Home Medicine Biological variation estimates obtained from Chinese subjects for 32 biochemical measurands in serum
Article
Licensed
Unlicensed Requires Authentication

Biological variation estimates obtained from Chinese subjects for 32 biochemical measurands in serum

  • Liming Ma , Bin Zhang , Limei Luo , Rui Shi , Yonghua Wu and Yunshuang Liu EMAIL logo
Published/Copyright: August 18, 2022
Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 60 Issue 10

Abstract

Objectives

The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) have established a program of work to make available, and to enable delivery of well characterized data describing the biological variation (BV) of clinically important measurands. Guided by the EFLM work the study presented here delivers BV estimates obtained from Chinese subjects for 32 measurands in serum.

Methods

Samples were drawn from 48 healthy volunteers (26 males, 22 females; age range, 21–45 years) for 5 consecutive weeks at Chinese laboratory. Sera were stored at −80 °C before triplicate analysis of all samples on a Cobas 8000 modular analyzer series. Outlier and homogeneity analyses were performed, followed by CV-ANOVA, to determine BV estimates with confidence intervals.

Results

The within-subject biological variation (CVI) estimates for 30 of the 32 measurands studied, were lower than listed on the EFLM database; the exceptions were alanine aminotransferase (ALT), lipoprotein (a) (LP(a)). Most of the between-subject biological variation (CVG) estimates were lower than the EFLM database entries.

Conclusions

This study delivers BV data for a Chinese population to supplement the EFLM BV database. Population differences may have an impact on applications of BV Data.

Keywords: analytical performance specifications; biochemical measurement; biological variation; index of individuality; reference change value
Corresponding author: Yunshuang Liu, Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Changjia Alley of Jingzhong Street 12 621000 Mianyang, P.R. China, Phone: +86 816 2247 526, E-mail:
Liming Ma and Bin Zhang contributed equally to this work.

  1. Research funding: None declared.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: This study was approved by the Ethics Committee of Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China (No. S – 2020–051).

References

1. Ricós, C, Álvarez, V, Minchinela, J, Fernández-Calle, P, Perich, C, Boned, B, et al.. Biologic variation approach to daily laboratory. Clin Lab Med 2017;37:47–56. https://doi.org/10.1016/j.cll.2016.09.005.Search in Google Scholar PubMed

2. Minchinela, J, Ricós, C, Perich, C, Fernández-Calle, P, Alvarez, V, Domnech, MV, et al.. Biological variation database and quality specifications for imprecision, bias and total error (desirable and minimum) The 2014 Update. Available from: http://www.westgard.com/biodatabase-2014-update.htm [Accessed 18 Feb 2021].Search in Google Scholar

3. Aarsand, AK, Fernandez-Calle, P, Webster, C, Coskun, A, Gonzales-Lao, E, Diaz-Garzon, J, et al.. The EFLM biological variation database. Available from: http://biologicalvariation.eu/ [Accessed 17 Mar 2022].Search in Google Scholar

4. 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.Search in Google Scholar PubMed

5. Ricós, C, Álvarez, V, Perich, C, Fernández-Calle, P, Minchinela, J, Cava, F, et al.. Rationale for using data on biological variation. Clin Chem Lab Med 2015;53:863–70. https://doi.org/10.1515/cclm-2014-1142.Search in Google Scholar PubMed

6. Perich, C, Minchinela, J, Ricos, C, Fernandez-Calle, P, Alvarez, V, Domenech, MV, et al.. Biological variation database: structure and criteria used for generation and update. Clin Chem Lab Med 2015;53:299–305. https://doi.org/10.1515/cclm-2014-0739.Search in Google Scholar PubMed

7. 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.Search in Google Scholar PubMed

8. Bartlett, WA, Braga, F, Carobene, A, Coşkun, A, Prusa, R, Fernandez-Calle, P, et al.. Biological variation working group, European federation of clinical chemistry and laboratory medicine (EFLM). A checklist for critical appraisal of studies of biological variation. Clin Chem Lab Med 2015;53:879–85.10.1515/cclm-2014-1127Search in Google Scholar PubMed

