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Biological variation database: structure and criteria used for generation and update

  • Carmen Perich , Joana Minchinela , Carmen Ricós EMAIL logo , Pilar Fernández-Calle , Virtudes Alvarez , María Vicenta Doménech , Margarita Simón , Carmen Biosca , Beatriz Boned , José Vicente García-Lario , Fernando Cava , Pilar Fernández-Fernández and Callum G. Fraser

Abstract

Background: Numerical data on the components of biological variation (BV) have many uses in laboratory medicine, including in the setting of analytical quality specifications, generation of reference change values and assessment of the utility of conventional reference values.

Methods: Generation of a series of up-to-date comprehensive database of components of BV was initiated in 1997, integrating the more relevant information found in publications concerning BV. A scoring system was designed to evaluate the robustness of the data included. The database has been updated every 2 years, made available on the Internet and derived analytical quality specifications for imprecision, bias and total allowable error included in the tabulation of data.

Results and conclusions: Our aim here is to document, in detail, the methodology we used to evaluate the reliability of the included data compiled from the published literature. To date, our approach has not been explicitly documented, although the principles have been presented at many symposia, courses and conferences.


Corresponding author: Dra. Carmen Ricós, Spanish Society of Clinical Biochemistry and Molecular Pathology (SEQC), Analytical Quality Commission, Plaza Gala Placidia 2, Barcelona, Spain, E-mail:

References

1. Fraser CG. Biological variation: from principles to practice. Washington DC: AACC Press, 2001.Search in Google Scholar

2. Fraser CG. The application of theoretical goals based on biological variation data in proficiency testing. Arch Pathol Lab Med 1988;112:404–15.Search in Google Scholar

3. Fraser CG. Biological variation in clinical chemistry. An update: collated data, 1988–1991. Arch Pathol Lab Med 1992;116:916–23.Search in Google Scholar

4. Sebastián-Gámbaro MA, Lirón-Hernández FJ, Fuentes-Arderiu X. Intra- and inter-individual biological variability data bank. Eur J Clin Chem Clin Biochem 1997;35:845–52.Search in Google Scholar

5. Ricós C, Álvarez V, Cava F, García-Lario JV, Hernández A, Jiménez CV, et al. Current databases on biological variation: pros, cons and progress. Scand J Clin Lab Invest 1999;59:491–500.10.1080/00365519950185229Search in Google Scholar PubMed

6. Minchinela J, Ricós C, Perich C, Fernández-Calle P, Alvarez V, Doménech 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 7 July, 2014.Search in Google Scholar

7. Minchinela J, Ricós C, Perich C, Fernández-Calle P, Alvarez V, Doménech MV, et al. Base de datos de los componentes de Variación Biológica, con las especificaciones de la calidad analítica (deseable, mínima y óptima). Actualización del año 2014. Available from: http://www.seqc.es/es/Comisiones/18/9/102/Base_de_datos_de_Variacion_biologica_%7C_Comision_de_Calidad_Analitica_%7C_Comite_Cientifico/. Accessed 7 July, 2014.Search in Google Scholar

8. Fraser CG, Browning MC. The “index of fiduciality” proposed for use in evaluation and comparison of methods. Clin Chem 1988;34:1356–7.10.1093/clinchem/34.6.1356Search in Google Scholar

9. Fraser CG, Harris EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Clin Lab Sci 1989;27:409–37.10.3109/10408368909106595Search in Google Scholar PubMed

10. Costongs GM, Janson PC, Bas BM, Hermans J, Van Werch JW, Brombacher PJ. Short-term and long-term intraindividual variations and critical differences of clinical chemistry laboratory parameters. J Clin Chem Clin Biochem 1985;23:7–16.Search in Google Scholar

11. Fraser CG, Cummings ST, Wilkinson SP, Neville RG, Knox JD, Ho O, et al. biological variability of 26 clinical chemistry analytes in elderly people. Clin Chem 1989,35:783–6.10.1093/clinchem/35.5.783Search in Google Scholar

12. Gallagher SK, Johnson LK, Milne DB. Short-term and long-term variability of indices related to nutritional status. I: Ca, Cu, Fe, Mg and Zn. Clin Chem 1989;35:369–73.10.1093/clinchem/35.3.369Search in Google Scholar

13. González-Revalderia J, García-Bermejo S, Menchén-Herreros A, Fernandez-Rodriguez E. Towards narrower analytical goals in routine laboratory work. Clin Chem 1991;37:596.10.1093/clinchem/37.4.596Search in Google Scholar

14. Gowans EM, Fraser CG. Long-term biological variability of commonly analyzed serum constituents. Clin Chem 1987;33:717.10.1093/clinchem/33.5.717Search in Google Scholar

15. Hölzel WG. Influence of hypertension and antihypertensive drugs on the biological intra-individual variation of electrolytes and lipids in serum. Clin Chem 1988;34:1485–8.10.1093/clinchem/34.7.1485Search in Google Scholar

16. Hölzel WG. Intra-individual biological variation of some analytes in serum of patients with chronic renal failure. Clin Chem 1987;33:670–3.10.1093/clinchem/33.5.670Search in Google Scholar

