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Analytical Performance Specifications for Lipoprotein(a), Apolipoprotein B-100, and Apolipoprotein A-I Using the Biological Variation Model in the EuBIVAS Population
(OXFORD UNIV PRESS INC, 2020-01-01) Clouet-Foraison, Noemie; Marcovina, Santica M.; Guerra, Elena; Aarsand, Aasne K.; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Sandberg, Sverre; Ceriotti, Ferruccio; Carobene, Anna; Chem, European Federation Clinical
BACKGROUND: With increased interest in lipoprotein(a) (Lp{[}a]) concentration as a target for risk reduction and growing clinical evidence of its impact on cardiovascular disease (CVD) risk, rigorous analytical performance specifications (APS) and accuracy targets for Lp(a) are required. We investigated the biological variation (BV) of Lp(a), and 2 other major biomarkers of CVD, apolipoprotein A-I (apoA-I) and apolipoprotein B-100 (apoB), in the European Biological Variation Study population. METHOD: Serum samples were drawn from 91 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate on a Roche Cobas 8000 c702. Outlier, homogeneity, and trend analysis were performed, followed by CV-ANOVA to determine BV estimates and their 95\% CIs. These estimates were used to calculate APS and reference change values. For Lp(a), BV estimates were determined on normalized concentration quintiles. RESULTS: Within-subject BV estimates were significantly different between sexes for Lp(a) and between women aged <50 and >50 years for apoA-I and apoB. Lp(a) APS was constant across concentration quintiles and, overall, lower than APS based on currently published data, whereas results were similar for apoA-I and apoB. CONCLUSION: Using a fully Biological Variation Data Critical Appraisal Checklist (BIVAC)-compliant protocol, our study data confirm BV estimates of Lp(a) listed in the European Federation of Clinical Chemistry and Laboratory Medicine database and reinforce concerns expressed in recent articles regarding the suitability of older APS recommendations for Lp(a) measurements. Given the heterogeneity of Lp(a), more BIVAC-compliant studies on large numbers of individuals of different ethnic groups would be desirable.
Biological variation data for lipid cardiovascular risk assessment biomarkers. A systematic review applying the biological variation data critical appraisal checklist (BIVAC)
(ELSEVIER, 2019-01-01) Diaz-Garzon, Jorge; Fernandez Calle, Pilar; Minchinela, Joana; Aarsand, Aasne K.; Bartlett, William A.; Aslan, Berna; Boned, Beatriz; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Gonzalez-Lao, Elisabet; Jonker, Niels; Marques-Garcia, Fernando; Perich, Carmen; Ricos, Carmen; Simon, Margarita; Sandberg, Sverre
Background: Biological variation (BV) data can be used to set analytical performance specifications (APS) for lipid assays. Poor performance will impact upon the efficacy of international guidelines for cardiovascular risk assessment (CVR) and relevant clinical decision limits. This systematic review applies the Biological Variation Data Critical Appraisal Checklist (BIVAC) to published studies of BV of CVR biomarkers enabling metanalysis of the data. Methods: Studies of BV of total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides and apolipoproteins A(1) and B, retrieved using a systematic literature search, were evaluated and graded using the BIVAC. Meta analysis of CV1 and CVG estimates were performed utilizing weightings based upon BIVAC grades and the width of the data confidence intervals. Results: Applying the BIVAC, ten publications were graded as D, 43 as C, 5 as B and 1 as A (fully compliant). A total of 196 CV1 and 87 CVG estimates were available for the different lipid measurands. The meta-analysis-derived BV data estimates were generally concordant with those in the online 2014 BV database. Conclusions: Application of BIVAC identifies BV data suitable for many important applications including setting APS. Additionally, this review identifies a need for new BIVAC compliant studies to deliver BV reference data in different subpopulations.