9. Aarsand, AK, Røraas, T, Fernandez-Calle, P, Ricos, C, Díaz-Garzón, J, Jonker, N, et al.. European federation of clinical chemistry and laboratory medicine working group on biological variation and task and finish group for the biological variation database. The biological variation data critical appraisal checklist: a standard for evaluating studies on biological variation. Clin Chem 2018;64:501–14.10.1373/clinchem.2017.281808Search in Google Scholar PubMed

10. Carobene, A, Røraas, T, Sølvik, UØ, Sylte, MS, Sandberg, S, Guerra, E, et al.. European biological variation study of the EFLM working group on biological variation. Biological variation estimates obtained from 91 healthy study participants for 9 enzymes in serum. Clin Chem 2017;63:1141–50. https://doi.org/10.1373/clinchem.2016.269811.Search in Google Scholar PubMed

11. Carobene, A, Marino, I, Coşkun, A, Serteser, M, Unsal, I, Guerra, E, et al.. European biological variation study of the EFLM working group on biological variation. 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.Search in Google Scholar PubMed

12. Coşkun, A, Carobene, A, Kilercik, M, Serteser, M, Sandberg, S, Aarsand, AK, et al.. European biological variation study of the EFLM working group on biological variation. Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects. Clin Chem Lab Med 2018;56:1309–18. https://doi.org/10.1515/cclm-2017-1155.Search in Google Scholar PubMed

13. 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 2021;60:505–17. https://doi.org/10.1515/cclm-2021-0370.Search in Google Scholar PubMed

14. Carobene, A, Aarsand, AK, Guerra, E, Bartlett, WA, Coşkun, A, Díaz-Garzón, J, et al.. European federation of clinical chemistry and laboratory medicine working group on biological variation. 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.Search in Google Scholar PubMed

15. Ceriotti, F, Díaz-Garzón Marco, J, Fernández-Calle, P, Maregnani, A, Aarsand, AK, Coskun, A, et al.. European federation of clinical chemistry and laboratory medicine (EFLM) working group on biological variation. 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;25–58:1741–7.10.1515/cclm-2019-1182Search in Google Scholar PubMed

16. 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.Search in Google Scholar PubMed

17. Carobene, A, Strollo, M, Jonker, N, Barla, G, Bartlett, WA, Sandberg, S. Biological variation working group, European federation of clinical chemistry and laboratory medicine. 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;54:1599–608.10.1515/cclm-2016-0035Search in Google Scholar PubMed

18. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney inter, Suppl 2013;3:1–150.Search in Google Scholar

19. 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.Search in Google Scholar PubMed

20. Braga, F, Panteghini, M. Generation of data on within-subject biological variation in laboratory medicine: an update. Crit Rev Clin Lab Sci 2016;53:313–25. https://doi.org/10.3109/10408363.2016.1150252.Search in Google Scholar PubMed

21. Fernández-Calle, P, Díaz-Garzón, J, Bartlett, W, Sandberg, S, Braga, F, Beatriz, B, et al.. EFLM working group on biological variation and task group for the biological variation database. Biological variation estimates of thyroid related measurands – meta-analysis of BIVAC compliant studies. Clin Chem Lab Med 2021;60:483–93. https://doi.org/10.1515/cclm-2021-0904.Search in Google Scholar PubMed

22. Carobene, A, Braga, F, Roraas, T, Sandberg, S, Bartlett, WA. A systematic review of data on biological variation for alanine aminotransferase, aspartate aminotransferase and γ-glutamyl transferase. Clin Chem Lab Med 2013;51:1997–2007. https://doi.org/10.1515/cclm-2013-0096.Search in Google Scholar PubMed

23. Hölzel, WG. Intra-individual variation of some analytes in serum of patients with insulin-dependent diabetes mellitus. Clin Chem 1987;33:57–61. https://doi.org/10.1093/clinchem/33.1.57.Search in Google Scholar

