Utility of a panel of sera for the alignment of test results in the worldwide multicenter study on reference values

Kiyoshi Ichihara, Yesim Ozarda, George Klee, Joely Straseski, Nikola Baumann, Kiyohide Ishikura

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Background: In a planned International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) worldwide study on reference intervals (RIs), a common panel of serum samples is to be measured by laboratories from different countries, and test results are to be compared through conversion using linear regression analysis. This report presents a validation study that was conducted in collaboration with four laboratories. Methods: A panel composed of 80 sera was prepared from healthy individuals, and 45 commonly tested analytes (general chemistry, tumor markers, and hormones) were measured on two occasions 1 week apart in each laboratory. Reduced major-axis linear regression was used to convert reference limits ( LL and UL ). Precision was expressed as a ratio of the standard error of converted LL or UL to the standard deviation (SD) comprising RI (approx. 1/4 of the RI width corresponding to between-individual SD). The allowable and optimal levels of error for the SD ratio (SDR) were set as . 0.250 and . 0.125, respectively, in analogy to the common method of setting limits for analytical bias based on between-individual SD. Results: The values for the calculated SDRs depended upon the distribution patterns of test results: skewness toward higher values makes SDR LL lower and SDR UL higher. However, the CV of the regression line slope, CV( b ), is less affected by skewness. The average of SDR LL and SDR UL (aveSDR) correlates closely with CV( b ) (r = 0.995). The aveSDRs of . 0.25 and . 0.125 corresponds approximately to CV( b ) values of . 11% and . 5.5%, respectively. For all results (i.e., n = 80), conversion was allowable (optimal) in 98% (89%) of the analytes, as judged by CV( b ). Resampling studies using random subsets of data with a data size (n) of 70 to 20 revealed that SDRs and CV( b ) gradually increase with reduction of n, especially with n . 30. Conclusions: CV( b ) is a robust estimator for judging the convertibility of reference values among laboratories, even with a skewed distribution. Assuming 40 sera to be a practical size for the panel, reference values of 89% (80%) of analytes examined were made comparable by regression analysis with the allowable (optimal) level of precision.

Original languageEnglish (US)
Pages (from-to)1007-1025
Number of pages19
JournalClinical Chemistry and Laboratory Medicine
Volume51
Issue number5
DOIs
StatePublished - May 2013

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Multicenter Studies
Reference Values
Serum
Linear regression
Regression analysis
Clinical laboratories
Linear Models
Regression Analysis
Tumor Biomarkers
Clinical Chemistry
Validation Studies
Medicine
Hormones

Keywords

  • Method comparison
  • Multicenter study
  • Panel of sera
  • Reduced major-axis regression
  • Reference interval

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Biochemistry, medical

Cite this

Utility of a panel of sera for the alignment of test results in the worldwide multicenter study on reference values. / Ichihara, Kiyoshi; Ozarda, Yesim; Klee, George; Straseski, Joely; Baumann, Nikola; Ishikura, Kiyohide.

In: Clinical Chemistry and Laboratory Medicine, Vol. 51, No. 5, 05.2013, p. 1007-1025.

Research output: Contribution to journalArticle

Ichihara, Kiyoshi ; Ozarda, Yesim ; Klee, George ; Straseski, Joely ; Baumann, Nikola ; Ishikura, Kiyohide. / Utility of a panel of sera for the alignment of test results in the worldwide multicenter study on reference values. In: Clinical Chemistry and Laboratory Medicine. 2013 ; Vol. 51, No. 5. pp. 1007-1025.
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AU - Baumann, Nikola

AU - Ishikura, Kiyohide

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N2 - Background: In a planned International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) worldwide study on reference intervals (RIs), a common panel of serum samples is to be measured by laboratories from different countries, and test results are to be compared through conversion using linear regression analysis. This report presents a validation study that was conducted in collaboration with four laboratories. Methods: A panel composed of 80 sera was prepared from healthy individuals, and 45 commonly tested analytes (general chemistry, tumor markers, and hormones) were measured on two occasions 1 week apart in each laboratory. Reduced major-axis linear regression was used to convert reference limits ( LL and UL ). Precision was expressed as a ratio of the standard error of converted LL or UL to the standard deviation (SD) comprising RI (approx. 1/4 of the RI width corresponding to between-individual SD). The allowable and optimal levels of error for the SD ratio (SDR) were set as . 0.250 and . 0.125, respectively, in analogy to the common method of setting limits for analytical bias based on between-individual SD. Results: The values for the calculated SDRs depended upon the distribution patterns of test results: skewness toward higher values makes SDR LL lower and SDR UL higher. However, the CV of the regression line slope, CV( b ), is less affected by skewness. The average of SDR LL and SDR UL (aveSDR) correlates closely with CV( b ) (r = 0.995). The aveSDRs of . 0.25 and . 0.125 corresponds approximately to CV( b ) values of . 11% and . 5.5%, respectively. For all results (i.e., n = 80), conversion was allowable (optimal) in 98% (89%) of the analytes, as judged by CV( b ). Resampling studies using random subsets of data with a data size (n) of 70 to 20 revealed that SDRs and CV( b ) gradually increase with reduction of n, especially with n . 30. Conclusions: CV( b ) is a robust estimator for judging the convertibility of reference values among laboratories, even with a skewed distribution. Assuming 40 sera to be a practical size for the panel, reference values of 89% (80%) of analytes examined were made comparable by regression analysis with the allowable (optimal) level of precision.

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