OBJECTIVES: A multicenter study was organized to explore sources of variation (SVs) of reference values (RVs) for 22 major immunochemistry analytes and to determine reference intervals (RIs) for the Russian population. METHODS: According to IFCC Committee on Reference Intervals and Decision Limits (C-RIDL) protocol, 758 healthy volunteers were recruited in St. Petersburg, Moscow, and Yekaterinburg. Serum samples were tested for five tumor markers, 17 hormones and related tests by Beckman Coulter's UniCel DxI 800 immunochemistry analyzer. SVs were explored using multiple regression analysis and ANOVA. Standard deviation ratio (SDR) of 0.4 was used as primary guide for partitioning RIs by gender and age. RESULTS: SDR for between-city difference was <0.4 for all analytes. Secondary exclusion of individuals was done under the following conditions: for female sex-hormones, those with contraceptives (8%); for CA19-9, those supposed to have negative Lewis blood-group (10.5% males and 11.3% females); for insulin, those with BMI≥28 kg/m2 (31%); for the thyroid panel, those with anti-thyroid antibodies (10.3% males; 24.5% females), for CEA those with smoking habit (30% males and 16% females). Gender-specific RIs were required for all analytes except CA19-9, CA15-3, thyroid-related tests, parathyroid hormone, and insulin. Age-specific RIs were required for alpha-fetoprotein, CEA, all sex-hormones for females, FSH and progesterone for both sexes. RIs were generally derived by parametric method after Gaussian transformation using modified Box-Cox formula. Exceptions were growth hormone, estradiol for females in postmenopause, and progesterone for females in premenopause, for which nonparametric method was required due to bimodal distribution and/or insufficient detection limit. CONCLUSION: RIs for major hormones and tumor markers specific for the Russian population were derived based on the up-to-date internationally harmonized protocol by careful consideration of analyte-specific SVs.
OBJECTIVES: A multicenter study was organized to explore sources of variation (SVs) of reference values (RVs) for 22 major immunochemistry analytes and to determine reference intervals (RIs) for the Russian population. METHODS: According to IFCC Committee on Reference Intervals and Decision Limits (C-RIDL) protocol, 758 healthy volunteers were recruited in St. Petersburg, Moscow, and Yekaterinburg. Serum samples were tested for five tumor markers, 17 hormones and related tests by Beckman Coulter's UniCel DxI 800 immunochemistry analyzer. SVs were explored using multiple regression analysis and ANOVA. Standard deviation ratio (SDR) of 0.4 was used as primary guide for partitioning RIs by gender and age. RESULTS: SDR for between-city difference was <0.4 for all analytes. Secondary exclusion of individuals was done under the following conditions: for female sex-hormones, those with contraceptives (8%); for CA19-9, those supposed to have negative Lewis blood-group (10.5% males and 11.3% females); for insulin, those with BMI≥28 kg/m2 (31%); for the thyroid panel, those with anti-thyroid antibodies (10.3% males; 24.5% females), for CEA those with smoking habit (30% males and 16% females). Gender-specific RIs were required for all analytes except CA19-9, CA15-3, thyroid-related tests, parathyroid hormone, and insulin. Age-specific RIs were required for alpha-fetoprotein, CEA, all sex-hormones for females, FSH and progesterone for both sexes. RIs were generally derived by parametric method after Gaussian transformation using modified Box-Cox formula. Exceptions were growth hormone, estradiol for females in postmenopause, and progesterone for females in premenopause, for which nonparametric method was required due to bimodal distribution and/or insufficient detection limit. CONCLUSION: RIs for major hormones and tumor markers specific for the Russian population were derived based on the up-to-date internationally harmonized protocol by careful consideration of analyte-specific SVs.
Authors: E M Camacho; I T Huhtaniemi; T W O'Neill; J D Finn; S R Pye; D M Lee; A Tajar; G Bartfai; S Boonen; F F Casanueva; G Forti; A Giwercman; T S Han; K Kula; B Keevil; M E Lean; N Pendleton; M Punab; D Vanderschueren; F C W Wu Journal: Eur J Endocrinol Date: 2013-02-20 Impact factor: 6.664
Authors: Kiyoshi Ichihara; Yoshihisa Itoh; Christopher W K Lam; Priscilla M K Poon; Jeong-Ho Kim; Hiroshi Kyono; Naning Chandrawening; Dewi Muliaty Journal: Clin Chem Date: 2007-12-18 Impact factor: 8.327
Authors: Thomas W Kelsey; Lucy Q Li; Rod T Mitchell; Ashley Whelan; Richard A Anderson; W Hamish B Wallace Journal: PLoS One Date: 2014-10-08 Impact factor: 3.240