Giuseppe, Lippi

Padoan, Andrea

Plebani, Mario

English

Padua Research Archive

Biological variation: back to basics

PLEBANI, MARIO

PADOAN, ANDREA

Giuseppe Lippi

Archivio istituzionale della ricerca - Università di Padova

Clin Chem Lab Med 2015; 53(2): 155–156EditorialMario Plebani, Andrea Padoan and Giuseppe LippiBiological variation: back to basicsDOI 10.1515/cclm-2014-1182The appreciation of the substantial influence of biologi-cal variation (BV) on laboratory testing and interpreta-tion of laboratory results has represented a milestone in the history of laboratory medicine. It has paved the way for a wide series of studies aimed to accurately define the components of BV, set analytical quality specifications and related goals for internal quality control and exter-nal quality assessment programs, along with specific criteria for data interpretation, including the reference change value (RCV) [1–3]. The unquestionable importance of quality specifications based on BV in the hierarchy of models defined in the Stockholm Conference in 1999 [4, 5] represented a breakthrough in promoting the generation and application of data on BV. This issue has been for long recognized in Clinical Chemistry and Laboratory Medicine as an essential concept for defining the appropriateness of reference values for specific constituents, and for support-ing the adoption of RCV in the interpretation of data from serial measurements [6–16]. In this issue of the journal, we publish an article about structure and criteria used for the generation of the BV database [17] along with a comment-ing Editorial, which are aimed to update our knowledge in this field and encouraging the revision and update of BV database, to reassure that the information is prominently evidence-based [18].A number of problems are increasingly recognized as a source of debate and concern. First, in an era of global harmonization, mystification should be prevented in the broad range of terms and symbols used to define the components of BV [19]. Therefore, we recognize and support the recent proposition by Simundic et al. to adopt a consistent and harmonized use of terms and symbols as follows [20]: – CVI: within-subject biological variation (variation within a single individual estimated as a pooled vari-ation from a group of individuals); – CVG: between-subject biological variation (varia-tion between the central tendencies of a group of individuals); – CVA: analytical variation (analytical imprecision); should always be clarified, giving mode of derivation and type (such as reproducibility, reliability, or total) and number of analyses, runs, and time period; – RCV: reference change value (difference required for significance for 2 serial results from an individual); should always be accompanied by the formula used, namely, × ×1 2 1 22 2A I2 (CV CV ) ;Z  the Z-score should be defined to state the probability and whether unidi-rectional or bidirectional differences were calculated; and – II: index of individuality (ratio of analytical and within-subject to between-subject biological variation); should always be accompanied with the formula used for calculation: the preferred × 1 22 2A I G(CV CV ) /CV  or the now seemingly more usual CVI/CVG.Accordingly, the journal will now recommend both authors and referees to comply with this harmonized use of terms and symbols, which are those originally used by Callum G. Fraser and adopted in the papers presented at the Stockholm Conference [3–5]. Further terms and symbols should, therefore, be viewed as simple mistakes or ‘deviation from the right way’.Second, to guarantee the publication of valuable results, clinical investigations on BV should then rely on appropriate study designs, and in particular the reference population inclusion criteria should be carefully speci-fied. Demographic characteristics, (e.g., age, sex and eth-nicity), the clinical examination used to establish health in an individual, and subgroups analyses should be declared by authors. Therefore, we also support the sug-gestion of Aarstand and colleagues to develop an interna-tional standard for performing and reporting of studies on BV [18].As a final consideration, studies should be based on a robust statistical analysis of data. This firstly entails the verification of data distribution, that can be either Gauss-ian (i.e., normal) or non-Gaussian (i.e., non-normal). In the former instance, parametric analysis can be used [i.e., mean and standard deviation distribution, Pearson’s corre-lation, Student’s t-test, and analysis of variance (ANOVA), etc]. As reported by Fraser and Harris [1], nested ANOVA is an efficient way to estimate CVI. Despite this method not being very sensitive to slightly deviation from normality, Brought to you by | Universita degli Studi di PadovaAuthenticatedDownload Date | 4/1/15 12:27 PM156      Plebani et al.: Biological variation: back to basicsit is highly sensitive to highly aberrant  observations.  