Browsing by Author "Klee, George"
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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 A global multicenter study on reference values: 1. Assessment of methods for derivation and comparison of reference intervals(Elsevier, 2017-04) Ichihara, Kiyoshi; Barth, Julian H; Klee, George; Qiu, Ling; Erasmus, Rajiv Rajiv; Borai, Anwar; Evgina, Svetlana; Ashavaid, Tester; Khan, Dilshad; Schreier, Laura; Rolle, Reynan; Shimizu, Yoshihisa; Kimura, Shogo; Kawano, Reo; Armbruster, David; Mori, Kazuo; Yadav, Binod Binod; Özarda, Ozarda, Yesim Yesim; Uludağ Üniversitesi/Tıp Fakültesi/Biyokimya Anabilim Dalı.; AAL-8873-2021; 35741320500Objectives: The IFCC Committee on Reference Intervals and Decision Limits coordinated a global multicenter study on reference values (RVs) to explore rational and harmonizable procedures for derivation of reference intervals (Rls) and investigate the feasibility of sharing RIs through evaluation of sources of variation of RVs on a global scale. Methods: For the common protocol, rather lenient criteria for reference individuals were adopted to facilitate harmonized recruitment with planned use of the latent abnormal values exclusion (LAVE) method. As of July 2015, 12 countries had completed their study with total recruitment of 13,386 healthy adults. 25 analytes were measured chemically and 25 immunologically. A serum panel with assigned values was measured by all laboratories. Rls were derived by parametric and nonparametric methods. Results: The effect of LAVE methods is prominent in analytes which reflect nutritional status, inflammation and muscular exertion, indicating that inappropriate results are frequent in any country. The validity of the parametric method was confirmed by the presence of analyte-specific distribution patterns and successful Gaussian transformation using the modified Box-Cox formula in all countries. After successful alignment of RVs based on the panel test results, nearly half the analytes showed variable degrees of between-country differences. This finding, however, requires confirmation after adjusting for BMI and other sources of variation. The results are reported in the second part of this paper. Conclusion: The collaborative study enabled us to evaluate rational methods for deriving Rls and comparing the RVs based on real-world datasets obtained in a harmonized manner.Item Protocol and standard operating procedures for common use in a worldwide multicenter study on reference values(Walter De Gruyter Gmbh, 2013-05) Ichihara, Kiyoshi; Barth, Julian H.; Klee, George; Özarda, Yeşim; Uludağ Üniversitesi/Tıp Fakültesi/Biyokimya Anabilim Dalı.; AAL-8873-2021; 35741320500The reference intervals (RIs) given in laboratory reports have an important role in aiding clinicians in interpreting test results in reference to values of healthy populations. In this report, we present a proposed protocol and standard operating procedures (SOPs) for common use in conducting multicenter RI studies on a national or international scale. The protocols and consensus on their contents were refined through discussions in recent C-RIDL meetings. The protocol describes in detail (1) the scheme and organization of the study, (2) the target population, inclusion/exclusion criteria, ethnicity, and sample size, (3) health status questionnaire, (4) target analytes, (5) blood collection, (6) sample processing and storage, (7) assays, (8) cross-check testing, (9) ethics, (10) data analyses, and (11) reporting of results. In addition, the protocol proposes the common measurement of a panel of sera when no standard materials exist for harmonization of test results. It also describes the requirements of the central laboratory, including the method of cross-check testing between the central laboratory of each country and local laboratories. This protocol and the SOPs remain largely exploratory and may require a reevaluation from the practical point of view after their implementation in the ongoing worldwide study. The paper is mainly intended to be a basis for discussion in the scientific community.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.