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

Establishment and validation of a nomogram for subsequent first-cycle live births in patients diagnosed with recurrent implantation failure: a population-based analysis

Background

The inability of patients with recurrent implantation failure (RIF) to achieve pregnancy and a live birth after multiple high-quality embryo transfer treatments has been recognized as a major obstacle to successful application of artificial reproductive technologies. The objective of this study was to establish and validate a nomogram for prediction of subsequent first-cycle live births to guide clinical practice in patients diagnosed with RIF.

Methods

A total of 538 patients who underwent in vitro fertilization/intracytoplasmic sperm injection treatment and were first diagnosed with RIF at the Reproductive Center of the First Affiliated Hospital of Xinjiang Medical University between January 2017 and December 2020 were enrolled. The patients were randomly divided into a training cohort (n=408) and a validation set (n=175) in a ratio of 7:3. A nomogram model was constructed using the training set based on the results of univariate and multivariate logistic regression analyses and validated in the validation set.

Results

Age, body mass index, duration of RIF, endometrial thickness, type of embryo transferred, and number of previous biochemical pregnancies were included in the nomogram for prediction of subsequent first-cycle live births in patients diagnosed with RIF. Analysis of the area under the receiver-operating characteristic curve, calibration plots, and decision curve analysis showed that our predictive model for live births had excellent performance.

Conclusion

We have developed and validated a novel predictive model that estimates a woman's chances of having a live birth after a diagnosis of RIF and provides clinicians with a personalized clinical decision-making tool.

Predicting the ovarian response: towards a determinant model and implications for practice

OBJECTIVE

To improve the reliability of prediction models for ovarian response to stimulation in ART.

DESIGN

A multicenter retrospective cohort study.

SETTING

Twelve reproductive centers.

PATIENTS

A total of 25,854 controlled ovarian stimulations between 2005 and 2016, including cycles cancelled for inadequate response, were included.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Precision of the prediction of the number of oocytes at ovarian pickup and of cancellation rate for poor ovarian response.

RESULTS

Both AMH and antral follicle count exhibit a non-linear effect on the oocyte yield, with a linear relationship after log-transformation. After adjustment for age, BMI, and center, ovarian response observed in a previous stimulation was found to be the best predictor, followed by AMH and AFC. The zero-inflated binomial negative model showed that predictors of cycle cancellation and number of oocytes at retrieval were different, and assimilating cancellation to zero oocyte greatly reduces the determination of the model. Our model was characterized by the best ever reached determination (R2=0.505 for non-naïve women, 0.313 for all the women) and provided evidence of a very strong difference among centers. The results can be easily converted in the prediction of response levels (poor-medium-good-high). Finally, in case of partial report of the above predictors, we show that the univariate prediction based on the best predictor provides a good approximation.

CONCLUSION(S)

A substantial improvement of the ovarian response prediction is possible in modelling the possible cancellation decision, followed by the oocyte retrieval itself, according to an appropriate model based on previous stimulation and non-linear effects of AMH and AFC.

Machine Learning-Based Modeling of Ovarian Response and the Quantitative Evaluation of Comprehensive Impact Features

Appropriate ovarian responses to the controlled ovarian stimulation strategy is the premise for a good outcome of the in vitro fertilization cycle. With the booming of artificial intelligence, machine learning is becoming a popular and promising approach for tailoring a controlled ovarian stimulation strategy. Nowadays, most machine learning-based tailoring strategies aim to generally classify the controlled ovarian stimulation outcome, lacking the capacity to precisely predict the outcome and evaluate the impact features. Based on a clinical cohort composed of 1365 women and two machine learning methods of artificial neural network and supporting vector regression, a regression prediction model of the number of oocytes retrieved is trained, validated, and selected. Given the proposed model, an index called the normalized mean impact value is defined and calculated to reflect the importance of each impact feature. The proposed models can estimate the number of oocytes retrieved with high precision, with the regression coefficient being 0.882% and 89.84% of the instances having the prediction number ≤ 5. Among the impact features, the antral follicle count has the highest importance, followed by the E2 level on the human chorionic gonadotropin day, the age, and the Anti-Müllerian hormone, with their normalized mean impact value > 0.3. Based on the proposed model, the prognostic results for ovarian response can be predicted, which enables scientific clinical decision support for the customized controlled ovarian stimulation strategies for women, and eventually helps yield better in vitro fertilization outcomes.

