Clin Chem Lab Med 2012;50(5):963–964 © 2012 by Walter de Gruyter • Berlin • Boston. DOI 10.1515/CCLM.2011.826
Letter to the Editor: Reply to Fuentes-Arderiu X, et al.
Reference change values may need some improvement but are invaluable tools in laboratory medicine
Callum G. Fraser1,*, Giuseppe Lippi2 and Mario Plebani3 1 Centre for Research into Cancer Prevention and Screening, University of Dundee, Dundee, Scotland, UK 2 U.O. Diagnostica Ematochimica, Dipartimento di Patologia e Medicina di Laboratorio, Azienda OspedalieroUniversitraria di Parma, Parma, Italy 3 Department of Laboratory Medicine, University-Hospital, Padova, Italy
Keywords: biological variation; critical difference; imprecision; reference change value. We thank Fuentes-Arderiu and colleagues for their thoughtful critique (1) of our strong advocacy of the use of reference change values (RCV) in a recent Mini Review (2) and accompanying Editorial (3). They are right that the Mini Review has only one paragraph specifically devoted to the potential disadvantages of RCV, but the material following did address many of these concerns. Some additional concerns that they have regarding the value of RCV were listed (1) and will be addressed in this response. i. We agree that, for some quantities (e.g., those related to spinal fluid, arterial blood and the neonatal period), it may be challenging to define the within-subject biological variation. We believe, however, that these difficulties should be overcome by careful selection of reference individuals, and have pointed to recent studies on monoclonal proteins in stable patients (4), glycated haemoglobin in children (5) and arterial gases and electrolytes in intensive care (6) as good examples. The identification of appropriate reference populations does require flair and imagination, and we encourage further insightful efforts. ii. Fuentes-Arderiu et al. (1) state that data on biological variation of quantities obtained with different immunochemical measuring systems should not be pooled. We totally agree. The problem here is not that the studies done *Corresponding author: Professor Callum G. Fraser, PhD, Centre for Research into Cancer Prevention and Screening, University of Dundee Ninewells Hospital and Medical School, Dundee DD1 9SY, Scotland, UK Phone: +44 1382553799, Fax: +44 1382425679, E-mail:
[email protected] Received November 28, 2011; accepted November 28, 2011; previously published online February 10, 2012
are in any way suspect, it is because the quantity being examined is not defined well enough and, in consequence, dissimilar are being regarded as a single entity. For example, if cardiac troponin was being studied, we believe that it is totally unsatisfactory to just state, for example, cardiac troponin I, since there are several methods available that use a different cocktail of antibodies and therefore measure quantities that really do differ, although they are referred to with a single name throughout laboratory medicine (7). This problem can be solved if any data generated on biological variation was clearly accompanied by name of manufacturer as well as test method and date, since methods change with time also. Unlike most current practice, laboratories should also ensure that the names of all quantities examined are sufficiently detailed to guarantee that comparison of data over time and geography are not compromised by using the same name for what are actually different quantities. iii. Regarding the calculation of RCV, it must be borne in mind that, for very many quantity examinations, the use of modern methodology and technology means that the analytical imprecision, irrespective whether it varies with the value of the quantity or not, is actually insignificant especially when compared with the uncertainty arising from pre-analytical variability (8). Once the analytical imprecision is a fraction of the within-subject biological variation, then changes in imprecision do not affect the magnitude of the RCV to a significant extent (9). iv. For RCV, in any case, each laboratory should use its own analytical imprecision, derived from in-house quality control or, better, duplicate analyses of samples from patients, to calculate the RCV and this should be done at medically significant concentrations or activities, minimising any adverse effect of heteroscedasticity. v. Of course, the within-subject biological variation differs between individuals and there is bound to be inherent heterogeneity of estimates done on small numbers of samples from individuals. The significance of this can be examined using the “index of heterogeneity of within-subject biological variation” (10). However, we consider that there is much evidence that estimates of the within-subject biological variation represent a quantitation of the magnitude of homeostatic mechanisms in a single species, Homo sapiens, and therefore is assumed to be constant (9). The evidence is that this generally holds, even in chronic but stable disease (11), since estimates are similar to those in healthy subjects (12). Lack of agreement
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Fraser et al.: Reference change values are invaluable tools
in published studies of within-subject biological variation may be due to lack of rigour in the design and execution of some experiments done on biological variation as well as to technological heterogeneity: we concur with Bartlett’s proposal seeking a careful critical appraisal of the existing data (13). We too are convinced that the interpretation of a difference between serial results in an individual is very important information that should be included in clinical laboratory reports, as some of us have done for several years (9, 14). We believe that RCV currently provides a simple and effective means of generating the data needed that all laboratories can use. However, we would advocate that these need to be better used taking both the probability appropriate for decisionmaking and the assessment of whether the clinical decision is actually change (two-sided) or rise or fall (one-sided) into account (15). Finally, we do accept that there are some disadvantages and join with Fuentes-Arderiu et al. (1) in encouraging development of new approaches: yet again, we also encourage the generation and application of good quality data on biological variation of as yet unstudied quantities.