Outliers can be detected by Cochran’s test and the Reed’s criterion, considering that if an assay is done in dupli-cate and one measurement is aberrant, the advisable approach is to delete both of them. Moreover, data should be carefully inspected for homoscedasticity before apply-ing ANOVA, as serious violation in homoscedasticity may result in biased estimates and in overestimated goodness of fit. In case of data showing a log-normal rather than a normal distribution, log-transformation should be per-formed before the analyses as CVI and CVG can be calcu-lated by back-transformation. Finally, for data that does meet neither normal nor log-normal distributions, a non-parametric approach could be alternatively used, possibly evaluating the imprecision of estimates (i.e., median and percentile distribution, Spearman’s or Kendall’s correla-tion, Mann-Whitney-Wilcoxon test, etc.) [21]. However, as up to now this latter topic has been only marginally studied, we suggest that clinical investigators should con-centrate their future efforts to deal with BV calculation on non-normal distributed data.Author contributions: All the authors have accepted respon-sibility for the entire content of this submitted manuscript and approved submission.Financial support: None declared.Employment or leadership: None declared.Honorarium: None declared.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.References1. Fraser CG, Harris EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Clin Lab Sci 1989;27:409–37.2. Fraser CG. The application of theoretical goals based on biologi-cal variation data in proficiency testing. Arch Pathol Lab Med 1988;112:404–15.3. Fraser CG. General strategies to set quality specifications for reliability performance characteristics. Scand J Clin Lab Invest 1999;59:487–90.4. Fraser CG, Kallner A, Kenny D, Hyltoft Petersen P. Strategies to set global quality specifications in laboratory medicine. Scand J Clin Lab Invest 1999;59:477–8.5. Kenny D, Fraser CG, Hyltoft Petersen P, Kallner A. Consensus agreement. Scand J Clin Lab Invest 1999;59:585.6. Büttner J. Biological variation and quantification of health: the emergence of the concept of normality. Clin Chem Lab Med 1998;36:69–73.7. Franzini C. Need for correct estimates of biological variation:  the example of C-reactive protein. Clin Chem Lab Med 1998;36:131–2.8. Henny J, Petitclerc C, Fuentes-Arderiu X, Petersen PH,  Queraltó JM, Schiele F, et al. Need for revisiting the concept of reference values. Clin Chem Lab Med 2000;38:589–95.9. Fraser CG. Reference change values. Clin Chem Lab Med 2011;50:807–12.10. Plebani M, Lippi G. Biological variation and reference change values: an essential piece of the puzzle of laboratory testing. Clin Chem Lab Med 2012;50:189–90.11. Carlsen S, Petersen PH, Skeie S, Skadberg Ø, Sandberg S. Within-subject biological variation of glucose and HbA(1c) in healthy persons and in type 1 diabetes patients. Clin Chem Lab Med 2011;49:1501–7.12. Yin L, Li G, Hu D. Application of quality specification based on biological variation in planning quality control strategy. Clin Chem Lab Med 2012;50:1843–4.13. Siest G, Henny J, Gräsbeck R, Wilding P, Petitclerc C,  Queraltó JM, et al. The theory of reference values: an unfinished symphony. Clin Chem Lab Med 2013;51:47–64.14. 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;51:851–62.15. 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;51:1997–2007.16. Braga F, Ferraro S, Mozzi R, Panteghini M. The importance of individual biology in the clinical use of serum biomarkers for ovarian cancer. Clin Chem Lab Med 2014;52:1625–31.17. Perich C, Minchinela J, Ricós C, Fernández-Calle P, Alvarez V, Doménech MV, et al. Biological variation database: structure and criteria used for generation and update. Clin Chem Lab Med 2015;53:299–305.18. Aarsand AK, Roraas T, Sandberg S. Biological variation. Reliable data is essential. Clin Chem Lab Med 2015;53:153–4.19. 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 [Epub ahead of print 2014 Nov 17]. pii: clinchem.2014.233791.20. Plebani M. Harmonization in laboratory medicine: the complete picture. Clin Chem Lab Med 2013;51:741–51.21. Nakagawa S, Schielzeth H. Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists. Biol Rev Camb Philos Soc 2010;85:935–56.*Corresponding author: Mario Plebani, Department of  Medicine-DIMED, University-Hospital of Padua, Via Giustiniani, 2, 35128 Padua, Italy, Phone: +49 8212780/92, Fax: +49 663240, E-mail: mario.plebani@unipd.itAndrea Padoan: Department of Medicine-DIMED, University-Hospital of Padua, Padua, ItalyGiuseppe Lippi: U.O. Diagnostica Ematochimica, Azienda Ospedaliero-Università di Parma, Parma, ItalyQ1:Please  supply voulme and page number for ref. [19]Brought to you by | Universita degli Studi di PadovaAuthenticatedDownload Date | 4/1/15 12:27 PM

Plebani M

Padoan A

LIPPI, Giuseppe

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Biological variation: back to basics.

Mario Plebani

Andrea Padoan

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Biological variation: back to basics

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