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Permanent URI for this collectionhttps://hdl.handle.net/11443/932

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Author: search.filters.author.Diaz-Garzon, JorgeSubject: search.filters.subject.reference change value

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    European Biological Variation Study (EuBIVAS): within- and between-subject biological variation estimates for serum thyroid biomarkers based on weekly samplings from 91 healthy participants
    (WALTER DE GRUYTER GMBH, 2022-01-01) Bottani, Michela; Aarsand, Aasne K.; Banfi, Giuseppe; Locatelli, Massimo; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Sandberg, Sverre; Ceriotti, Ferruccio; Carobene, Anna; Chem, European Federation Clinical
    Objectives Thyroid biomarkers are fundamental for the diagnosis of thyroid disorders and for the monitoring and treatment of patients with these diseases. The knowledge of biological variation (BV) is important to define analytical performance specifications (APS) and reference change values (RCV). The aim of this study was to deliver BV estimates for thyroid stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), thyroglobulin (TG), and calcitonin (CT). Methods Analyses were performed on serum samples obtained from the European Biological Variation Study population (91 healthy individuals from six European laboratories
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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.
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    Biological variation: recent development and future challenges
    (WALTER DE GRUYTER GMBH, 2022-01-01) Sandberg, Sverre; Carobene, Anna; Bartlett, Bill; Coskun, Abdurrahman; Fernandez-Calle, Pilar; Jonker, Niels; Diaz-Garzon, Jorge; Aarsand, Aasne K.
    Biological variation (BV) data have many applications in laboratory medicine. However, these depend on the availability of relevant and robust BV data fit for purpose. BV data can be obtained through different study designs, both by experimental studies and studies utilizing previously analysed routine results derived from laboratory databases. The different BV applications include using BV data for setting analytical performance specifications, to calculate reference change values, to define the index of individuality and to establish personalized reference intervals. In this review, major achievements in the area of BV from last decade will be presented and discussed. These range from new models and approaches to derive BV data, the delivery of high-quality BV data by the highly powered European Biological Variation Study (EuBIVAS), the Biological Variation Data Critical Appraisal Checklist (BIVAC) and other standards for deriving and reporting BV data, the EFLM Biological Variation Database and new applications of BV data including personalized reference intervals and measurement uncertainty.