Authors
Mengxi Guo, Zhengquan Wang, Xin Chang, Xinxin Ren, Manman Zhang, Yu Tao, Hong Pan, Ningling Wang, Ying Guo, Haixia Ding, Yu Xiao, Yiling Ke, Dandan Wu, Xiaojun Chen, Li Wang, Qing Zhang, Qinhua Zhang, Wen Li
Published in
Frontiers in medicine. Volume 13. Pages 1867311. Epub Jul 13, 2026.
Abstract
The trueness of serum estradiol (E2) measurement is critical for monitoring follicle development in assisted reproductive technology (ART). This study aimed to evaluate E2 assay standardization, assess the trueness of harmonized E2 results across platforms, and investigate the relationship between estimated E2 levels and follicle diameters on human chorionic gonadotropin (hCG) trigger days.
Serum samples from 90 individuals were analyzed using assays from four manufacturers and LC-MS, which served as the reference method. A Bland-Altman plot-based harmonization algorithm (BA-BHA) was applied to harmonize E2 results. Trueness was assessed by mean percent difference and 95% limits of agreement (LoA). Harmonized results were compared to identify high-trueness kits. Additionally, 237 serum samples with corresponding follicle data from ART patients on hCG trigger days were analyzed. Multiple linear regression was applied to establish the relationship between harmonized E2 levels and follicle diameters.
Before harmonization, mean percent differences from LC-MS ranged from-2.3% to 17.4%. LiCA-E2 demonstrated the best performance. Following harmonization using the BA-BHA, LiCA maintained superior trueness, as indicated by a mean percent difference of 0.1% and a sum of 95% LoA of 41.4%. Multiple linear regression revealed a positive correlation between estimated E2 levels and follicle diameters. LiCA exhibited the strongest linear correlation between estimated E2 levels and corresponding diameters of follicle, with a linear regression equation and a Pearson's correlation coefficient r = 0.8077.
Harmonization effectively improves E2 assay comparability. LiCA's superior performance and strong E2-follicle correlation offer a reliable tool for predicting follicle maturation, guiding clinical decisions in ART.
PMID:
42517035
Bibliographic data and abstract were imported from PubMed on 28 Jul 2026.
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