Which is more predictive ovarian sensitivity marker if there is discordance between serum anti-Müllerian hormone levels and antral follicle count? A retrospective analysis

This retrospective study aims to determine the more predictive ovarian reserve marker when there is discordance between anti-Müllerian hormone (AMH) and antral follicle count (AFC) in patients with diminished ovarian reserve (DOR). Patients who underwent ICSI because of DOR were divided into three groups. Group 1: patients with low AMH (<1.1 ng/ml) and AFC (n < 7), group 2: patients with low AMH (<1.1 ng/ml) and normal AFC (n ≥ 7) and group 3: patients with normal AMH (≥1.1 ng/dl) and low AFC (n < 7). Demographic values, follicle output rate (FORT) score and follicle to oocyte index (FOI) score of the groups were compared. Totally, 662 cycles were enrolled in the study. There were 418 cycles in group 1, 167 cycles in group 2 and 77 cycles in group 3. As the primary result, FORT and FOI scores were higher in group 3 than the other two groups. Median FORT Score with quartiles: group 1: 100 (66-150), group 2: 71 (57-100), group 3: 136 (96-200), p<.01 - median FOI score with quartiles: group 1: 83 (50-140), group 2: 71 (40-100), group 3: 116 (66-216), p<.01. In conclusion, serum AMH level has more predictive value for stimulation success if there is discordance with AFC.Impact StatementWhat is already known on this subject? Female age, serum Anti-Müllerian Hormone (AMH) levels, and antral follicle count (AFC) are commonly used to assess ovarian reserve and predict response to ovarian stimulation. AMH and AFC are both positively correlated with ovarian reserve.What do the results of this study add? If there is discordance between AFC and AMH in patients with diminished ovarian reserve (DOR), the ovarian response is better in patients with high AMH and low AFC than the patients with low AMH and high AFC.What are the implications of these findings for clinical practice and/or further research? It is important to assess both AFC and AMH before controlled ovarian hyperstimulation, to predict ovarian response in DOR patients, rather than assessing AFC or AMH alone.

Association Between the Ratio of Ovarian Stimulation Duration to Original Follicular Phase Length and In Vitro Fertilization Outcomes: A Novel Index to Optimise Clinical Trigger Time

The duration of ovarian stimulation which is largely dependent on the ovarian response to hormonal stimulation may influence in vitro fertilization (IVF) outcomes. Menstrual cycle length is potentially a good indicator of ovarian reserve and can predict ovarian response. Ovarian stimulation and the follicular phase of the menstrual cycle are both processes of follicular development. There is no published research to predict the duration of ovarian stimulation based on the length of the menstrual cycle. Our retrospective cohort study included 6110 women with regular menstrual cycles who underwent their first IVF treatment between January 2015 and October 2020. Cycles were classified according to quartiles of the ratio of ovarian stimulation duration to original follicular phase length (OS/FP). Multivariate generalized linear models were applied to assess the association between OS/FP and IVF outcomes. The odds ratio (OR) or relative risk (RR) was estimated for each quartile with the lowest quartile as the comparison group. OS/FP of 0.67 to 0.77 had more retrieved and mature oocytes (adjusted RR 1.11, 95% confidence interval [CI] 1.07-1.15, p for trend = 0.001; adjusted RR 1.14, 95% CI 1.09-1.19, p for trend = 0.001). OS/FP of 0.67 to 0.77 showed the highest rate of fertilization (adjusted OR 1.11, 95% CI 1.05-1.17, p for trend = 0.001). OS/FP > 0.77 had the lowest rate of high-quality blastocyst formation (adjusted OR 0.81, 95% CI 0.71-0.93, p for trend = 0.01). No apparent association was noted between OS/FP and clinical pregnancy, live birth, or early miscarriage rate. In conclusion, OS/FP has a significant effect on the number of oocytes, fertilization rate, and high-quality blastocyst formation rate. MCL could be used to predict the duration of ovarian stimulation with an OS/FP of 0.67 to 0.77, which provides a new indicator for the individualized clinical optimization of the trigger time.

