Biological variation: recent development and future challenges.

BIVAC EuBIVAS biological variation personalized reference intervals (prRI) reference change value

Journal

Clinical chemistry and laboratory medicine
ISSN: 1437-4331
Titre abrégé: Clin Chem Lab Med
Pays: Germany
ID NLM: 9806306

Informations de publication

Date de publication:
25 04 2023
Historique:
received: 10 12 2022
accepted: 12 12 2022
medline: 3 4 2023
pubmed: 21 12 2022
entrez: 20 12 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 36537071
pii: cclm-2022-1255
doi: 10.1515/cclm-2022-1255
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

741-750

Informations de copyright

© 2022 Walter de Gruyter GmbH, Berlin/Boston.

Références

Sandberg, S, Røraas, T, Aarsand, AK. Biological variation and analytical performance specifications (Internet). In: Rifai, N, Chiu, RWK, Young, I, Burnham, CAD, Wittver, CT, editors. Tietz textbook of Laboratory medicine , 7th ed. St Lous: Elsevier; 2022:335–56 pp.
Coşkun, A, Sandberg, S, Unsal, I, Cavusoglu, C, Serteser, M, Kilercik, M, et al.. Personalized reference intervals in laboratory medicine: a new model based on within-subject biological variation. Clin Chem 2021;67:374–84. https://doi.org/10.1093/clinchem/hvaa233 .
doi: 10.1093/clinchem/hvaa233
Carobene, A. Reliability of biological variation data available in an online database: need for improvement. Clin Chem Lab Med 2015;53:871–7. https://doi.org/10.1515/cclm-2014-1133 .
doi: 10.1515/cclm-2014-1133
Sandberg, S, Carobene, A, Aarsand, AK. Biological variation – eight years after the 1st Strategic Conference of EFLM. Clin Chem Lab Med 2022;60:465–8. https://doi.org/10.1515/cclm-2022-0086 .
doi: 10.1515/cclm-2022-0086
EFLM – working group: biological variation . Available from: https://www.eflm.eu/site/page/a/1148 [Accessed 10 Dec 2022].
EFLM – task group biological variation database . Available from: https://www.eflm.eu/site/page/a/1394 [Accessed 10 Dec 2022].
Fraser, CG, Harris, EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Clin Lab Sci 1989;27:409–37. https://doi.org/10.3109/10408368909106595 .
doi: 10.3109/10408368909106595
Aarsand, AK, Webster, C, Coskun, A, Gonzales-Lao, E, Diaz-Garzon, J, Roraas, T, et al.. EFLM biological variation database. Available from: https://biologicalvariation.eu [Accessed 10 Dec 2022].
Røraas, T, Støve, B, Petersen, PH, Sandberg, S. Biological variation: the effect of different distributions on estimated within-person variation and reference change values. Clin Chem 2016;62:725–36. https://doi.org/10.1373/clinchem.2015.252296 .
doi: 10.1373/clinchem.2015.252296
Røraas, T, Sandberg, S, Aarsand, AK, Støve, B. A Bayesian approach to biological variation analysis. Clin Chem 2019;65:995–1005. https://doi.org/10.1373/clinchem.2018.300145 .
doi: 10.1373/clinchem.2018.300145
Jones, GRD. Estimates of within-subject biological variation derived from pathology databases: an approach to allow assessment of the effects of age, sex, time between sample collections, and analyte concentration on reference change values. Clin Chem 2019;65:579–88. https://doi.org/10.1373/clinchem.2018.290841 .
doi: 10.1373/clinchem.2018.290841
Røys, EÅ, Guldhaug, NA, Viste, K, Jones, GD, Alaour, B, Sylte, MS, et al.. Sex hormones and adrenal steroids: biological variation estimated using direct and indirect methods. Clin Chem 2023;69:100–9. https://doi.org/10.1093/clinchem/hvac175 .
doi: 10.1093/clinchem/hvac175
Marques-Garcia, F, Boned, B, González-Lao, E, Braga, F, Carobene, A, Coskun, A, et al.. Critical review and meta-analysis of biological variation estimates for tumor markers. Clin Chem Lab Med 2022;60:494–504. https://doi.org/10.1515/cclm-2021-0725 .
doi: 10.1515/cclm-2021-0725
