Publication:

Predictors of optimal ovarian response in GnRH antagonist ovarian stimulation protocol

Background The outcome of assisted reproductive technology (ART) is significantly influenced by the ovarian response to controlled ovarian stimulation (COS). Identifying robust and reliable predictors of ovarian response is essential for tailoring individualized treatment strategies and optimizing reproductive success. This study aims to investigate clinical, hormonal, and stimulation-related variables that influence ovarian response among women undergoing ART and to identify significant predictors for both hyper-response and hypo-response patterns.

Methods A retrospective cohort analysis was conducted involving 278 women who underwent COS under a gonadotropin-releasing hormone (GnRH) antagonist protocol. Based on ovarian responsiveness, participants were categorized into three groups: high responders (n=56), normal responders (n=151), and low responders (n=71). Demographic data, hormonal markers (including Anti-Müllerian hormone [AMH], antral follicle count [AFC], follicle-stimulating hormone [FSH], and luteinizing hormone [LH]), stimulation characteristics, and infertility etiologies were systematically analyzed. Statistical comparisons utilized t-tests and chi-square tests, while logistic regression identified independent predictive parameters. A p-value of less than 0.05 was considered statistically significant.

Results Higher AFC and AMH levels, younger age, and lower baseline FSH levels were significantly correlated with high ovarian response. In contrast, women with low AMH, high FSH, reduced AFC, and prolonged stimulation duration tended to demonstrate poor ovarian responsiveness. Notably, polycystic ovary syndrome (PCOS) was more frequent in high responders, while diminished ovarian reserve (DOR) predominated in low responders. Multivariate logistic regression identified AMH and AFC as the most significant independent predictors of ovarian response.

Conclusions Age, AMH, AFC, and baseline FSH are critical determinants of ovarian response in ART cycles. Incorporating these biomarkers into pre-treatment evaluation facilitates the customization of stimulation protocols, thereby enhancing oocyte yield and improving overall clinical outcomes. Personalized treatment planning grounded in these predictors holds promise for advancing ART success.