Biological variation estimates of thyroid related measurands - meta-analysis of BIVAC compliant studies
(WALTER DE GRUYTER GMBH, 2022-01-01) Fernandez-Calle, Pilar; Diaz-Garzon, Jorge; Bartlett, William; Sandberg, Sverre; Braga, Federica; Beatriz, Boned; Carobene, Anna; Coskun, Abdurrahman; Gonzalez-Lao, Elisabet; Marques, Fernando; Perich, Carmen; Simon, Margarida; Aarsand, Aasne K.; Variation, E.F.L.M. Working Grp Biol; Database, Task Grp Biol Variation
Objectives Testing for thyroid disease constitutes a high proportion of the workloads of clinical laboratories worldwide. The setting of analytical performance specifications (APS) for testing methods and aiding clinical interpretation of test results requires biological variation (BV) data. A critical review of published BV studies of thyroid disease related measurands has therefore been undertaken and meta-analysis applied to deliver robust BV estimates. Methods A systematic literature search was conducted for BV studies of thyroid related analytes. BV data from studies compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) were subjected to meta-analysis. Global estimates of within subject variation (CVI) enabled determination of APS (imprecision and bias), indices of individuality, and indicative estimates of reference change values. Results The systematic review identified 17 relevant BV studies. Only one study (EuBIVAS) achieved a BIVAC grade of A. Methodological and statistical issues were the reason for B and C scores. The meta-analysis derived CVI generally delivered lower APS for imprecision than the mean CVA of the studies included in this systematic review. Conclusions Systematic review and meta-analysis of studies of BV of thyroid disease biomarkers have enabled delivery of well characterized estimates of BV for some, but not all measurands. The newly derived APS for imprecision for both free thyroxine and triiodothyronine may be considered challenging. The high degree of individuality identified for thyroid related measurands reinforces the importance of RCVs. Generation of BV data applicable to multiple scenarios may require definition using ``big data{''} instead of the demanding experimental approach.
Biological Variation of Cardiac Troponins in Health and Disease: A Systematic Review and Meta-analysis
(OXFORD UNIV PRESS INC, 2021-01-01) Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Sandberg, Sverre; Ozcurumez, Mustafa; Bartlett, William A.; Coskun, Abdurrahman; Carobene, Anna; Perich, Carmen; Simon, Margarita; Marques, Fernando; Boned, Beatriz; Gonzalez-Lao, Elisabet; Braga, Federica; Aarsand, Aasne K.; Chem, European Federation Clinical; Database, Task Grp Biol Variation
BACKGROUND: Many studies have assessed the biological variation (BV) of cardiac-specific troponins (cTn), reporting widely varying within-subject BV (CVI) estimates. The aim of this study was to provide metaanalysis-derived BV estimates for troponin I (cTnI) and troponin T (cTnT) for different sampling intervals and states of health. METHODS: Relevant studies were identified by a systematic literature search. Studies were classified according to their methodological quality by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC-compliant studies were performed after stratification by cTn isoform, exclusion of results below the limit of detection, states of health, and sampling interval to deliver reference change values (RCV), index of individuality (II) and analytical performance specifications (APS) for these settings. RESULTS: Sixteen and 15 studies were identified for cTnI and cTnT, respectively, out of which 6 received a BIVAC grade A. Five studies had applied contemporary cTnI assays, but none contemporary cTnT. High-sensitivity (hs-) cTnI and cTnT delivered similar estimates in all settings. Long-term CVI estimates (15.1
Biological variation of serum iron from the European biological variation study (EuBIVAS)
(WALTER DE GRUYTER GMBH, 2022-01-01) Carobene, Anna; Aarsand, Aasne K.; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Locatelli, Massimo; Fernandez-Calle, Pilar; Sandberg, Sverre; Ceriotti, Ferruccio; Chem, European Federation Clinical
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.
Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes
(WALTER DE GRUYTER GMBH, 2022-01-01) Jonker, Niels; Aslan, Berna; Boned, Beatriz; Marques-Garcia, Fernando; Ricos, Carmen; Alvarez, Virtudes; Bartlett, William; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Gonzalez-Lao, Elisabet; Minchinela, Joana; Perich, Carmen; Simon, Margarita; Sandberg, Sverre; Aarsand, Aasne K.