Cembrowski, GS, Lyon, AW, McCudden, C, Qiu, Y, Xu, Q, Mei, J, et al.. Transformation of sequential hospital and outpatient laboratory data into between-day reference change values. Clin Chem 2022;68:595–603. https://doi.org/10.1093/clinchem/hvab271 .
doi: 10.1093/clinchem/hvab271
Marqués-García, F, Nieto-Librero, A, González-García, N, Galindo-Villardón, P, Martínez-Sánchez, LM, Tejedor-Ganduxé, X, et al.. Within-subject biological variation estimates using an indirect data mining strategy. Spanish multicenter pilot study (BiVaBiDa). Clin Chem Lab Med 2022;60:1804–12. https://doi.org/10.1515/cclm-2021-0863 .
doi: 10.1515/cclm-2021-0863
Carobene, A, Strollo, M, Jonker, N, Barla, G, Bartlett, WA, Sandberg, S, et al.. Sample collections from healthy volunteers for biological variation estimates’ update: a new project undertaken by the Working Group on Biological Variation established by the European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem Lab Med 2016;54:1599–608. https://doi.org/10.1515/cclm-2016-0035 .
doi: 10.1515/cclm-2016-0035
Aarsand, AK, Díaz-Garzón, J, Fernandez-Calle, P, Guerra, E, Locatelli, M, Bartlett, WA, et al.. The EuBIVAS: within- and between-subject biological variation data for electrolytes, lipids, urea, uric acid, total protein, total bilirubin, direct bilirubin, and glucose. Clin Chem 2018;64:1380–93. https://doi.org/10.1373/clinchem.2018.288415 .
doi: 10.1373/clinchem.2018.288415
Carobene, A, Aarsand, AK, Guerra, E, Bartlett, WA, Coskun, A, Díaz-Garzón, J, et al.. European biological variation study (EuBIVAS): within- and between-subject biological variation data for 15 frequently measured proteins. Clin Chem 2019;65:1031–41. https://doi.org/10.1373/clinchem.2019.304618 .
doi: 10.1373/clinchem.2019.304618
Bottani, M, Banfi, G, Guerra, E, Locatelli, M, Aarsand, AK, Coşkun, A, et al.. 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. Ann Transl Med 2020;8:855. https://doi.org/10.21037/atm-19-4498 .
doi: 10.21037/atm-19-4498
Ceriotti, F, Marco, JDG, Fernández-Calle, P, Maregnani, A, Aarsand, AK, Coskun, A, et al.. The European Biological Variation Study (EuBIVAS): weekly biological variation of cardiac troponin I estimated by the use of two different high-sensitivity cardiac troponin I assays. Clin Chem Lab Med 2020;58:1741–7. https://doi.org/10.1515/cclm-2019-1182 .
doi: 10.1515/cclm-2019-1182
Cavalier, E, Lukas, P, Bottani, M, Aarsand, AK, Ceriotti, F, Coşkun, A, et al.. European biological variation study (EuBIVAS): within- and between-subject biological variation estimates of β-isomerized C-terminal telopeptide of type I collagen (β-CTX), N-terminal propeptide of type I collagen (PINP), osteocalcin, intact fibroblast growth factor 23 and uncarboxylated-unphosphorylated matrix-gla protein—a cooperation between the EFLM working group on biological variation and the international osteoporosis foundation-international federation of clinical chemistry committee on bone metabolism. Osteoporos Int 2020;31:1461–70. https://doi.org/10.1007/s00198-020-05362-8 .
doi: 10.1007/s00198-020-05362-8
Clouet-Foraison, N, Marcovina, SM, Guerra, E, Aarsand, AK, Coşkun, A, Díaz-Garzón, J, et al.. Analytical performance specifications for lipoprotein(a), apolipoprotein B-100, and apolipoprotein A-I using the biological variation model in the EuBIVAS population. Clin Chem 2020;66:727–36. https://doi.org/10.1093/clinchem/hvaa054 .
doi: 10.1093/clinchem/hvaa054
Carobene, A, Guerra, E, Marqués-García, F, Boned, B, Locatelli, M, Coşkun, A, et al.. Biological variation of morning serum cortisol: updated estimates from the European Biological Variation Study (EuBIVAS) and meta-analysis. Clin Chim Acta 2020;509:268–72. https://doi.org/10.1016/j.cca.2020.06.038 .
doi: 10.1016/j.cca.2020.06.038
