Helicobacter pylori infection prevalence in ambulatory settings in 2017-2019 in RUSSIA: The data of real-world national multicenter trial.

BACKGROUND: The recent data on the prevalence of Helicobacter pylori (H. pylori) infection in Russia are limited. The aim of the study was to compare Helicobacter pylori infection prevalence in ambulatory settings in Russia in 2017 and 2019 years. MATERIALS AND METHODS: Subjects visiting primary care centers were invited to take part in the study. H. pylori status was assessed by 13 C-urea breath test (UBT). Data on subjects' demography, previous treatment exposure, and place of residence were collected in all federal districts of Russia in 2017 and in 2019 calendar years and processed centrally. RESULTS: The data of 19,875 subjects were available for analysis. The prevalence of H. pylori infection assessed by positive UBT in treatment-naive subjects was highest in the Southern (54.9%) and the North Caucasian (45.1%) federal districts. A significant difference (p < 0.05) in H. pylori prevalence between two testing periods was found only in a half of federal districts: the Central (46.2% in 2017 vs. 36.2% in 2019), the Northwestern (38.6% vs. 35.5% accordingly), the Volga (40.6% vs. 33.0%, accordingly), and the Ural (40.4% vs. 32.7%, accordingly). The lowest prevalence of H. pylori infection was revealed in the age group <18 years old (20.2%), while the highest in the age group of 41-50 years old (43.9%). In 2017, the prevalence of H. pylori was significantly (p < 0.05) higher than in 2019 in all age groups but younger than 18 and older than 70 y.o., where similar rates were found during both study periods. CONCLUSIONS: The prevalence of H. pylori according to 13 C-UBT testing of primary care visitors in Russia is lower than expected (38.8%). The highest prevalence of H. pylori infection found in the Southern and the North Caucasian federal districts of Russia and in the age group of 41-50 years old. This study was registered at clinicaltrials.gov (NCT04892238).

Sources of variation and establishment of Russian reference intervals for major hormones and tumor markers.

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.

Establishing reference intervals for major biochemical analytes for the Russian population: a research conducted as a part of the IFCC global study on reference values.

OBJECTIVES: Because reference intervals (RIs) for biochemistry analytes matched to the Russian population are not well defined, we joined the global study on reference values (RVs) coordinated by the IFCC Committee on Reference Intervals and Decision Limits (C-RIDL). METHODS: According to the C-RIDL harmonized protocol, 793 healthy volunteers were recruited in Saint-Petersburg, Moscow, and Yekaterinburg. Serum samples were tested for 34 biochemistry analytes. Sources of variation of RVs were explored using multiple regression analysis. The need for partitioning RVs by sex and age were judged using standard deviation ratio based on ANOVA. Latent abnormal values exclusion (LAVE) method was applied to reduce the influence of individuals with metabolic syndrome and/or inappropriate sampling conditions. RIs were computed by the parametric method. RESULTS: No appreciable between-city differences were observed. Partition of RVs by sex was required for 17 analytes. Age-related changes in RVs were observed in many analytes, especially in females. The trend was exaggerated in nutritional and inflammatory markers that were closely associated with body mass index (BMI), because BMI increases prominently with age. Therefore, for those analytes, volunteers with BMI > 28 kg/m2 were excluded in determining RIs for age-specific RIs. The LAVE method was effective in lowering the upper limits of the RIs for nutritional and inflammatory markers. CONCLUSION: RIs matched to the Russian population were established for 34 biochemical analytes using up-to-date methods in detailed consideration of sources of variation of RVs. The majority of Russian RIs are similar to those of Caucasian populations among the participating countries.