Analysis of relative factors and prediction model for optimal ovarian response with gonadotropin-releasing hormone antagonist protocol

OBJECTIVE

To explore the relative factors for best ovarian response in patients undergoing assisted reproductive technology with the gonadotropin-releasing hormone antagonist protocol and to establish a nomogram prediction model of ovarian response.

METHODS

A retrospective cohort analysis of the clinical data of 1,944 patients who received assisted reproductive treatment in the Center for Reproductive Medicine of Fujian Maternity and Child Health Hospital from April 1, 2018, to June 30, 2020. According to the number of oocytes obtained, there were 659 cases in the low ovarian response group (no more than five oocytes were retrieved), 920 cases in the normal ovarian response group (the number of retrieved oocytes was >5 but ≤18), and 365 cases in the high ovarian response group (>18 oocytes retrieved). Independent factors affecting ovarian responsiveness were screened by logistic regression, which were the model entry variables, and a nomogram prediction model was established based on the regression coefficients.

RESULTS

There were statistically significant differences in age, anti-Mullerian hormone, antral follicle count, the diagnosis of endometriosis, decreased ovarian reserve, polycystic ovary syndrome, basal follicle-stimulating hormone and basal luteinizing hormone among the three groups (P < 0.001). Multifactorial stepwise regression analysis showed that female age (0.95 [0.92-0.97], P = 0.000), decreased ovarian reserve (0.27 [0.19-0.38]), P = 0.000), endometriosis (0.81 [0.56-0.86], P = 0.000), antral follicle count (1.09 [1.06-1.12], P = 0.000), basal follicle-stimulating hormone (0.90 [0.85-0.96], P = 0.001), Anti-Mullerian hormone (1.19 [1.13-1.26], P= 0.000) and luteinizing hormone on trigger day (0.73 [0.66-0.80], P= 0.000), were independent factors for the occurrence of different ovarian responses during ovarian hyperstimulation. The predictive model of ovarian responsiveness was constructed based on the above factors, and the model was verified with 589 patients' data from July 1, 2020, to December 31, 2020, at this center. The predicted ovarian response (number of eggs obtained) of a total of 450 patients was consistent with the actual results, with a coincidence degree of 76.4%, and the consistency index of the model is 0.77.

CONCLUSION

The nomogram model was successfully developed to effectively, intuitively, and visually predict the ovary reactivity in the gonadotropin-releasing hormone antagonist protocol and provide guidance for clinical practice.

Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study

Objective

To develop and validate a prediction model for high ovarian response in in vitro fertilization-embryo transfer (IVF-ET) cycles.

Methods

Totally, 480 eligible outpatients with infertility who underwent IVF-ET were selected and randomly divided into the training set for developing the prediction model and the testing set for validating the model. Univariate and multivariate logistic regressions were carried out to explore the predictive factors of high ovarian response, and then, the prediction model was constructed. Nomogram was plotted for visualizing the model. Area under the receiver-operating characteristic (ROC) curve, Hosmer-Lemeshow test and calibration curve were used to evaluate the performance of the prediction model.

Results

Antral follicle count (AFC), anti-Müllerian hormone (AMH) at menstrual cycle day 3 (MC3), and progesterone (P) level on human chorionic gonadotropin (HCG) day were identified as the independent predictors of high ovarian response. The value of area under the curve (AUC) for our multivariate model reached 0.958 (95% CI: 0.936-0.981) with the sensitivity of 0.916 (95% CI: 0.863-0.953) and the specificity of 0.911 (95% CI: 0.858-0.949), suggesting the good discrimination of the prediction model. The Hosmer-Lemeshow test and the calibration curve both suggested model's good calibration.