Carobene, A, Aarsand, AK, Coşkun, A, Díaz-Garzón, J, Locatelli, M, Fernandez-Calle, P, et al.. Biological variation of serum iron from the European biological variation study (EuBIVAS). Clin Chem Lab Med 2023;61:e57–60. https://doi.org/10.1515/cclm-2022-1091 .
doi: 10.1515/cclm-2022-1091
Aarsand, AK, Røraas, T, Fernandez-Calle, P, Ricos, C, Díaz-Garzón, J, Jonker, N, et al.. The biological variation data critical appraisal checklist: a standard for evaluating studies on biological variation. Clin Chem 2018;64:501–14. https://doi.org/10.1373/clinchem.2017.281808 .
doi: 10.1373/clinchem.2017.281808
Bartlett, WA, Braga, F, Carobene, A, Coskun, A, Prusa, R, Fernandez-Calle, P, et al.. A checklist for critical appraisal of studies of biological variation. Clin Chem Lab Med 2015;53:879–85. https://doi.org/10.1515/cclm-2014-1127 .
doi: 10.1515/cclm-2014-1127
Carobene, A, Marino, I, Coskun, A, Serteser, M, Unsal, I, Guerra, E, et al.. The EuBIVAS project: within-and between-subject biological variation data for serum creatinine using enzymatic and alkaline picrate methods and implications for monitoring. Clin Chem 2017;63:1527–36. https://doi.org/10.1373/clinchem.2017.275115 .
doi: 10.1373/clinchem.2017.275115
Carobene, A, Aarsand, AK, Bartlett, WA, Coskun, A, Diaz-Garzon, J, Fernandez-Calle, P, et al.. The European Biological Variation Study (EuBIVAS): a summary report. Clin Chem Lab Med 2022;60:505–17. https://doi.org/10.1515/cclm-2021-0370 .
doi: 10.1515/cclm-2021-0370
Buoro, S, Carobene, A, Seghezzi, M, Manenti, B, Dominoni, P, Pacioni, A, et al.. Short- and medium-term biological variation estimates of red blood cell and reticulocyte parameters in healthy subjects. Clin Chem Lab Med 2018;56:954–63. https://doi.org/10.1515/cclm-2017-0902 .
doi: 10.1515/cclm-2017-0902
Buoro, S, Seghezzi, M, Manenti, B, Pacioni, A, Carobene, A, Ceriotti, F, et al.. Biological variation of platelet parameters determined by the Sysmex XN hematology analyzer. Clin Chim Acta 2017;470:125–32. https://doi.org/10.1016/j.cca.2017.05.004 .
doi: 10.1016/j.cca.2017.05.004
Buoro, S, Carobene, A, Seghezzi, M, Manenti, B, Pacioni, A, Ceriotti, F, et al.. Short- and medium-term biological variation estimates of leukocytes extended to differential count and morphology-structural parameters (cell population data) in blood samples obtained from healthy people. Clin Chim Acta 2017;473:147–56. https://doi.org/10.1016/j.cca.2017.07.009 .
doi: 10.1016/j.cca.2017.07.009
Coskun, A, Carobene, A, Kilercik, M, Serteser, M, Sandberg, S, Aarsand, AK, et al.. Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects. Clin Chem Lab Med 2018;58:618–28.
Carobene, A, Campagner, A, Uccheddu, C, Banfi, G, Vidali, M, Cabitza, F. The multicenter European Biological Variation Study (EuBIVAS): a new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurands. Clin Chem Lab Med 2022;60:556–68. https://doi.org/10.1515/cclm-2021-0599 .
doi: 10.1515/cclm-2021-0599
Diaz-Garzon, J, Fernandez-Calle, P, Aarsand, AK, Sandberg, S, Coskun, A, Carobene, A, et al.. Long-term within- and between-subject biological variation of 29 routine laboratory measurands in athletes. Clin Chem Lab Med 2022;60:618–28. https://doi.org/10.1515/cclm-2021-0910 .
doi: 10.1515/cclm-2021-0910
Diaz–Garzon, J, Fernandez-Calle, P, Aarsand, AK, Sandberg, S, Buno, A. Biological variation of venous acid-base status measurands in athletes. Clin Chim Acta 2021;523:497–503. https://doi.org/10.1016/j.cca.2021.11.001 .
doi: 10.1016/j.cca.2021.11.001
Kristoffersen, AH, Petersen, PH, Sandberg, S. A model for calculating the within-subject biological variation and likelihood ratios for analytes with a time-dependent change in concentrations; exemplified with the use of D-dimer in suspected venous thromboembolism in healthy pregnant women. Ann Clin Biochem 2012;49:561–9. https://doi.org/10.1258/acb.2012.011265 .
