Optimal antimüllerian hormone levels in oocyte donors: a national database analysis.

OBJECTIVE: To study the relationship between high antimüllerian hormone (AMH) levels in oocyte donors and embryo development and pregnancy outcomes among donor oocyte recipients. DESIGN: Retrospective cohort study. SETTING: Donor Egg Bank Database. PATIENTS: Patients undergoing in vitro fertilization using vitrified donor oocytes from 35 in vitro fertilization centers in the United States between 2013 and 2021. For each recipient, the first oocyte lot that was received with a planned insemination and embryo transfer (ET) was included. INTERVENTION: Oocyte donor-recipient cycles. MAIN OUTCOME MEASURES: Ongoing pregnancy rate (OPR) per ET. RESULTS: A total of 3,871 donor oocyte-recipient thaw cycles were analyzed. On the basis of donor AMH serum concentration, cycles were stratified into the high AMH group (AMH ≥5 ng/mL; n = 1,821) and the referent group (AMH <5 ng/mL; n = 2,050). Generalized estimating equation models were used to account for donors that contributed more than one lot of oocytes. The number of usable embryos per lot (median [interquartile range]) was significantly increased in the high AMH group (2 [2-4]) compared with the referent group (2 [1-3]) (relative risk [RR] 1.06; confidence interval [CI] 1.01-1.12). Among recipients with a planned ET, there was no difference in OPR between the high AMH group (45.4%) and the referent group (43.5%) (RR 1.04; 95% CI 0.94-1.15). Among preimplantation genetic testing for aneuploidy cycles, the embryo euploidy rate per biopsy was similar at 66.7% (50%-100%) in both groups (RR 1.04; CI 0.92-1.17). The OPR per euploid ET among patients who used preimplantation genetic testing for aneuploidy was also comparable, at 52% in the high AMH group and 54.1% in the referent group (RR 0.95; CI 0.74-1.23). CONCLUSION: This large national database study observed that there was no association between a high level of AMH (≥5 ng/mL) in oocyte donors and an OPR in the recipient after the first ET. On the basis of these findings, recipients and physicians can be reassured that oocyte donors with a high AMH level can be expected to produce outcomes that are at least as good as donors with an AMH level (<5 ng/mL).

Reproductive genetics laboratory may impact euploid blastocyst and live birth rates: a comparison of 4 national laboratories' PGT-A results from vitrified donor oocytes.

OBJECTIVE: To evaluate potential variation in the euploid blastocyst rate and live birth rate (LBR) per single frozen euploid blastocyst transfer, among 4 unique United States reproductive genetics laboratories. Analyses were limited to blastocysts derived from vitrified donor oocytes, to minimize variation in oocyte quality. DESIGN: Retrospective cohort study from 2016 to 2020. SETTING: Donor Egg Bank Database. PATIENT(S): Patients undergoing in vitro fertilization with donor oocytes. We excluded patients with uterine factor, male factor, or surgically extracted sperm. Only healthy women <34 years old were accepted as oocyte donors. INTERVENTION(S): Next generation sequencing platforms for chromosomal analysis MAIN OUTCOME MEASURE(S): Euploid blastocyst rate and LBR per euploid transfer. Secondary outcomes included the rate of aneuploidy, mosaic calls, biochemical pregnancy loss, and miscarriage rate. RESULT(S): A total of 2,633 embryos were included. Four laboratories had >200 embryos tested. Euploid blastocyst rate was significantly higher in laboratory A (73.6%) vs. B (63.3%), C (60.9%), and D (52.3%). Mosaic rate was significantly lower for Laboratories B (2.8%) and C (5.5%) vs. Laboratories A (9.9%) and D (11.5). The LBR was significantly higher in laboratory A (58.73%) vs. laboratory D (47.3%). There were no significant differences in the implantation or miscarriage rate among laboratories. CONCLUSION(S): In this large study, controlling for oocyte quality, some preimplantation genetic testing for aneuploidy (PGT-A) laboratories report a significantly higher euploid blastocyst rate with concurrent higher LBR. This type of comparison is important as it provides insight into the role of the PGT-A process in outcomes. Further research is needed to evaluate the differences in laboratory techniques and bioinformatic algorithms accounting for variable outcomes across PGT-A laboratories.