Conclusion

The developed prediction model had good discrimination and accuracy via internal validation, which could help clinicians efficiently identify patients with high ovarian response, thereby improving the pregnancy rates and clinical outcomes in IVF-ET cycles. However, the conclusion needs to be confirmed by more related studies.

Does an association exist between menstrual cycle length within the normal range and ovarian reserve biomarkers during the reproductive years? A systematic review and meta-analysis

BACKGROUND

Regular menstrual cycling during the reproductive years is an indicator of spontaneous ovulation but sometimes falsely perceived as an indicator of preserved fertility. In contrast, menstrual cycle shortening, a physiologic occurrence preceding the menopausal transition, is not usually perceived as an indicator of decreased ovarian reserve in the general population.

OBJECTIVE AND RATIONALE

The individual decrease in menstrual cycle length (MCL) might represent a sensitive biomarker of diminishing ovarian reserve. The aim of this systematic review and meta-analysis is to examine the possible association between MCL in regularly cycling women (21-35 days) and ovarian reserve tests (ORT), fecundability in natural cycles and IVF outcomes.

SEARCH METHODS

An electronic database search employing PubMed, Web of Science, Trip, EBSCO, ClinicalTrials.gov and the Cochrane library was performed to identify research articles, only on human, published between January 1978 and August 2019. Search terms were pregnancy OR fertility OR fecundity OR fecundability, anti-Müllerian hormone OR AMH OR antral follicle count OR AFC OR ovarian reserve OR ovarian reserve test, in vitro fertilization OR ART OR assisted reproductive therapy OR assisted reproductive treatment OR assisted reproductive technology OR IVF OR ICSI, menstrual cycle length OR menstrual cycle characteristics. We combined these terms to complete the search. All prospective and retrospective studies exploring an association between MCL and proxies of ovarian reserve were included. The exclusions included studies of PCOS, ovarian failure, oral contraception treatment, prior chemotherapy and/or radiotherapy or ovarian surgery. The Newcastle-Ottawa scale was used to assess the quality of studies that were eligible for meta-analysis.

OUTCOMES

Eleven studies were eligible for meta-analysis, including 12 031 women. The included studies had a low risk of bias. Short MCL (21-27 days) was associated with lower ORT values as compared to normal (28-31 days), long (32-35 days) and all other (28-35 days) MCL sets. The estimated weighted mean difference (WMD) of AMH level was -1.3 ng/mL (95% CI: -1.75 to -0.86, P < 0.001) between the short and normal MCL sets. The estimated WMD of AFC values was -5.17 (95% CI: -5.96 to -4.37, P < 0.001) between the short and normal MCL sets. The weighted overall odds ratio (OR) of fecundability in natural cycles between women with short versus normal MCL sets was statistically significant (overall OR 0.81; 95% CI 0.72-0.91, P < 0.001). In the IVF setting, fewer oocytes were retrieved in short MCL in comparison to normal, long and all other MCL sets, with an estimated WMD of -1.8 oocytes (95% CI: -2.5 to -1.1, P < 0.001) in the short versus normal MCL sets. The weighted overall OR of clinical pregnancy rate between women with short versus all other MCL sets was statistically significant (overall OR 0.76; 95% CI: 0.60 to 0.96, P = 0.02). Low levels of heterogeneity were found in most meta-analyses of MCL and qualitative ovarian reserve biomarkers, while heterogeneity was high in meta-analyses performed for quantitative measures.

WIDER IMPLICATIONS

MCL in regularly cycling women is closely related to ovarian reserve biomarkers during the reproductive years. A short MCL, as compared to normal, is significantly associated with lower ORT values, reduced fecundability and inferior IVF outcomes, independent of age. The results imply that short MCL may be a sign of ovarian aging, combining the quantitative and qualitative facets of ovarian reserve. Educational efforts ought to be designed to guide women with short MCL at a young age, who desire children in the future, to seek professional counselling.

Novel nomogram-based integrated gonadotropin therapy individualization in in vitro fertilization/intracytoplasmic sperm injection: A modeling approach

OBJECTIVE

This study aimed to characterize a validated model for predicting oocyte retrieval in controlled ovarian stimulation (COS) and to construct model-based nomograms for assistance in clinical decision-making regarding the gonadotropin protocol and dose.