Objectives Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma
Critical review and meta-analysis of biological variation estimates for tumor markers
(WALTER DE GRUYTER GMBH, 2022-01-01) Marques-Garcia, Fernando; Boned, Beatriz; Gonzalez-Lao, Elisabet; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Carmen Perich, Maria; Simon, Margarida; Jonker, Niels; Aslan, Berna; Bartlett, William Alexander; Sandberg, Sverre; Aarsand, Aasne K.; Chem, European Federation Clinical; Database, Task Grp Biol Variation
Objectives Biological variation data (BV) can be used for different applications, but this depends on the availability of robust and relevant BV data. In this study, we aimed to summarize and appraise BV studies for tumor markers, to examine the influence of study population characteristics and concentrations on BV estimates and to discuss the applicability of BV data for tumor markers in clinical practice. Methods Studies reporting BV data for tumor markers related to gastrointestinal, prostate, breast, ovarian, haematological, lung, and dermatological cancers were identified by a systematic literature search. Relevant studies were evaluated by the Biological Variation Data Critical Appraisal Checklist (BIVAC) and meta-analyses were performed for BIVAC compliant studies to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV with 95\% CI. Results The systematic review identified 49 studies delivering results for 22 tumor markers
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
European Biological Variation Study (EuBIVAS): within-and between-subject biological variation estimates for serum biointact parathyroid hormone based on weekly samplings from 91 healthy participants
(AME PUBL CO, 2020-01-01) Bottani, Michela; Banfi, Giuseppe; Guerra, Elena; Locatelli, Massimo; Aarsand, Aasne K.; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Sandberg, Sverre; Ceriotti, Ferruccio; Gonzalez-Lao, Elisabet; Simon, Margarita; Carobene, Anna; Chem, European Federation Clinical
Background: The European Biological Variation Study (EuBIVAS) was created by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Biological Variation to establish high-quality biological variation (BV) estimates for clinically important measurands. In this study, the aim was to deliver reliable BV estimates for the biointact parathyroid hormone (PTH 1-84). Methods: Serum samples were obtained from a population of 91 healthy individuals (38 men, 43 premenopausal women, and 10 post-menopausal women
Harmonization initiatives in the generation, reporting and application of biological variation data
(2018-01-01) Aarsand, Aasne K.; Roraas, Thomas; Bartlett, William A.; Coskun, Abdurrahman; Carobene, Anna; Fernandez-Calle, Pilar; Jonker, Niels; Diaz-Garzon, Jorge; Braga, Federica; Sandberg, Sverre; Chem, European Federation Clinical
Biological variation (BV) data have many applications in laboratory medicine. However, concern has been raised that some LW estimates in use today may be irrelevant or of unacceptable quality. A number of initiatives have been launched by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and other parties to deliver a more harmonized practice in the generation, reporting and application of BV data. Resulting from a necessary focus upon the veracity of historical BV studies, critical appraisal and meta-analysis of published BV studies is possible through application of the Biological Variation Data Critical Appraisal Checklist (BIVAC), published in 2017. The BIVAC compliant large-scale European Biological Variation Study delivers updated high-quality BV data for a wide range of measurands. Other significant developments include the publication of a Medical Subject Heading term for BV and recommendations for common terminology for reporting of BV data. In the near future, global BV estimates derived from meta-analysis of BIVAC appraised publications will be accessible in a Biological Variation Database at the EFLM website. The availability of these high-quality data, which have many applications that impact on the quality and interpretation of clinical laboratory results, will afford improved patient care.
Long-term within- and between-subject biological variation of 29 routine laboratory measurands in athletes
(WALTER DE GRUYTER GMBH, 2022-01-01) Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Aarsand, Aasne K.; Sandberg, Sverre; Coskun, Abdurrahaman; Carobene, Anna; Jonker, Niels; Itkonen, Outi; Bartlett, William A.; Buno, Antonio; Chem, European Federation Clinical
Objectives Within- and between-subject biological variation (BV) estimates have many applications in laboratory medicine. However, robust high-quality BV estimates are lacking for many populations, such as athletes. This study aimed to deliver BV estimates of 29 routine laboratory measurands derived from a Biological Variation Data Critical Appraisal Checklist compliant design in a population of high-endurance athletes. Methods Eleven samples per subject were drawn from 30 triathletes monthly, during a whole sport season. Serum samples were measured in duplicate for proteins, liver enzymes, lipids and kidney-related measurands on an Advia2400 (Siemens Healthineers). After outlier and homogeneity analysis, within-subject (CVI) and between-subject (CVG) biological variation estimates were delivered (CV-ANOVA and log-ANOVA, respectively) and a linear mixed model was applied to analyze the effect of exercise and health related variables. Results Most CVI estimates were similar or only slightly higher in athletes compared to those reported for the general population, whereas two- to three-fold increases were observed for amylase, ALT, AST and ALP. No effect of exercise and health related variables were observed on the CVI estimates. For seven measurands, data were not homogeneously distributed and BV estimates were therefore not reported. Conclusions The observation of higher CVI estimates in athletes than what has been reported for the general population may be related to physiological stress over time caused by the continuous practice of exercise. The BV estimates derived from this study could be applied to athlete populations from disciplines in which they exercise under similar conditions of intensity and duration.
