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Clinical Chemistry 50: 907-914, 2004. First published March 11, 2004; 10.1373/clinchem.2003.023770
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(Clinical Chemistry. 2004;50:907-914.)
© 2004 American Association for Clinical Chemistry, Inc.

Laboratory Management

Centile Charts II: Alternative Nonparametric Approach for Establishing Time-Specific Reference Centiles and Assessment of the Sample Size Required

Jenny K. Griffiths1, Terence C. Iles2,a, Martin Koduah2 and Arthur B.J. Nix1

1 Department of Epidemiology, Statistics and Public Health, University of Wales College of Medicine, Heath Park, Cardiff, United Kingdom.2 School of Mathematics, Cardiff University, Senghennydd Road, PO Box 926, Cardiff CF24 4YH, United Kingdom.

aAuthor for correspondence. Fax 44-29-2087-4199; e-mail iles{at}cardiff.ac.uk.

Background: Reference intervals, and more generally centile estimates, are used to characterize a reference population for the purposes of interpreting an individual patient’s clinical measurement. We describe methods of calculating reference intervals where these centiles vary with a covariate, usually age or time.

Methods: The US Food and Drug Administration and the IFCC have made recommendations on two approaches: the parametric approach, which models the structural characteristics of the data set with a theoretical distribution, and the nonparametric approach, which makes no particular assumption about this structure. In this report we propose a nonparametric procedure that relies on the principles of regression and show how sample size determination can be assessed. We also show how the sample size calculation is influenced by the distribution of the times measured.

Results: We illustrated our method on three data sets and compared the results for our proposed nonparametric method with parametric estimates. We showed that the bias is reduced and that the nonparametric method is less likely to produce fluctuating profiles.

Conclusions: To achieve adequate precision the sample size needs to be larger than 120, as has often been recommended. If there is doubt about the parametric model, then threshold sample sizes may need to be as high as 500.






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Copyright © 2004 by the American Association for Clinical Chemistry.