METHODS

This observational, retrospective, cohort study included 636 women with primary unexplained infertility and a normal menstrual cycle who were attempting assisted reproductive therapy for the first time. The enrolled women were split into an index group (n=497) for model building and a validation group (n=139). The primary outcome was absolute oocyte count. The dose-response relationship was tested using modified Poisson, negative binomial, hybrid Poisson-Emax, and linear models. The validation group was similarly analyzed, and its results were compared to that of the index group.

RESULTS

The Poisson model with the log-link function demonstrated superior predictive performance and precision (Akaike information criterion, 2,704; λ=8.27; relative standard error (λ)=2.02%). The covariate analysis included women's age (p<0.001), antral follicle count (p<0.001), basal follicle-stimulating hormone level (p<0.001), gonadotropin dose (p=0.042), and protocol type (p=0.002 and p<0.001 for short and antagonist protocols, respectively). The estimates from 500 bootstrap samples were close to those of the original model. The validation group showed model assessment metrics comparable to the index model. Based on the fitted model, a static nomogram was built to improve visualization. In addition, a dynamic electronic tool was created for convenience of use.

CONCLUSION

Based on our validated model, nomograms were constructed to help clinicians individualize the stimulation protocol and gonadotropin doses in COS cycles.

Are ovarian response and pregnancy rates similar in selected FMR1 premutated and mutated patients undergoing preimplantation genetic testing?

PURPOSE

To assess if the ovarian response of FMR1 premutated women undergoing preimplantation genetic testing (PGT) for Fragile X syndrome is lower compared with fully mutated patients, due to their frequent premature ovarian failure.

METHODS

In a retrospective cohort study from January 2009 to March 2019, we compared PGT outcomes in 18 FMR1 premutated women and 12 fully mutated women and aimed to identify predictive factors of stimulation outcomes.

RESULTS

Eighty-six IVF/PGT-M cycles for FMR1 PGT were analyzed. Premutation and full mutation patients were comparable in terms of age, body mass index (BMI), basal FSH, antral follicular count, and cycle length. However, premutation carriers had significantly lower AMH (1.9 versus 4.0 ng/mL, p = 0.0167). Premutated patients required higher doses of FSH (2740 versus 1944 IU, p = 0.0069) but had similar numbers of metaphase II oocytes (7.1 versus 6.6, p = 0.871) and embryos (5.6 versus 4.9, p = 0. 554). Pregnancy rates (37.1% versus 13.3%, p = 0.1076) were not statistically different in both groups.

CONCLUSION

In spite of lower ovarian reserve and thanks to an increased total dose of FSH, FMR1 premutated selected patients seem to have similar ovarian response as fully mutated patients. Neither the number of CGG repeats in FMR1 gene nor FMR1 mutation status was good predictors of the number of retrieved oocytes.

Performance of prognostic modelling of high and low ovarian response to ovarian stimulation for IVF

STUDY QUESTION

What is the performance of previously established regression models in predicting low and high ovarian response to 150 μg corifollitropin alfa/GnRH-antagonist ovarian stimulation in an independent dataset?

SUMMARY ANSWER

The outcome of ovarian stimulation with 150 μg corifollitropin alfa in a fixed, multiple dose GnRH-antagonist protocol can be validly predicted using logistic regression models with AMH being of paramount importance.

WHAT IS KNOWN ALREADY

Predictors of ovarian response have been identified in FSH/GnRH agonist protocols as well as ovarian stimulation with corifollitropin alfa/GnRH-antagonist. Multivariable response models have been established already, however, external validation of model performance has so far been lacking.

