Predictive factors for ovarian response in a corifollitropin alfa/GnRH antagonist protocol for controlled ovarian stimulation in IVF/ICSI cycles

Sergio Oehninger, Scott M Nelson, Pierre Verweij, Barbara J Stegmann, Sergio Oehninger, Scott M Nelson, Pierre Verweij, Barbara J Stegmann

Abstract

Background: This secondary analysis aimed to identify predictors of low (<6 oocytes retrieved) and high ovarian response (>18 oocytes retrieved) in IVF patients undergoing controlled ovarian stimulation with corifollitropin alfa in a gonadotropin-releasing hormone (GnRH) antagonist protocol.

Methods: Statistical model building for high and low ovarian response was based on the 150 μg corifollitropin alfa treatment group of the Pursue trial in infertile women aged 35-42 years (n = 694).

Results: Multivariable logistic regression models were constructed in a stepwise fashion (P <0.05 for entry). 14.1 % of subjects were high ovarian responders and 23.2 % were low ovarian responders. The regression model for high ovarian response included four independent predictors: higher anti-Müllerian hormone (AMH) and antral follicle count (AFC) increased the risk, and higher follicle-stimulating hormone (FSH) levels and advancing age decreased the risk of high ovarian response. The regression model for low ovarian response also included four independent predictors: advancing age increased the risk, and higher AMH, higher AFC and longer menstrual cycle length decreased the risk of low ovarian response.

Conclusions: AMH, AFC and age predicted both high and low ovarian responses, FSH predicted high ovarian response, and menstrual cycle length predicted low ovarian response in a corifollitropin alfa/GnRH antagonist protocol.

Trial registration number: NCT01144416 , Protocol P06029.

Figures

Fig. 1
Fig. 1
Receiver operating characteristic curves for models for high ovarian response (>18 oocytes). AUC: area under the curve; AMH: anti-Müllerian hormone; AFC: antral follicle count; FSH: follicle-stimulating hormone
Fig. 2
Fig. 2
Receiver operating characteristic curves for models for low ovarian response (

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Source: PubMed

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