Conflict of interest statement Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article. Research funding: None declared. Employment or leadership: None declared. Honorarium: None declared.
References 1. Fuentes-Arderiu X, Padró-Miquel A, Rigo-Bonnin R. Disadvantages of using biological variation data for reference change values. Clin Chem Lab Med 2012;50:961. 2. Fraser CG. Reference change values. Clin Chem Lab Med 2012;50:807–12. 3. 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.
4. Katzmann JA, Snyder MR, Rajkumar SV, Kyle RA, Therneau TM, Benson JT, et al. The long-term biologic variation of serum protein electrophoresis M-spike, urine M-spike, and monoclonal serum free light chain quantitation: implications for monitoring monoclonal gammopathies. Clin Chem 2011;57:1689–92. 5. Desmeules P, Cousineau J, Allard P. Biological variation of glycated haemoglobin in a paediatric population and its application to calculation of significant change between results. Ann Clin Biochem 2010;47:35–8. 6. Cembrowski GS, Tran DV, Higgins TN. The use of serial patient blood gas, electrolyte and glucose results to derive biologic variation: a new tool to assess the acceptability of intensive care unit testing. Clin Chem Lab Med 2010;48:1447–54. 7. Lippi G, Avanzini P, Dipalo M, Aloe R, Cervellin G. Influence of hemolysis on troponin testing: studies on Beckman Coulter UniCel Dxl 800 Accu-TnI and overview of the literature. Clin Chem Lab Med 2011;49:2097–100. 8. Lippi G, Chance JJ, Church S, Dazzi P, Fontana R, Giavarina D, et al. Preanalytical quality improvement: from dream to reality. Clin Chem Lab Med 2011;49:1113–26. 9. Fraser CG. Biological variation: from principles to practice. Washington, DC: AACC Press, 2001. 10. Fraser CG, Harris EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Clin Lab Sci 1989;27:409–37. 11. Ricos C, Iglesias N, Garcıa-Lario J-V, Simon M, Cava F, Hernandez A, et al. Within-subject biological variation in disease: collated data and clinical consequences. Ann Clin Biochem 2007:44:343–52. See http://www. westgard.com/biological-variation-in-patients-with-disease.htm. Accessed 24 Nov 2011. 12. Ricos C, Garcıa-Lario J-V, Alvares V, Cava F, Domenech M, Hernandez A, et al. Biological variation database, and quality specifications for imprecision, bias and total error (desirable and minimum). The 2010 update. Westgard QC. http://www.westgard.com/biodatabase-2010-update.htm. Accessed 24 Nov 2011. 13. Bartlett B. Biological variation data: the need for appraisal of the evidence base. Presented at the IFCC-WorldLab-EuroMedLab Berlin 2011. May 18, 2011, Berlin, Germany. http://biologicalvariation.com/ESW/Files/BERLIN_final_2011PD.pdf. Accessed 24 Nov 2011. 14. Plebani M. What information on quality specifications should be communicated to clinicians, and how? Clin Chim Acta 2004;346:25–35. 15. Fraser CG. Improved monitoring of differences in serial laboratory results. Clin Chem 2011;57:1635–7.
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