STUDY DESIGN, SIZE, DURATION

Data from a prospective, multi-centre (n = 5), multi-national, investigator-initiated, observational cohort study were analysed. Infertile women (n = 211), body weight >60 kg, were undergoing ovarian stimulation with 150 μg corifollitropin alfa in a GnRH-antagonist multiple dose protocol for transvaginal oocyte retrieval for IVF. Demographic, sonographic and endocrine parameters were prospectively assessed on cycle Day 2 or 3 of spontaneous menstruation before ovarian stimulation. Main outcomes were low (<6 oocytes) and high (>18 oocytes) ovarian response.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Firstly, previously established prediction models for low ovarian response (LOR) and high ovarian response (HOR) were tested using the original parameters. Secondly, re-estimated parameters generated from the present data were tested on the established models. Thirdly, for the development of new predictive models of both LOR and HOR, several logistic regression models were estimated. Resulting prediction models were compared by means of the area under the receiver operating characteristic curve (AUC) and bias-corrected Akaike's Information Criterion (AICc) to identify the most reasonable model for each scenario.

MAIN RESULTS AND THE ROLE OF CHANCE

The previously established prediction models for low and high response performed remarkably well on this dataset (low response AUC 0.8879 (95% CI: 0.8185-0.9573) and high response AUC 0.8909 (95% CI: 0.8251-0.9568)). A newly developed simplified model for LOR with log-transformed AMH values and only age as another covariate showed an AUC of 0.8920 (95% CI: 0.8237-0.9603) with the lowest AICc of all models compared. For predicting HOR, we suggest a simplified model using AMH, FSH and AFC (AUC of 0.8976, 95% CI: 0.8206-0.9746).

LIMITATIONS, REASONS FOR CAUTION

All analyses were done on data from women with a body weight >60 kg. The newly developed simplified models may suffer from overfitting and need to be tested in further independent data sets.

WIDER IMPLICATIONS OF THE FINDINGS

Patient selection for ovarian stimulation with corifollitropin alfa should utilize established response prediction models. The clinical impact of this needs to be evaluated in future studies.

STUDY FUNDING/COMPETING INTEREST(S)

The study was funded by university funds. M.O.S., T.L. and I.R.K. have nothing to declare. G.G. has received personal fees and non-financial support from MSD, Ferring, Merck-Serono, Finox, TEVA, IBSA, Glycotope, Abbott, Marckryl Pharma, VitroLife, NMC Healthcare, ReprodWissen, ZIVA and BioSilu.

TRIAL REGISTRATION NUMBER

Not applicable.

Corifollitropin- α compared to daily r-FSH in for patients undergoing intracytoplasmic sperm injection: Clinical trial study

Background

The current treatment regimen for ovarian stimulation in Intracytoplasmic sperm injection (ICSI) patients is daily injections of Gonadotropins. Recombinant DNA technologies have produced a new recombinant molecule that is a long-acting Follicle Stimulating Hormone (FSH), named corifollitropin alfa. A single injection of long-acting FSH can replace seven daily FSH injections during the first week of controlled ovarian stimulation (COS) and can make assisted reproduction more patients-friendly. There is limited data with different results in this area.

Objective

To compare the effectiveness of long-acting FSH vs. daily r-FSH in terms of pregnancy and safety outcomes in women undergoing ICSI cycles.

Materials and Methods

In this clinical trial study, 109 women who were the candidates for ICSI at azzahra hospital were divided in two groups. The first group received 150 units of daily Gonal-f from second or third day of menstruation. The second group received a 150IU corifollitropin alfa on the second or third day of mensuration, and the treatment continued from day eighth of stimulation with Gonal-f based on the ultrasound finding. Both the groups received GnRH antagonist from fifth day of stimulation. Two groups were compared in terms of number of dominant follicles, number of oocytes, stimulation duration, total number of embryos, number of transferred embryos, and success rate of pregnancy.

Results

No significant difference was found between the two groups in terms of stimulation duration, number of follicles, number of oocytes, total number of embryos, and number of transferred embryos. Moreover, pregnancy outcomes including chemical pregnancy rate (positive pregnancy test), clinical pregnancy rate (detection of fetal heart), the rate of ovarian hyper-stimulation syndrome, multiple-pregnancy, ectopic pregnancy, and miscarriage didn't have a significant difference between the two groups.

Conclusion

As corifollitropin alfa was as effective as r-FSH, it could be used as an alternative to ovulation stimulation method in patients undergoing ICSI.

