Association of ovarian response with picoAMH in women undergoing controlled ovarian hyperstimulation

Antimüllerian hormone and antral follicle count thresholds for hyperresponse risk assessment in in vitro fertilization: a Hyperresponse Risk Assessment consensus study

OBJECTIVE

To determine the serum antimüllerian hormone (AMH) and antral follicle count (AFC) thresholds indicating an increased risk of hyperresponse to ovarian stimulation (OS) during in vitro fertilization, as defined by the Hyperresponse Risk Assessment (HERA) Delphi Consensus.

DESIGN

A retrospective multicenter cohort study.

SETTING

Three fertility centers.

PATIENT(S)

Women with normal ovarian reserve markers according to the POSEIDON criteria (AMH level of ≥1.2 ng/mL and AFC of ≥5) undergoing their first in vitro fertilization/ intracytoplasmic sperm injection cycle with conventional OS (follicle-stimulating hormone [FSH] level of ≥150 IU/d) using the gonadotropin-releasing hormone antagonist protocol (2015-2017) were included.

INTERVENTION(S)

Hyperresponse was defined as ≥15 retrieved oocytes, on the basis of the HERA definition, compared with non-HERA hyperresponders, defined as patients with ovarian reserve markers within the normal range per the POSEIDON criteria and with <15 oocytes retrieved.

MAIN OUTCOME MEASURE(S)

The primary outcome was the AMH and AFC threshold values, indicating an increased risk of a hyperresponse, using receiver operator characteristic curves. Outcomes were further stratified by patients' age (<35 and ≥35 years). Multivariable logistic regression explored factors associated with an HERA hyperresponse.

RESULT(S)

A total of 4,220 patients were included, of whom 2,132 (50.5%) were hyperresponders. Receiver operator characteristic curves revealed the following thresholds for a hyperresponse: AMH level of ≥4.38 ng/mL (area under the curve [AUC], 0.71) and AFC of ≥16 (AUC, 0.80) for the entire cohort; AMH level of ≥4.95 ng/mL (AUC, 0.68) and AFC of ≥18 (AUC, 0.76) for women aged <35 years (N = 3,056); and AMH level of ≥4.33 ng/mL (AUC, 0.77) and AFC of ≥15 (AUC, 0.86) for women aged ≥35 years (N = 1,164). Older women received higher median daily and total FSH doses than younger women. The AMH, AFC, female age, daily/total gonadotropin dose, type of gonadotropin, and trigger strategy were significant predictors for hyperresponse.

CONCLUSION(S)

The AMH and AFC values at and above these thresholds warrant increased caution when planning gonadotropin dosing, regimen, and trigger strategies before OS. These thresholds were lower in older women, potentially due to higher FSH dosing in this population.

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.