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Determination of reference intervals for 26 commonly measured biochemical analytes with consideration of long-term within-individual variation
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Akemi Matsubara
Published/Copyright:
May 1, 2008
Abstract
Background: A reference interval (RI) is usually derived from a data set obtained cross-sectionally without consideration of the long-term analytical coefficient of variation (CV) (CVA) or within-individual CV (CVI).
Methods: A total of 135 healthy volunteers, 22–59 years of age, working in eight clinical laboratories in Japan participated in a study to determine RIs for 26 commonly measured biochemical analytes. Blood samples were collected monthly for 1 year and measured in each laboratory. Common quality control (QC) specimens were measured monthly. RIs were derived parametrically using a modified Box-Cox power transformation method. Subjects with abnormal results for test items other than the one for derivation were excluded.
Results: Although there was no statistically significant between-month variation, unacceptably large between-laboratory differences were observed in QC test results. Thus, all values were transformed to those of the main laboratory based on cross-check test results. CVI values computed by two-level nested analysis of variance were generally greater than those commonly cited in the literature. Average RIs derived from the monthly results agreed well with those derived from the entire results. However, CVs of lower and upper limits of the monthly RIs were greater than CVA.
Conclusions: To derive reliable RIs, it is important to consider long-term variability of CVI and CVA.
Clin Chem Lab Med 2008;46:691–8.
Keywords: analytical variation; between-individual variation; bootstrap method; latent abnormal values exclusion method; within-individual variation
Received: 2007-11-27
Accepted: 2008-1-31
Published Online: 2008-05-01
Published in Print: 2008-05-01
©2008 by Walter de Gruyter Berlin New York
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Keywords for this article
analytical variation;
between-individual variation;
bootstrap method;
latent abnormal values exclusion method;
within-individual variation
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