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Objective: Ovarian response indexes have been proposed in assisted reproductive technology (ART) in order to optimize live birth rates (LBR), adjusting ovarian stimulation (OS), and minimizing risks. Gonadotropin doses are commonly adjusted according to ovarian reserve parameters, including antral follicle count (AFC), anti-Mullerian hormone (AMH), and basal follicle stimulating hormone (FSH) levels. The retrospective assessment of ovarian responses allows one to identify three primary indexes: (i) follicular output rate (FORT), the ratio of the number of pre-ovulatory follicles obtained at OS completion over AFC; (ii) follicle oocyte index (FOI), the ratio of oocytes retrieved over AFC; (iii) ovarian sensitivity index (OSI), the ratio of oocytes retrieved over the total gonadotropin dose administered. In recent publications, these indexes were reported to predict ART outcome. In the present study, we assessed the ability of these indexes to predict cumulative ART outcome in women ≥39 years. Materials and Methods: Retrospective cohort study. All patients ≥39 years who performed their first ART cycle with an antagonist protocol in our center between 01/2018 and 04/2020 were included. Patients with basal FSH &gt; 20 IU/l, AMH &lt; 0.1 ng/mL and severe male factors (azoospermia with testicular biopsy) were excluded. All patients received both recombinant FSH and human menopausal gonadotropin (hMG). Cumulative live birth rate (cLBR) was the primary outcome. Secondary outcomes included: the number of MII oocytes, cumulative implantation (cIR), and usable blastulation rates. Logistic regressions were performed to assess the predictive values of FORT, FOI, and OSI in cLBR and embryo culture success. For each parameter, the ability of the logistic regression models to predict embryo culture success was quantified by the area under the ROC curve (AUC). Only the significant findings related to FORT, FOI, and OSI were included in the multiple logistic regression model. Linear regression models were performed between cIR, cLB, FORT, FOI, and OSI. Each statistic model was adjusted for age. Concerning OR for OSI, values were multiplied *100 due to the very low value. Results: 429 patients met the inclusion criteria. There were 298 obtained usable blastocysts after ART treatment. Age-adjusted OSI was significantly associated with cLBR [OR = 17.58 95% CI (5.48–56.40), AUC = 0.707 95% CI (0.651–0.758)) and cIR (beta = 30.22 (SE: 7.88), p &lt; 0.001, R2= 0.060). Both FOI (OR = 6.33 95% CI (3.27–12.25), AUC = 0.725 95% CI (0.675–0.771), R2 = 0.090, p &lt; 0.001) and OSI (OSI*100; OR = 1808.93 95% CI (159.24–19,335.13), AUC = 0.790 95% CI (0.747–0.833), R2 = 0.156, p &lt; 0.001) were independently, when age adjusted, associated with embryo culture success. OSI showed a main performance to explain successful embryo culture than FOI (R2 = 0.156 vs. R2 = 0.090, p &lt; 0.001). In the age-adjusted linear regression model, FOI (R2 = 0.159, p &lt; 0.001), OSI (R2 = 0.606, p &lt; 0.001), and FORT (r2 = 0.030, p &lt; 0.001) were predictive of the number of MII oocytes collected. Furthermore, for OSI (r2 = 0.759, p &lt; 0.001) and FOI (r2 = 0.297, p &lt; 0.001), the correlation with the number of metaphase II oocytes collected was significantly higher in the non-linear regression model. Conclusions: Our findings suggest that the best index, among those analyzed, to predict cIR and cLBR, is OSI. Both OSI and FOI predict embryo culture with success, but OSI is more accurate. OSI, FOI, and FORT are significantly related to the number of MII oocytes obtained.

Are There Ovarian Responsive Indexes That Predict Cumulative Live Birth Rates in Women over 39 Years?