大型捐贈卵子IVF(<34y) 之 PGS顯示
Euploid blastocyst 胚胎染色體正常機率為52-73%
活產率(LBR per euploid transfer) 47-58%
胚胎染色體鑲嵌Mosaic機率 2.8-11.5%
Reproductive genetics laboratory may impact euploid blastocyst and live birth rates: a comparison of 4 national laboratories' PGT-A results from vitrified donor oocytes
Published:November 29, 2022DOI:https://doi.org/10.1016/j.fertnstert.2022.10.010
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.
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