24. Pineda-Tenor, D, Laserna-Mendieta, EJ, Timón-Zapata, J, Rodelgo-Jiménez, L, Ramos-Corral, R, Recio-Montealegre, A, et al.. Biological variation and reference change values of common clinical chemistry and haematologic laboratory analytes in the elderly population. Clin Chem Lab Med 2013;51:851–62. https://doi.org/10.1515/cclm-2012-0701.Search in Google Scholar PubMed

25. Jonker, N, Aslan, B, Boned, B, Marqués-García, F, Ricós, C, Alvarez, V, et al.. The European federation of clinical chemistry and laboratory medicine working group on biological variation and task group for the biological variation database. Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes. Clin Chem Lab Med 2020;60:469–78.10.1515/cclm-2020-1168Search in Google Scholar PubMed

26. Groesbeck, D, Köttgen, A, Parekh, R, Selvin, E, Schwartz, GJ, Coresh, J, et al.. Age, gender, and race effects on cystatin C levels in US adolescents. Clin J Am Soc Nephrol 2008;3:1777–85. https://doi.org/10.2215/cjn.00840208.Search in Google Scholar

27. Pei, X, Bao, L, Xu, Z, Yan, C, He, J, Zhu, B, et al.. Diagnostic value of cystatin C and glomerular filtration rate formulae in Chinese nonelderly and elderly populations. J Nephrol 2013;26:476–84. https://doi.org/10.5301/jn.5000181.Search in Google Scholar PubMed

28. González-Lao, E, Corte, Z, Simón, M, Ricós, C, Coskun, A, Braga, F, et al.. European federation of clinical chemistry and laboratory medicine working group on biological variation and task group for the biological variation database. Systematic review of the biological variation data for diabetes related analytes. Clin Chim Acta 2019;488:61–7.10.1016/j.cca.2018.10.031Search in Google Scholar PubMed

29. Pagani, F, Panteghini, M. Significance of various parameters derived from biological variability for lipid and lipoprotein analyses. Clin Biochem 1993;26:415–20. https://doi.org/10.1016/0009-9120(93)90119-q.Search in Google Scholar PubMed

30. Lindberg, M, Borgstrøm Hager, H, Brokner, M. Week-to-week biological variation of methylmalonic acid and homocysteine in healthy women. Scand J Clin Lab Invest 2019;79:247–50. https://doi.org/10.1080/00365513.2019.1590858.Search in Google Scholar PubMed

31. Qi, Z, Chen, Y, Zhang, L, Ma, X, Wang, F, Cheng, Q, et al.. Biological variations of thirteen plasma measurands. Clin Chim Acta 2016;452:87–91. https://doi.org/10.1016/j.cca.2015.11.008.Search in Google Scholar PubMed

32. Aarsand, AK, Díaz-Garzón, J, Fernandez-Calle, P, Guerra, E, Locatelli, M, Bartlett, WA, et al.. European federation of clinical chemistry and laboratory medicine working group on biological variation. 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;64:1380–93.10.1373/clinchem.2018.288415Search in Google Scholar PubMed

33. Liang, L, He, H, Zeng, Y, Zhang, M, Wang, X, Li, X, et al.. Evaluation of biological variation of glycated hemoglobin and glycated albumin in healthy Chinese subjects. J Clin Lab Anal 2019;33:e22715. https://doi.org/10.1002/jcla.22715.Search in Google Scholar PubMed PubMed Central

34. Petersen, PH, Fraser, CG, Sandberg, S, Goldschmidt, H. The index of individuality is often a misinterpreted quantity characteristic. Clin Chem Lab Med 1999;37:655–61. https://doi.org/10.1515/cclm.1999.102.Search in Google Scholar

35. Petersen, PH, Sandberg, S, Fraser, CG, Goldschmidt, H. Influence of index of individuality on false positives in repeated sampling from healthy individuals. Clin Chem Lab Med 2001;39:160–5. https://doi.org/10.1515/cclm.2001.027.Search in Google Scholar PubMed

36. Ceriotti, F, Hinzmann, R, Panteghini, M. Reference intervals: the way forward. Ann Clin Biochem 2009;46:8–17. https://doi.org/10.1258/acb.2008.008170.Search in Google Scholar PubMed