doi: 10.1258/acb.2012.011265
Kristoffersen, AH, Petersen, PH, Bjørge, L, Røraas, T, Sandberg, S. Concentration of fibrin monomer in pregnancy and during the postpartum period. Ann Clin Biochem 2019;89:73–9. https://doi.org/10.1177/0004563219869732 .
doi: 10.1177/0004563219869732
Kristoffersen, AH, Petersen, PH, Røraas, T, Sandberg, S. Estimates of within-subject biological variation of protein C, antithrombin, protein S free, protein S activity, and activated protein C resistance in pregnant women. Clin Chem 2017;63:898–907. https://doi.org/10.1373/clinchem.2016.265900 .
doi: 10.1373/clinchem.2016.265900
Kristoffersen, AH, Petersen, PH, Bjørge, L, Røraas, T, Sandberg, S. Within-subject biological variation of activated partial thromboplastin time, prothrombin time, fibrinogen, factor VIII and von Willebrand factor in pregnant women. Clin Chem Lab Med 2018;56:1297–308. https://doi.org/10.1515/cclm-2017-1220 .
doi: 10.1515/cclm-2017-1220
Diaz-Garzón, J, Fernandez-Calle, P, Minchinela, J, Aarsand, AK, Bartlett, WA, Aslan, B, et al.. Biological variation data for lipid cardiovascular risk assessment biomarkers. A systematic review applying the biological variation data critical appraisal checklist (BIVAC). Clin Chim Acta 2019;495:467–75. https://doi.org/10.1016/j.cca.2019.05.013 .
doi: 10.1016/j.cca.2019.05.013
Fernández-Calle, P, Díaz-Garzón, J, Bartlett, W, Sandberg, S, Braga, F, Beatriz, B, et al.. Biological variation estimates of thyroid related measurands – meta-analysis of BIVAC compliant studies. Clin Chem Lab Med 2022;60:483–93. https://doi.org/10.1515/cclm-2021-0904 .
doi: 10.1515/cclm-2021-0904
Diaz-Garzon, J, Fernandez-Calle, P, Sandberg, S, Özcürümez, M, Bartlett, WA, Coskun, A, et al.. Biological variation of cardiac troponins in health and disease: a systematic review and meta-analysis. Clin Chem 2021;67:256–64. https://doi.org/10.1093/clinchem/hvaa261 .
doi: 10.1093/clinchem/hvaa261
Carobene, A, Lao, EG, Simon, M, Locatelli, M, Coşkun, A, Díaz-Garzón, J, et al.. Biological variation of serum insulin: updated estimates from the European Biological Variation Study (EuBIVAS) and meta-analysis. Clin Chem Lab Med 2022;60:479–82. https://doi.org/10.1515/cclm-2020-1490 .
doi: 10.1515/cclm-2020-1490
Jonker, N, Aslan, B, Boned, B, Marqués-García, F, Ricós, C, Alvarez, V, et al.. Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes. Clin Chem Lab Med 2022;60:469–78. https://doi.org/10.1515/cclm-2020-1168 .
doi: 10.1515/cclm-2020-1168
Ricos, C, Fernandez-Calle, P, Gonzales-Lao, E, Simon, M, Diaz-Garzon, J, Boned, B, et al.. Critical appraisal and meta-analysis of BV studies on glycosylated albumin, glucose, and HbA1c. Adv Lab Med 2020;1:23–9.
Coskun, A, Braga, F, Carobene, A, Ganduxe, XT, Aarsand, AK, Fernandez-Calle, P, et al.. Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of 20 haematological parameters. Clin Chem Lab Med 2020;58:25–32. https://doi.org/10.1515/cclm-2019-0658 .
doi: 10.1515/cclm-2019-0658
Coşkun, A, Aarsand, AK, Braga, F, Carobene, A, Díaz-Garzón, J, Fernandez-Calle, P, et al.. Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of serum Zinc, Copper and Selenium. Clin Chem Lab Med 2022;60:479–82. https://doi.org/10.1515/cclm-2021-0723 .
doi: 10.1515/cclm-2021-0723
González-Lao, E, Corte, Z, Simón, M, Ricos, C, Coskun, A, Braga, F, et al.. Systematic review of the biological variation data for diabetes related analytes. Clin Chim Acta 2019;488:61–7. https://doi.org/10.1016/j.cca.2018.10.031 .
doi: 10.1016/j.cca.2018.10.031
Sandberg, S, Carobene, A, Aarsand, AK, Issue editors. Biological variation – 8 years after the 1st Strategic Conference of EFLM (special issue). Clin Chem Lab Med 2022;60:462–644.