Association of progesterone production with serum anti-Müllerian hormone levels in assisted reproductive technology cycles with corifollitropin alfa

The use of corifollitropin alfa (CA) in assisted reproductive technology (ART) cycles is dependent on the antral follicle count and body weight of patients. The present study investigated the safety and efficacy of using 100μg of CA in predicted excessive responders based on serum anti-Mullerian hormone (AMH) level. The results of 381 ART cycles stimulated by CA versus daily recombinant follicle-stimulation hormone (rFSH) in patients with low (<1.0 ng/mL; n = 38 vs. n = 90), moderate (1.0–3.36 ng/mL; n = 38 vs. n = 95), and high (> 3.36 ng/mL; n = 48 vs. n = 72) serum AMH levels, were analyzed. Pregnancy and live birth rates did not significantly differ between CA and daily rFSH groups. In the patients with high AMH levels, serum progesterone (P4) levels on the day of human chorionic gonadotropin (hCG) injection were significantly lower in the CA group than in the rFSH group (0.93 ± 0.55 vs. 1.16 ± 0.64 ng/mL). Furthermore, serum P4 levels on the day of hCG injection were negatively correlated with baseline AMH levels in the CA group, but not in the rFSH group, in the patients with high AMH levels. In conclusion, the use of 100 μg of CA in patients with high AMH levels is safe and effective and is associated with a lower P4 level on the day of hCG injection compared with the use of daily rFSH.

Corifollitropin alfa compared with follitropin beta in GnRH-antagonist ovarian stimulation protocols in an unselected population undergoing IVF/ICSI

Recombinant DNA technologies have produced Corifollitropin alfa (CFa) used during IVF/ICSI in order to keep the circulating FSH levels above the threshold necessary to support multi-follicular growth for a week. In this prospective case-control study, we compared 70 participants treated with 150 μg CFa combined with 150 IU of follitropin beta (study group) with 70 subfertile participants with matching baseline characteristics, conforming with the same inclusion criteria and treated with an antagonist protocol using follitropin beta (control group). Live birth was the primary outcome, while secondary outcome measures were IVF/ICSI cycles characteristics, including adverse events and complications. Live birth was determined in reduced rates in the study compared to the control group, reaching statistical significance [6/70 versus 20/70, p = 0.002], as also in the respective number of clinical pregnancies [9/70 versus 23/70, p = 0.005], although the incidence of miscarriage was similar for both groups [6/70 versus 5/70, p > 0.99]. Most of the secondary parameters examined were similar between groups. Logistic regression revealed that protocol and AFC had a direct impact on live birth. Ovarian stimulation with CFa does not seem to constitute an equally effective method as compared with follitropin beta to be offered in a general subfertile population seeking IVF/ICSI treatments.

Establishment and validation of a score to predict ovarian response to stimulation in IVF

This study aimed to integrate clinical and biological parameters in a score able to predict ovarian response to stimulation for IVF in gonadotrophin-releasing hormone (GnRH) antagonist protocols. A progressive discriminant analysis to establish a score including the main clinical and biological parameters predicting ovarian response was performed by retrospectively analysing data from the first ovarian stimulation cycle of 494 patients. The score was validated in a prospectively enrolled, independent set of 257 patients undergoing their first ovarian stimulation cycle. All ovarian stimulations were performed using a combination of GnRH antagonist and recombinant FSH. Ovarian response was assessed through ovarian sensitivity index (OSI). Parameters from the patients' database were classified according to correlation with OSI: the progressive discriminant analysis resulted in the following calculation: score = 0.192 - (0.004 × FSH (IU/l)) + (0.012 × LH:FSH ratio) + (0.002 × AMH (ng/ml)) - (0.002 × BMI (kg/m²)) + (0.001 × AFC) - (0.002 × age (years)). This score was significantly correlated with OSI in the retrospective (r = 0.599; P < 0.0001) and prospective (r = 0.584; P < 0.0001) studies. In conclusion, the score including clinical and biological parameters could explain 60% of the variance in ovarian response to stimulation.