37. Braga, F, Panteghini, M. Verification of in vitro medical diagnostics (IVD) metrological traceability: responsibilities and strategies. Clin Chim Acta 2014;432:55–61. https://doi.org/10.1016/j.cca.2013.11.022.Search in Google Scholar PubMed

38. Sandberg, S, Fraser, FG, 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.Search in Google Scholar PubMed

39. Panteghini, M, Sandberg, S. Defining analytical performance specifications 15 years after the Stockholm conference. Clin Chem Lab Med 2015;53:829–32. https://doi.org/10.1515/cclm-2015-0303.Search in Google Scholar PubMed

40. Klee, GG. Establishment of outcome-related analytic performance goals. Clin Chem 2010;56:714–22. https://doi.org/10.1373/clinchem.2009.133660.Search in Google Scholar PubMed

41. Fraser, CG, Hyltoft Petersen, P, Libeer, JC, Ricos, C. Proposals for setting generally applicable quality goals solely based on biology. Ann Clin Biochem 1997;34:8–12. https://doi.org/10.1177/000456329703400103.Search in Google Scholar PubMed

42. Díaz-Garzón, J, Fernández-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.Search in Google Scholar PubMed

43. 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.Search in Google Scholar PubMed

44. 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.Search in Google Scholar PubMed

Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2021-0928).

Received: 2021-08-20
Accepted: 2022-06-24
Published Online: 2022-08-18
Published in Print: 2022-09-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. The relevance of establishing method-dependent decision thresholds of serum folate in pregnancy and lactation: when the laboratory stewardship meets the health-care needs
  4. Reviews
  5. Strategies to minimise the current disadvantages experienced by women in faecal immunochemical test-based colorectal cancer screening
  6. What is the impact of circulating histones in COVID-19: a systematic review
  7. Mini Review
  8. Diagnostic utility of pleural cell-free nucleic acids in undiagnosed pleural effusions
  9. Guidelines and Recommendations
  10. Evaluation of the cardiovascular risk in patients undergoing major non-cardiac surgery: role of cardiac-specific biomarkers
  11. Genetics and Molecular Diagnostics
  12. Detection of DNA copy number alterations by matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis of single nucleotide polymorphisms
  13. General Clinical Chemistry and Laboratory Medicine
  14. Fifty years of newborn screening for congenital hypothyroidism: current status in Australasia and the case for harmonisation
  15. Commutability assessment of reference materials for homocysteine
  16. External quality assessment for detection of methylated Syndecan 2 (SDC2) in China
  17. Patient-based real-time quality control for quantitative hepatitis B virus DNA test using moving rate of positive and negative patient results
  18. Performance of HDL-C measurements assessed by a 4-year trueness-based EQA/PT program in China
  19. Two-site evaluation of the Roche Elecsys Vitamin D total III assay
  20. A novel point-of-care device accurately measures thyrotropin in whole blood, capillary blood and serum
  21. IgA rheumatoid factor in rheumatoid arthritis
  22. Reference Values and Biological Variations
  23. Reference intervals of 14 biochemical markers for children and adolescence in China: the PRINCE study
  24. Chinese normotensive and essential hypertensive reference intervals for plasma aldosterone and renin activity by liquid chromatography-tandem mass spectrometry
  25. Biological variation estimates obtained from Chinese subjects for 32 biochemical measurands in serum
  26. Cancer Diagnostics
  27. Testosterone analysis in castrated prostate cancer patients: suitability of the castration cut-off and analytical accuracy of the present-day clinical immunoassays
  28. Cardiovascular Diseases
  29. Point-of-care high-sensitivity troponin-I analysis in capillary blood for acute coronary syndrome diagnostics
  30. Platelet count and clinical outcomes among ischemic stroke patients with endovascular thrombectomy in DIRECT-MT
  31. Infectious Diseases
  32. Measurement of anti SARS-CoV-2 RBD IgG in saliva: validation of a highly sensitive assay and effects of the sampling collection method and correction by protein
  33. Letters to the Editors
  34. The simple reproducibility of a measurement result does not equal its overall measurement uncertainty
  35. Complexity of serological assays and misunderstandings of WHO International Units
  36. Ct values of different SARS CoV2 variants: a single center observational study from Innsbruck, Austria
  37. Alignment of the new generation of Abbott Alinity γ-glutamyltransferase assay to the IFCC reference measurement system should be improved
  38. Thermal and chronological stability of monocyte distribution width (MDW), the new biomarker for sepsis
  39. Two comments for the current commutability assessment
  40. Plasma neurofilament light chain in Chinese children with later-onset spinal muscular atrophy
https://doi.org/10.1515/cclm-2021-0928
Keywords for this article
analytical performance specifications; biochemical measurement; biological variation; index of individuality; reference change value

