[en] As a cornerstone of quality management in the laboratory, External Quality Assessment (EQA) schemes are used to assess laboratory and analytical method performance. The characteristic function is used to describe the relation between the target concentration and the EQA standard deviation, which is an essential part of the evaluation process. The characteristic function is also used to compare the variability of different analytical methods.
We fitted the characteristic function to data from the Belgian External Quality Assessment program for serum ethanol. Data included results from headspace gas chromatography and the enzymatic methods of Abbott, Roche, Siemens, and Ortho-Clinical Diagnostics. We estimated the characteristic function with weighted nonlinear regression. By introducing dummy variables, we rewrote the original formula of the characteristic function to assess statistical inference for comparing the variability of the different analytical methods.
The characteristic function fitted the data precisely. Comparison between methods showed that there was little difference between the estimated variability for low concentrations, and that the increase in SD with increasing target concentration was slower for Abbott and Roche than for the other methods.
The characteristic function can successfully be introduced in clinical schemes, although its applicability to fit the data should always be assessed. Because of its easy parameterization, it can be used to assess differences in performance between analytical methods and to assess laboratory performance. The characteristic function also offers an alternative framework for coefficients of variation to describe variability of analytical methods.
Disciplines :
Pharmacy, pharmacology & toxicology
Author, co-author :
Coucke, Wim; Université Catholique de Louvain - UCL
Charlier, Corinne ; Université de Liège > Département de pharmacie > Chimie toxicologique
Lambert, Willy
Martens, Frank; Radboud Universiteit Nijmegen
Neels, Hugo; Universiteit Antwerpen - UA
Tytgat, Jan; Katholieke Universiteit Leuven - KUL
Van de Walle, Philippe
Vanescote, André
Wallemacq, Pierre; Université Catholique de Louvain - UCL
Wille, Sarah
Verstraete, Alain G; Universiteit Gent - Ugent
Language :
English
Title :
Application of the characteristic function to evaluate and compare analytical variability in an external quality assessment scheme for serum ethanol
Publication date :
July 2015
Journal title :
Clinical Chemistry
ISSN :
0009-9147
eISSN :
1530-8561
Publisher :
American Association for Clinical Chemistry, Washington, United States - District of Columbia
Thompson M. The characteristic function, a method-specific alternative to the Horwitz function. J AOAC Int 2012;95:1803-6.
International Organization for Standardization. ISO 17043. Conformity assessment: general requirements for proficiency testing. Geneva: ISO; 2010.
Horwitz W, Britton P, Chirtel SJ. A simple method for evaluating data from an interlaboratory study. J AOAC Int 1998;81:1257-65.
International Organization for Standardization. ISO 13528:2005. Statistical methods for use in proficiency testing by interlaboratory comparisons. Geneva: ISO;2005.
Whitehead T, Woodford F. External quality assessment of clinical laboratories in the United Kingdom. J Clin Pathol 1981;34:947-57.
Ehrmeyer S, Laessig R. Alternative statistical approach to evaluating interlaboratory performance. Clin Chem 1985;31:106-8.
Meijer P, de Maat MPM, Kluft C, Haverkate F, van Houwelingen HC. Long-term analytical performance of hemostasis field methods as assessed by evaluation of the results of an external quality assessment program for antithrombin. Clin Chem 2002;48:1011-5.
Coucke W, Van Blerk M, Libeer JC, Van Campenhout C, Albert A. A new statistical method for evaluating long-term analytical performance of laboratories applied to an external quality assessment scheme for flow cytometry. Clin Chem Lab Med 2010;48:645-50.
Kallner A, Khorovskaya L, Pettersson T. A method to estimate the uncertainty of measurements in a conglomerate of instruments/laboratories. Scand J Clin Lab Invest 2005;65:551-8.
Koch M, Magnusson B. Use of characteristic functions derived from proficiency testing data to evaluate measurement uncertainties. Accreditation Qual Assur 2012;17:399-403.
Duewer DL, Brown Thomas J, Kline MC, MacCrehan WA, Schaffer R, Sharpless KE, et al. NIST/NCI Micronutrients Measurement Quality Assurance Program: measurement repeatabilities and reproducibilities for fat-soluble vitamin-related compounds in human sera. Anal Chem 1997;69:1406-13.
Thompson M, Wood R. Using uncertainty functions to predict and specify the performance of analytical methods. Accreditation Qual Assur 2006;10:471-8.
Rozet E, Marini RD, Ziemons E, Hubert P, Dewé W, Rudaz S, et al. Total error and uncertainty: friends or foes? TrAC Trends Anal Chem 2011;30:797-806.
Thompson M, Mathieson K, Damant AP, Wood R. A general model for interlaboratory precision accounts for statistics from proficiency testing in food analysis. Accreditation Qual Assur 2008;13:223-30.
Jiménez-Chacón J, Alvarez-Prieto M. Modelling uncertainty in a concentration range. Accreditation Qual Assur 2009;14:15-27.
Côté I, Robouch P, Robouch B, Bisson D, Gamache P, LeBlanc A, et al. Determination of the standard deviation for proficiency assessment from past participant's performances. Accreditation Qual Assur 2012;17:389-93.
Rousseeuw PJ, Croux C. Alternatives to the median absolute deviation. J Am Stat Assoc 1993;88:1273-83.
Wilrich P-T. Robust estimates of the theoretical standard deviation to be used in interlaboratory precision experiments. Accreditation Qual Assur 2007;12:231-40.
Spang HA. A review of minimization techniques for nonlinear functions. SIAM Rev 1962;4:343-65.
Cleveland WS, Devlin SJ. Locally weighted regression: an approach to regression analysis by local fitting. J Am Stat Assoc 1988;83:596-610.
Coucke W, China B, Delattre I, Lenga Y, Van Blerk M, Van Campenhout C, et al. Comparison of different approaches to evaluate External Quality Assessment data. Clin Chim Acta 2012;413:582-6.