Browsing by Author "Straseski, Joely"
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Item A global multicenter study on reference values: 2. Exploration of sources of variation across the countries(Elsevier, 2017-04) Ichihara, Kiyoshi; Barth, Julian H; Klee, George; Shimizu, Yoshihisa; Xia, Liangyu; Hoffmann, Mariza; Shah, Swarup; Matsha, Tandi; Wassung, Janette; Smit, Francois; Ruzhanskaya, Anna; Straseski, Joely; Bustos, Daniel N; Kimura, Shogo; Takahashi, Aki; Özarda, Yeşim; Uludağ Üniversitesi/Tıp Fakültesi/Tıbbi Biyokimya Anabilim Dalı.; AAL-8873-2021; 35741320500Objectives: The intent of this study, based on a global multicenter study of reference values (RVs) for serum analytes was to explore biological sources of variation (SVs) of the RVs among 12 countries around the world. Methods: As described in the first part of this paper, RVs of 50 major serum analytes from 13,396 healthy individuals living in 12 countries were obtained. Analyzed in this study were 23 clinical chemistry analytes and 8 analytes measured by immunoturbidimetry. Multiple regression analysis was performed for each gender, country by country, analyte by analyte, by setting four major SVs (age, BMI, and levels of drinking and smoking) as a fixed set of explanatory variables. For analytes with skewed distributions, log-transformation was applied. The association of each source of variation with RVs was expressed as the partial correlation coefficient (rp). Results: Obvious gender and age-related changes in the RVs were observed in many analytes, almost consistently between countries. Compilation of age-related variations of RVs after adjusting for between-country differences revealed peculiar patterns specific to each analyte. Judged from the rp, BMI related changes were observed for many nutritional and inflammatory markers in almost all countries. However, the slope of linear regression of BMI vs. RV differed greatly among countries for some analytes. Alcohol and smoking-related changes were observed less conspicuously in a limited number of analytes. Conclusion: The features of sex, age, alcohol, and smoking-related changes in RVs of the analytes were largely comparable worldwide. The finding of differences in BMI-related changes among countries in some analytes is quite relevant to understanding ethnic differences in susceptibility to nutritionally related diseases.Item Utility of a panel of sera for the alignment of test results in the worldwide multicenter study on reference values(Walter De Gruyter GMBH, 2013-05) Ichihara, Kiyoshi; Klee, George; Straseski, Joely; Baumann, Nikola; Ishikura, Kiyohide; Özarda, Yeşim; Uludağ Üniversitesi/Tıp Fakültesi/Biyokimya Anabilim Dalı.; AAL-8873-2021; 35741320500Background: 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 SDRLL lower and SDRUL higher. However, the CV of the regression line slope, CV(b), is less affected by skewness. The average of SDRLL and SDRUL (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.