The Ovarian Sensitivity Index (OSI) Significantly Correlates with Ovarian Reserve Biomarkers, Is More Predictive of Clinical Pregnancy than the Total Number of Oocytes, and Is Consistent in Consecutive IVF Cycles

Abstract

BACKGROUND AND OBJECTIVES: Some biomarkers of ovarian responsiveness to gonadotropins and the total number of retrieved oocytes are known to affect the success rate after controlled ovarian stimulation (COS) and in vitro fertilization (IVF). The aim of this study was to study another putative marker, the Ovarian Sensitivity Index (OSI: (number of retrieved oocytes/total gonadotropin dose) × 1000), assessing whether (a) it correlates with ovarian responsiveness biomarkers, (b) it is an independent predictor of clinical pregnancy, (c) it predicts clinical pregnancy comparably to the number of retrieved oocytes, and (d) it is consistent in the repeated COS cycles of the same woman. DESIGN: retrospective analysis. SETTING: public IVF Unit in University Hospital. Cases and Measurements: 1612 patients submitted to 3353 IVF cycles were included, their OSI was calculated and it was correlated with the ovarian responsiveness biomarkers (age, BMI, anti-Mullerian hormone, antral follicle count). The OSI and the total number of oocytes were compared for their value in predicting clinical pregnancy. The inter-cycle consistency of the OSI was estimated in 209 patients who underwent two consecutive cycles in which the ovarian stimulation regimen was changed from the Gonadotropin-releasing Hormone (GnRH)-agonist long protocol to the GnRH-antagonist protocol or vice-versa. RESULTS: < 0.0001 vs. <0.002). In patients who underwent two consecutive COS cycles changing stimulation regimen, the OSI showed 82% consistency. CONCLUSION(S): The OSI significantly correlates to the currently used biomarkers of ovarian responsiveness; it is an independent predictor of clinical pregnancy; it is more predictive of clinical pregnancy than the total number of oocytes, and is highly consistent in repeated IVF cycles even when the COS protocol changes. These characteristics make the OSI quite suitable to be incorporated into more complex prediction models of IVF outcome.