William A.; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Guerra, Elena; Jonker, Niels; Locatelli, Massimo; Plebani, Mario; Sandberg, Sverre; Ceriotti, Ferruccio
    Biological variation (BV) data have many important applications in laboratory medicine. Concerns about quality of published BV data led the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) 1st Strategic Conference to indicate need for new studies to generate BV estimates of required quality. In response, the EFLM Working Group on BV delivered the multicenter European Biological Variation Study (EuBIVAS). This review summarises the EuBIVAS and its outcomes. Serum/plasma samples were taken from 91 ostensibly healthy individuals for 10 consecutive weeks at 6 European centres. Analysis was performed by Siemens ADVIA 2400 (clinical chemistry), Cobas Roche 8000, c702 and e801 (proteins and tumor markers/hormones respectively), ACL Top 750 (coagulation parameters), and IDS iSYS or DiaSorin Liaison (bone biomarkers). A strict preanalytical and analytical protocol was applied. To determine BV estimates with 95\% CI, CV-ANOVA after analysis of outliers, homogeneity and trend analysis or a Bayesian model was applied. EuBIVAS has so far delivered BV estimates for 80 different measurands. Estimates for 10 measurands (Non-HDL Cholesterol, S100-beta protein, neuron-specific enolase, soluble transferrin receptor, intact fibroblast growth-factor-23, uncarboxylated-unphosphorylated matrix-Gla protein, human epididymis protein-4, free, conjugated and \%free prostate-specific antigen), prior to EuBIVAS, have not been available. BV data for creatinine and troponin I were obtained using two analytical methods in each case. The EuBIVAS has delivered high-quality BV data for a wide range of measurands. The BV estimates are for many measurands lower than those previously reported, having an impact on the derived analytical performance specifications and reference change values.
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    The European Biological Variation Study (EuBIVAS): Biological Variation Data for Coagulation Markers Estimated by a Bayesian Model
    (OXFORD UNIV PRESS INC, 2021-01-01) Aarsand, Aasne K.; Kristoffersen, Ann Helen; Sandberg, Sverre; Stove, Bard; Coskun, Abdurrahman; Fernandez-Calle, Pilar; Diaz-Garzon, Jorge; Guerra, Elena; Ceriotti, Ferruccio; Jonker, Niels; Roraas, Thomas; Carobene, Anna; Chem, European Federation Clinical
    BACKGROUND: For biological variation (BV) data to be safely used, data must be reliable and relevant to the population in which they are applied. We used samples from the European Biological Variation Study (EuBIVAS) to determine BV of coagulation markers by a Bayesian model robust to extreme observations and used the derived within-participant BV estimates {[}CVP(i)] to assess the applicability of the BV estimates in clinical practice. METHOD: Plasma samples were drawn from 92 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate for activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen, D-dimer, antithrombin (AT), protein C, protein S free, and factor VIII (FVIII). A Bayesian model with Student t likelihoods for samples and replicates was applied to derive CVP(i) and predicted BV estimates with 95\% credibility intervals. RESULTS: For all markers except D-dimer, CVP( i) were homogeneously distributed in the overall study population or in subgroups. Mean within-subject estimates (CVI) were <5\% for APTT, PT, AT, and protein S free, <10\% for protein C and FVIII, and <12\% for fibrinogen. For APTT, protein C, and protein S free, estimates were significantly lower in men than in women <= 50 years. CONCLUSION: For most coagulation markers, a common CVI estimate for men and women is applicable, whereas for APTT, protein C, and protein S free, sex-specific reference change values should be applied. The use of a Bayesian model to deliver individual CVP(i) allows for improved interpretation and application of the data.