17. Morris HA, Wishart JM, Horowitz M, Need AG, Nordin BE. The reproducibility of bone-related biochemistry variables in post-menopausal women. Ann Clin Biochem 1990;27:562–8.10.1177/000456329002700607Search in Google Scholar PubMed

18. Pickup JF, Harris EK, Kearns M, Brown SS. Intra-individual variation of some serum constituents and its relevance to population-based reference ranges. Clin Chem 1977;23:842–50.10.1093/clinchem/23.5.842Search in Google Scholar

19. Pineda-Tenor D, Laserna-Mendieta EJ, Timón-Zapata J, Rodelgo-Jiménez L, Ramos-Corral L, Recio-Montealegre A, et al. Biological variation and reference change value of common chemistry and haematologic laboratory analytes in the elderly population. Clin Chem Lab Med 2013;51:851–62.10.1515/cclm-2012-0701Search in Google Scholar PubMed

20. Ricós C, García-Arumí E, Rodriguez-Rubio R, Schwartz S. Eficacia de un programa interno de control de calidad. Quim Clin 1986;5:159–65.Search in Google Scholar

21. Williams GZ, Widdowson GM, Penton J. individual character variation in time-series studies of healthy people. II. Differences in values for clinical chemistry analytes in serum among demographic groups, by age and sex. Clin Chem 1978;24:313–20.10.1093/clinchem/24.2.313Search in Google Scholar

22. Roraas R, Petersen HP, Sandberg S. Confidence intervals and power calculations for within-subject biological variation: effect of analytical variation, number of replicates, number of samples and number of individuals. Clin Chem 2012;58:1306–13.10.1373/clinchem.2012.187781Search in Google Scholar PubMed

23. Bailey D, Bevilcqua V, Colantonio DA, Pasic MD, Perumal N, Chan M, et al. Pediatric within-day biological variation and quality specifications for 38 biochemical markers in the CALIPER cohort. Clin Chem 2014;60:518–29.10.1373/clinchem.2013.214312Search in Google Scholar PubMed

24. Cembrowski GS, Tran DV, Higgins TN. The use of serial patient blood gas, electrolyte and glucose results to derive biological variation: a new tool to assess the acceptability of intensive care unit testing. Clin Chem Lab Med 2010;48:1447–54.10.1515/CCLM.2010.286Search in Google Scholar PubMed

25. Braga F, Dolci A, Mosca A, Panteghini M. Biological variation of glycated hemoglobin. Clin Chim Acta 2010;411:1006–10.10.1016/j.cca.2010.07.030Search in Google Scholar PubMed

26. Carlsten S, Hyltoft Petersen P, Skeie S, Skadberg O, Sandberg S. Within subject biological variation of glucose and HbA1c in healthy persons and type I diabetes patients. Clin Chem Lab Med 2011;49:1501–7.Search in Google Scholar

27. Carobene A, Graziani MS, Lo Cascio C, Tretti L, Cremonese E, Yabarek T, et al. Age dependence of within-subject BV of nine common clinical chemistry analytes. Clin Chem Lab Med 2012;50:841–4.10.1515/cclm-2011-0868Search in Google Scholar PubMed

28. Braga F, Panteghini M. Standardization and analytical goals for glycated hemoglobin measurement. Clin Chem Lab Med 2013;51:1719–26.10.1515/cclm-2013-5001Search in Google Scholar

29. Cooper G, DeJonge N, Ehrmeyer S, Yundt-Pacheco J, Jansen R, Ricós C, et al. Collective opinion paper on findings of the 2010 convocation of experts on laboratory quality. Clin Chem Lab Med 2011;49:793–802.10.1515/CCLM.2011.149Search in Google Scholar PubMed

30. 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-glutamyltransferase. Clin Chem Lab Med 2013;51:1997–2007.10.1515/cclm-2013-0096Search in Google Scholar PubMed

31. STARD guidelines. Available from: http://www.stard-statement.org/. Accessed 7 July, 2014.Search in Google Scholar

32. Bartlett W, Braga F, Carobene A, Coskun A, Prusa R, Fernandez-Calle P, et al. Identification of key meta data to enable safe accurate and effective transferability of biological variation data. 2014 American Association of Clinical Chemistry Annual Meeting AACC, Chicago, Illinois. Available from: http://www.aacc.org/events/2014_annual_meeting/abstracts/Documents/AACC_14_AM_A20.pdf. Accessed 8 July, 2014.Search in Google Scholar

33. Bartlett W, Braga F, Carobene A, Coskun A, Prusa R, Fernandez-Calle P, et al. Definition of a minimum data set to accompany indices of biological variation. 2014 International Federation of Clinical Chemistry Poster Abstract -IFCC WorldLab Istanbul 2014. Clin Chem Lab Med 2014;52(Suppl):S315.Search in Google Scholar


Supplemental Material

The online version of this article (DOI: 10.1515/cclm-2014-0739) offers supplementary material, available to authorized users.


Received: 2014-7-17
Accepted: 2014-9-29
Published Online: 2014-11-21
Published in Print: 2015-2-1

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