Journal of International Reproductive Health/Family Planning ›› 2026, Vol. 45 ›› Issue (5): 368-372.doi: 10.12280/gjszjk.20260383

• Original Article • Previous Articles     Next Articles

Construction of A Nomogram Model for Predicting Pregnancy Outcomes in Fresh Embryo Transfer Cycles Using GnRH Antagonist Protocols

LI Xin-xin, HUANG Yu-shan, GAN Tian, MENG Yue()   

  1. Center for Reproductive Medicine (LI Xin-xin, HUANG Yu-shan, GAN Tian), Department of Gynecology (MENG Yue), The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
  • Received:2026-07-17 Published:2026-09-15 Online:2026-09-20
  • Contact: MENG Yue, E-mail: mengy67@mail.sysu.edu.cn

Abstract:

Objective: To investigate the factors influencing the clinical pregnancy rate in fresh embryo transfer cycles using gonadotropin-releasing hormone (GnRH) antagonist protocols, and to construct and validate a predictive model. Methods: A total of 2 405 fresh embryo transfer cycles using GnRH antagonist protocols were retrospectively analyzed, at the Third Affiliated Hospital of Sun Yat-Sen University between January 2018 and December 2024. The cycles were randomly allocated into a training cohort (n=1 683) and a validation cohort (n=722) at a 7∶3 ratio. The independent factors influencing clinical pregnancy were identified by multivariate logistic regression analysis, which were subsequently used to construct a nomogram. The model performance was then evaluated using the area under the receiver operating characteristic curve and calibration curves. Results: Multivariable logistic regression analysis revealed that a greater number of high-quality D3 embryos (OR=0.88, 95%CI: 0.82-0.94) and the transfer of two embryos (versus one embryo, OR=0.52, 95%CI: 0.37-0.72) were associated with decreased probability of non-clinical pregnancy. Conversely, the advancing female age (OR=1.04, 95%CI: 1.00-1.09) and the elevated serum progesterone on trigger-day (OR=2.44, 95%CI: 1.46-4.09) were associated with increased probability of non-clinical pregnancy. Based on these four independent predictors, a predictive model for clinical pregnancy was developed, and a nomogram was constructed. The model was demonstrated the moderate discriminative performance, with an area under the receiver operating characteristic curve of 0.64 (95%CI: 0.61-0.67) in the training set and 0.65 (95%CI: 0.61-0.69) in the validation set. Calibration curves for both datasets showed a close agreement between predicted and observed probabilities, indicating good model calibration. Conclusions: The developed nomogram demonstrates favorable predictive performance, which may be used for the individualized prediction of clinical pregnancy, thereby providing data-driven recommendations for embryo transfer strategies.

Key words: Reproductive techniques, assisted, Embryo transfer, Gonadotropin-releasing hormone, Pregnancy outcome, Nomograms, GnRH antagonist protocol