Andrea Roberto Carosso, Rik van Eekelen, Alberto Revelli, Stefano Canosa, Noemi Mercaldo, Chiara Benedetto and Gianluca Gennarelli
J. Clin. Med.2022, 11(3), 859; https://doi.org/10.3390/jcm11030859
Received: 12 January 2022 / Revised: 1 February 2022 / Accepted: 1 February 2022 / Published: 6 February 2022
Abstract
Background: Several researchers have investigated alternative markers related to ovarian responsiveness in order to better predict IVF outcomes, particularly in advanced reproductive-aged women. The follicular output rate (FORT), the follicle-oocyte index (FOI) and the ovarian sensitivity index (OSI) are among the most promising. However, these three metrics have not been investigated as independent predictors of live birth in women of advanced reproductive age; neither have they been compared to the two ‘component’ characteristics that are used to calculate them. Methods: A logistic regression model containing all relevant predictors of ovarian reserve or response was used to evaluate the potential of FORT, FOI and OSI as predictors of live birth. After, the non-linear associations between FORT, FOI and OSI and the probability of live birth were evaluated. Finally, we fitted multiple logistic regression models to compare whether FORT, FOI and OSI were more informative predictors than their components.
Results: 590 couples received a total of 740 IVF cycles, after which, 127 (17.5%) obtained a live birth. None of FORT, FOI and OSI showed a strength of association or a p-value even close to female age (odds ratio for live birth (95% confidence interval) 1.00 (0.99–1.01), 1.00 (0.99–1.01), 0.98 (0.88–1.11) and 0.58 (0.48–0.72), respectively). The three models comparing FORT, FOI and OSI with the number of oocytes retrieved, the AFC, the number of preovulatory follicles and the FSH total dose were not more informative.
Conclusions: In a population of women of advanced age with unexplained infertility, none of FORT, FOI and OSI were predictive of live birth or more predictive than the two ‘component’ characteristics that were used to calculate them. We suggest clinicians and researchers still use female age as the most reliable predictor of an IVF treatment