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ORIGINAL RESEARCH article

Front. Endocrinol.

Sec. Reproduction

Volume 16 - 2025 | doi: 10.3389/fendo.2025.1551530

Analysis of Factors Influencing Clinical Pregnancy Rates in Frozen-Thawed Embryo Transfer Cycles

Provisionally accepted
Junqiang  WangJunqiang Wang1Zexing  YangZexing Yang2Ying  ChenYing Chen3Fengchen  GaoFengchen Gao1Wenxiu  ZhaoWenxiu Zhao1Shuxuan  CaoShuxuan Cao1Yixi  LiYixi Li1Limei  HeLimei He3*
  • 1School of Public Health, Kunming Medical University, Kunming, China
  • 2Department of Reproductive Genetics, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, China
  • 3Department of Epidemiology and Health Statistics, School of Public Health, Kunming Medical University, Kunming, China

The final, formatted version of the article will be published soon.

Objective: To identify the determinants influencing clinical pregnancy outcomes in frozen-thawed embryo transfer (FET) cycles.Methods: A retrospective analysis was conducted on patients who underwent FET at the Department of Reproductive Genetics, The First Affiliated Hospital of Kunming Medical University, between January 2018 and December 2023. A total of 7,302 FET cycles were included and categorized into two groups based on clinical pregnancy outcomes: the clinical pregnancy group (n = 3,365) and the non-clinical pregnancy group (n = 3,937). Baseline characteristics were compared between groups. A random forest algorithm was applied to rank the importance of variables, followed by dimensionality reduction using a sliding window sequential forward selection (SWSFS) method. The top-ranked predictors with the lowest average out-of-bag (OOB) error rates were incorporated into a multivariate logistic regression model to determine independent predictors of clinical pregnancy in FET cycles.Results: The overall clinical pregnancy rate (CPR) was 46.08%. The CPR was significantly higher in blastocyst transfers (61.14%) compared to cleavage-stage embryo transfers (34.13%) (χ² = 528.973, P < 0.01). The random forest model identified seven variables with the highest predictive value: female age, number of high-quality blastocysts, anti-Müllerian hormone (AMH) level, embryo stage at transfer, endometrial thickness on the day of transfer, number of high-quality cleavage-stage embryos, and pre-transfer endometrial thickness. Multivariate logistic regression analysis demonstrated that younger female age (OR: 0.93; 95% CI: 0.92–0.94), greater number of high-quality blastocysts (OR: 1.67; 95% CI: 1.49–1.88), higher AMH levels (OR: 1.03; 95% CI: 1.01–1.05), blastocyst transfer (OR: 2.31; 95% CI: 1.85–2.88), increased endometrial thickness on transfer day (OR: 1.10; 95% CI: 1.05–1.15), more high-quality cleavage-stage embryos (OR: 1.74; 95% CI: 1.59–1.92), and greater pre-transfer endometrial thickness (OR: 1.04; 95% CI: 1.00–1.09) were all independently associated with higher clinical pregnancy rates.Conclusion: Female age, number of high-quality blastocysts, AMH levels, embryo stage at transfer, endometrial thickness on the day of transfer, number of high-quality cleavage-stage embryos, and pre-transfer endometrial thickness are significant predictors of clinical pregnancy outcomes in FET cycles. These findings may guide individualized embryo transfer strategies to optimize reproductive success.

Keywords: Assisted Reproductive Technology, Frozen-thawed embryo transfer, Clinical pregnancy, Female age, Influencing factors

Received: 25 Dec 2024; Accepted: 11 Jun 2025.

Copyright: © 2025 Wang, Yang, Chen, Gao, Zhao, Cao, Li and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Limei He, Department of Epidemiology and Health Statistics, School of Public Health, Kunming Medical University, Kunming, China

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