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Original Article
- Reliability of Quadruplicated Serological Parameters in the Korean Genome and Epidemiology Study
- Jae Jeong Yang, Ji Hyun Yang, Jimin Kim, Lisa Y. Cho, Boyoung Park, Seung Hyun Ma, Sang Hoon Song, Won-Ki Min, Sung Soo Kim, Man Suck Park, Sue K. Park
- Epidemiol Health. 2011;33:e2011004. Published online May 19, 2011
- DOI: https://doi.org/10.4178/epih/e2011004
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Abstract
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Abstract<sec><title>OBJECTIVES</title><p>The aim of this study was to evaluate whether clinical test values from different laboratories in the Korean Genome and Epidemiology Study (KoGES) can be integrated through a statistical adjustment algorithm with appropriate intra- and inter-laboratory reliability.</p></sec><sec><title>METHODS</title><p>External quality control data were obtained from the Korean Society for Laboratory Medicine and quadruplicated standardized serological samples (N=3,200) were manufactured in order to check the intra- and inter-laboratory reliability for aspartic acid transaminase (AST), alanine transaminase (ALT), gamma-glutamyl transpeptidase (γ-GTP), blood urea nitrogen (BUN), creatinine, uric acid (UA), fasting blood sugar (FBS), cholesterol, and triglyceride (TG). As an index of inter- and intra-rater reliability, Pearson's correlation coefficient, intraclass correlation coefficients and kappa statistics were estimated. In addition, to detect the potential for data integration, we constructed statistical compensation models using linear regression analysis with residual analysis, and presented the R-square values.</p></sec><sec><title>RESULTS</title><p>All correlation coefficient values indicated good intra- and inter-laboratory reliability, which ranged from 0.842 to 1.000. Kappa coefficients were greater than 0.75 (0.75-1.00). All of the regression models based on the trial results had strong R-square values and zero sums of residuals. These results were consistent in the regression models using external quality control data.</p></sec><sec><title>CONCLUSION</title><p>The two laboratories in the KoGES have good intra- and inter-laboratory reliability for ten chemical test values, and data can be integrated through algorithmic statistical adjustment using regression equations.</p></sec>
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Citations
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