Personalized reference intervals - statistical approaches and considerations
(WALTER DE GRUYTER GMBH, 2022-01-01) Coskun, Abdurrahman; Sandberg, Sverre; Unsal, Ibrahim; Yavuz, Fulya G.; Cavusoglu, Coskun; Serteser, Mustafa; Kilercik, Meltem; Aarsand, Aasne K.
For many measurands, physicians depend on population-based reference intervals (popRI), when assessing laboratory test results. The availability of personalized reference intervals (prRI) may provide a means to improve the interpretation of laboratory test results for an individual. prRI can be calculated using estimates of biological and analytical variation and previous test results obtained in a steady-state situation. In this study, we aim to outline statistical approaches and considerations required when establishing and implementing prRI in clinical practice. Data quality assessment, including analysis for outliers and trends, is required prior to using previous test results to estimate the homeostatic set point. To calculate the prRI limits, two different statistical models based on `prediction intervals' can be applied. The first model utilizes estimates of `within-person biological variation' which are based on an individual's own data. This model requires a minimum of five previous test results to generate the prRI. The second model is based on estimates of `within-subject biological variation', which represents an average estimate for a population and can be found, for most measurands, in the EFLM Biological Variation Database. This model can be applied also when there are lower numbers of previous test results available. The prRI offers physicians the opportunity to improve interpretation of individuals' test results, though studies are required to demonstrate if using prRI leads to better clinical outcomes. We recommend that both popRIs and prRIs are included in laboratory reports to aid in evaluating laboratory test results in the follow-up of patients.
Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation
(OXFORD UNIV PRESS INC, 2021-01-01) Coskun, Abdurrahman; Sandberg, Sverre; Unsal, Ibrahim; Cavusoglu, Coskun; Serteser, Mustafa; Kilercik, Meltem; Aarsand, Aasne K.
BACKGROUND: The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. METHODS: A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. RESULTS: Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using >= 3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. CONCLUSIONS: Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.
Providing Correct Estimates of Biological Variation-Not an Easy Task. The Example of S100-beta Protein and Neuron-Specific Enolase
(AMER ASSOC CLINICAL CHEMISTRY, 2018-01-01) Carobene, Anna; Guerra, Elena; Locatelli, Massimo; Ceriotti, Ferruccio; Sandberg, Sverre; Fernandez-Calle, Pilar; Coskun, Abdurrahman; Aarsand, Aasne K.; Chem, European Federation Clinical; Variation, Working Grp Biological
Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of 20 haematological parameters
(WALTER DE GRUYTER GMBH, 2020-01-01) Coskun, Abdurrahman; Braga, Federica; Carobene, Anna; Tejedor Ganduxe, Xavier; Aarsand, Aasne K.; Fernandez-Calle, Pilar; Diaz-Garzon Marco, Jorge; Bartlett, William; Jonker, Niels; Aslan, Berna; Minchinela, Joana; Boned, Beatriz; Gonzalez-Lao, Elisabet; Marques-Garcia, Fernando; Perich, Carmen; Ricos, Carmen; Simon, Margarita; Sandberg, Sverre; Chem, European Federation Clinical
Background: Interpretation of the complete blood count (CBC) parameters requires reliable biological variation (BV) data. The aims of this study were to appraise the quality of publications reporting BV data for CBC parameters by applying the BV Data Critical Appraisal Checklist (BIVAC) and to deliver global BV estimates based on BIVAC compliant studies. Methods: Relevant publications were identified by a systematic literature search and evaluated for their compliance with the 14 BIVAC criteria, scored as A, B, C or D, indicating decreasing compliance. Global CVI and CVG estimates with 95\% CI were delivered by a meta-analysis approach using data from BIVAC compliant papers (grades A-C). Results: In total, 32 studies were identified
Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of serum Zinc, Copper and Selenium
(WALTER DE GRUYTER GMBH, 2022-01-01) Coskun, Abdurrahman; Aarsand, Aasne K.; Braga, Federica; Carobene, Anna; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Jonker, Niels; Lao, Elisabet Gonzalez; Marques-Garcia, Fernando; Sandberg, Sverre; Chem, European Federation Clinical; Grp, Lab Medicine Working
The Biological Variation Data Critical Appraisal Checklist: A Standard for Evaluating Studies on Biological Variation
(AMER ASSOC CLINICAL CHEMISTRY, 2018-01-01) Aarsand, Aasne K.; Roraas, Thomas; Fernandez-Calle, Pilar; Ricos, Carmen; Diaz-Garzon, Jorge; Jonker, Niels; Perich, Carmen; Gonzalez-Lao, Elisabet; Carobene, Anna; Minchinela, Joana; Coskun, Abdurrahman; Simon, Margarita; Alvarez, Virtudes; Bartlett, William A.; Fernandez-Fernandez, Pilar; Boned, Beatriz; Braga, Federica; Corte, Zoraida; Aslan, Berna; Sandberg, Sverre; Chem, European Federation Clinical; Variation, Working Grp Biological; Biological, Task \& Finish Grp
BACKGROUND: Concern has been raised about the quality of available biological variation (BV) estimates and the effect of their application in clinical practice. A European Federation of Clinical Chemistry and Laboratory Medicine Task and Finish Group has addressed this issue. The aim of this report is to (a) describe the Biological Variation Data Critical Appraisal Checklist (BIVAC), which verifies whether publications have included all essential elements that may impact the veracity of associated BV estimates, (b) use the BIVAC to critically appraise existing BV publications on enzymes, lipids, kidney, and diabetes-related measurands, and (c) apply metaanalysis to deliver a global within-subject BV (CVI) estimate for alanine aminotransferase (ALT). METHODS: In the BIVAC, publications were rated as A, B, C, or D, indicating descending compliance for 14 BIVAC quality items, focusing on study design, methodology, and statistical handling. A D grade indicated that associated BV estimates should not be applied in clinical practice. Systematic searches were applied to identify BV studies for 28 different measurands. RESULTS: In total, 128 publications were identified, providing 935 different BV estimates. Nine percent achieved D scores. Outlier analysis and variance homogeneity testing were scored as C in >60\% of 847 cases. Metaanalysis delivered a CVI estimate for ALT of 15.4\%. CONCLUSIONS: Application of BIVAC to BV publications identified deficiencies in required study detail and delivery, especially for statistical analysis. Those deficiencies impact the veracity of BV estimates. BV data from BIVAC-compliant studies can be combined to deliver robust global estimates for safe clinical application. (c) 2017 American Association for Clinical Chemistry
The EuBIVAS: Within- and Between-Subject Biological Variation Data for Electrolytes, Lipids, Urea, Uric Acid, Total Protein, Total Bilirubin, Direct Bilirubin, and Glucose
(AMER ASSOC CLINICAL CHEMISTRY, 2018-01-01) Aarsand, Aasne K.; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Guerra, Elena; Locatelli, Massimo; Bartlett, William A.; Sandberg, Sverre; Roraas, Thomas; Ceriotti, Ferruccio; Solvik, Una Orvim; Sylte, Marit Sverresdotter; Coskun, Abdurrahman; Serteser, Mustafa; Unsal, Ibrahim; Tosato, Francesca; Plebani, Mario; Jonker, Niels; Barla, Gerhard; Carobene, Anna; Chem, European Federation Clinical
BACKGROUND: The European Federation of Clinical Chemistry and Laboratory Medicine European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined data describing biological variation (BV) of clinically important measurands. Here, EuBIVAS-based BV estimates of serum electrolytes, lipids, urea, uric acid, total protein, total bilirubin, direct bilirubin, and glucose, as well as their associated analytical performance specifications (APSs), are presented. METHOD: Samples were drawn from 91 healthy individuals (38 male, 53 female
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.