1.Development of a normative model for quadruple markers in mongolian women during the second trimester
Azjargal Batdorj ; Urjindelger Tserensambuu ; Erdenetuya Ganbaatar ; Gerelmaa Nansal ; Munkhtsetseg Janlav
Diagnosis 2025;114(3):98-103
Background:
Down syndrome (DS) is a chromosomal disorder and a leading cause of intellectual and physical developmental delay in children. In Mongolia, there is no current national guideline recommending
the use of the quadruple biomarker test for prenatal screening of DS. Instead, triple marker testing during the second trimester remains standard practice. However, the quadruple test offers higher specificity and sensitivity. Therefore, this study was conducted to determine gestational age
specific normative values for the quadruple markers, adjusted for ethnic characteristics. Currently, multiple of the median (MoM) values for Mongolian women are calculated using reference medians derived from Caucasian populations. This study aims to establish population-specific reference values for Mongolian women.
Objective:
To determine the normative serum levels of second-trimester quadruple biomarkers — alpha-fetoprotein (AFP), free beta-subunit of human chorionic gonadotropin (β-hCG), unconjugated estriol (uE3), and inhibin A (Inh-A) — in Mongolian pregnant women. Methods: A retrospective study was conducted involving pregnant women between 14 and 21 weeks of gestation. The concentrations of each biomarker were analyzed using multivariable quantile regression models, adjusting for gestational age and maternal weight. Results: MoM values calculated using the Mongolian model differed significantly from those based on the Caucasian model (Wilcoxon signed-rank test; p < 0.001). Specifically, the concentrations and MoM values for AFP and uE3 were significantly lower, while those for β-hCG and Inh-A were notably higher in the Mongolian cohort.
Conclusion
The serum levels of β-hCG and Inh-A were significantly elevated in Mongolian pregnant women compared to the ethnicity-adjusted Caucasian reference model, highlighting the importance of using population-specific normative data for accurate prenatal screening.
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