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. The relevance of establishing method-dependent decision thresholds of serum folate in pregnancy and lactation: when the laboratory stewardship meets the health-care needs
  4. Reviews
  5. Strategies to minimise the current disadvantages experienced by women in faecal immunochemical test-based colorectal cancer screening
  6. What is the impact of circulating histones in COVID-19: a systematic review
  7. Mini Review
  8. Diagnostic utility of pleural cell-free nucleic acids in undiagnosed pleural effusions
  9. Guidelines and Recommendations
  10. Evaluation of the cardiovascular risk in patients undergoing major non-cardiac surgery: role of cardiac-specific biomarkers
  11. Genetics and Molecular Diagnostics
  12. Detection of DNA copy number alterations by matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis of single nucleotide polymorphisms
  13. General Clinical Chemistry and Laboratory Medicine
  14. Fifty years of newborn screening for congenital hypothyroidism: current status in Australasia and the case for harmonisation
  15. Commutability assessment of reference materials for homocysteine
  16. External quality assessment for detection of methylated Syndecan 2 (SDC2) in China
  17. Patient-based real-time quality control for quantitative hepatitis B virus DNA test using moving rate of positive and negative patient results
  18. Performance of HDL-C measurements assessed by a 4-year trueness-based EQA/PT program in China
  19. Two-site evaluation of the Roche Elecsys Vitamin D total III assay
  20. A novel point-of-care device accurately measures thyrotropin in whole blood, capillary blood and serum
  21. IgA rheumatoid factor in rheumatoid arthritis
  22. Reference Values and Biological Variations
  23. Reference intervals of 14 biochemical markers for children and adolescence in China: the PRINCE study
  24. Chinese normotensive and essential hypertensive reference intervals for plasma aldosterone and renin activity by liquid chromatography-tandem mass spectrometry
  25. Biological variation estimates obtained from Chinese subjects for 32 biochemical measurands in serum
  26. Cancer Diagnostics
  27. Testosterone analysis in castrated prostate cancer patients: suitability of the castration cut-off and analytical accuracy of the present-day clinical immunoassays
  28. Cardiovascular Diseases
  29. Point-of-care high-sensitivity troponin-I analysis in capillary blood for acute coronary syndrome diagnostics
  30. Platelet count and clinical outcomes among ischemic stroke patients with endovascular thrombectomy in DIRECT-MT
  31. Infectious Diseases
  32. Measurement of anti SARS-CoV-2 RBD IgG in saliva: validation of a highly sensitive assay and effects of the sampling collection method and correction by protein
  33. Letters to the Editors
  34. The simple reproducibility of a measurement result does not equal its overall measurement uncertainty
  35. Complexity of serological assays and misunderstandings of WHO International Units
  36. Ct values of different SARS CoV2 variants: a single center observational study from Innsbruck, Austria
  37. Alignment of the new generation of Abbott Alinity γ-glutamyltransferase assay to the IFCC reference measurement system should be improved
  38. Thermal and chronological stability of monocyte distribution width (MDW), the new biomarker for sepsis
  39. Two comments for the current commutability assessment
  40. Plasma neurofilament light chain in Chinese children with later-onset spinal muscular atrophy
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2026 De Gruyter Brill
Downloaded on 4.2.2026 from https://www.degruyterbrill.com/document/doi/10.1515/cclm-2021-0928/html?lang=en
Scroll to top button