STARD guidelines. Available from: https://www.equator-network.org/reporting-guidelines/stard/ [Accessed 10 Dec 2022].
Biological Variation Data Reporting Checklist. Available from: https://www.wabthings.co.uk/biological-variation [Accessed 2 Dec 2022].
Simundic, AM, Kackov, S, Miler, M, Fraser, CG, Petersen, PH. Terms and symbols used in studies on biological variation: the need for harmonization. Clin Chem 2015;61:438–9. https://doi.org/10.1373/clinchem.2014.233791 .
doi: 10.1373/clinchem.2014.233791
Plebani, M, Padoan, A, Lippi, G. Biological variation: back to basics. Clin Chem Lab Med 2015;53:155–6. https://doi.org/10.1515/cclm-2014-1182 .
doi: 10.1515/cclm-2014-1182
Sandberg, S, Fraser, CG, Horvath, AR, Jansen, R, Jones, G, Oosterhuis, W, et al.. Defining analytical performance specifications: consensus statement from the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem Lab Med 2015;53:833–5. https://doi.org/10.1515/cclm-2015-0067 .
doi: 10.1515/cclm-2015-0067
5th Symposium CELME 2023. Available from: http://www.celme2023.cz [Accessed 2 Dec 2022].
Coskun, A, Sandberg, S, Unsal, I, Cavusoglu, C, Serteser, M, Kilercik, M, et al.. Personalized reference intervals: using estimates of within-subject or within-person biological variation requires different statistical approaches. Clin Chim Acta 2021;524:201–2. https://doi.org/10.1016/j.cca.2021.10.034 .
doi: 10.1016/j.cca.2021.10.034
Coskun, A, Theodorsson, E, Oosterhuis, WP, Sandberg, S. Measurement uncertainty for practical use. Clin Chim Acta 2022;531:352–60. https://doi.org/10.1016/j.cca.2022.04.1003 .
doi: 10.1016/j.cca.2022.04.1003
Coskun, A, Sandberg, S, Unsal, I, Yavuz, FG, Cavusoglu, C, Serteser, M, et al.. Personalized reference intervals – statistical approaches and considerations. Clin Chem Lab Med 2022;60:629–35.
Coskun, A, Sandberg, S, Unsal, I, Serteser, M, Aarsand, AK. Personalized reference intervals: from theory to practice. Crit Rev Clin Lab Sci 2022;59:1–16.
Carobene, A, Banfi, G, Locatelli, M, Vidali, M. Personalized Reference Intervals: from the statistical significance to the clinical usefulness. Clin Chim Acta 2021;524:203–4. https://doi.org/10.1016/j.cca.2021.10.036 .
doi: 10.1016/j.cca.2021.10.036
Ozarda, Y, Sikaris, K, Streichert, T, Macri, J, (C-RIDL) IC on R intervals and, DL. Distinguishing reference intervals and clinical decision limits – a review by the IFCC Committee on Reference Intervals and Decision Limits. Crit Rev Clin Lab Sci 2018;55:420–31. https://doi.org/10.1080/10408363.2018.1482256 .
doi: 10.1080/10408363.2018.1482256

Auteurs

Sverre Sandberg (S)

Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway.
Department of Medical Biochemistry and Pharmacology, Norwegian Porphyria Centre, Haukeland University Hospital, Bergen, Norway.
Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.

Anna Carobene (A)

Laboratory Medicine, IRCCS San Raffaele Scientific Institute, Milan, Italy.

Bill Bartlett (B)

School of Science and Engineering, University of Dundee, Dundee, Scotland.

Abdurrahman Coskun (A)

Acibadem Mehmet Ali Aydınlar University, School of Medicine, Istanbul, Türkiye.

Pilar Fernandez-Calle (P)

Hospital Universitario La Paz, Quality Analytical Commission of Spanish Society of Clinical Chemistry (SEQC), Madrid, Spain.

Niels Jonker (N)

Certe, Wilhelmina Ziekenhuis Assen, Assen, The Netherlands.

Jorge Díaz-Garzón (J)

Hospital Universitario La Paz, Quality Analytical Commission of Spanish Society of Clinical Chemistry (SEQC), Madrid, Spain.

Aasne K Aarsand (AK)

Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway.
Department of Medical Biochemistry and Pharmacology, Norwegian Porphyria Centre, Haukeland University Hospital, Bergen, Norway.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH