ArticleInternational journal of women's health2025
Nomogram-Based Prediction of Live Birth in GnRH Antagonist Protocol Fresh IVF/ICSI Cycles.
Article in International journal of women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: This investigation sought to determine optimal prognostic indicators and develop an implementable predictive framework for estimating live birth probabilities in subfertile individuals receiving gonadotropin-releasing hormone antagonist-based ovarian stimulation during fresh embryo transfer cycles of assisted reproductive technology. Methods: In this observational cohort analysis, we examined consecutive fresh in vitro fertilization/embryo transfer (IVF/ET) cycles utilizing GnRH antagonist protocols (training = 587, validation = 168 cycles; 2017-2022). Live birth rate served as the principal outcome measure. Through multivariable regression modeling, we identified key predictive variables and constructed a visual prediction tool. Model robustness was assessed using ROC-AUC metrics and decision curve validation with 500 bootstrap iterations. Results: The final predictive algorithm incorporated six clinical parameters: serum progesterone on post-ovulation day 9 (serum P (OPU+9) ≥ 51.4 ng/mL), transferred embryo count, progesterone-follicle ratio (PFR), triggering-day progesterone levels, progesterone-to-total follicle ratio, and creatinine concentrations. The training cohort demonstrated moderate discriminative capacity (ROC-AUC 0.72, 95% CI 0.68-0.76), with enhanced performance in validation samples (AUC 0.81, 95% CI 0.73-0.89). Decision curve evaluations confirmed the model's clinical applicability. Conclusion: Our prognostic scoring chart offers an accessible and practical clinical instrument for estimating reproductive success in GnRH antagonist-based IVF/ICSI cycles. This tool facilitates personalized treatment planning and therapeutic strategy optimization, potentially improving resource allocation in fertility care.
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