Faculty Bibliography

We investigated clinical error rates with single thawed euploid embryo transfer (STEET) diagnosed by next generation sequencing (NGS) and array comparative genomic hybridization (aCGH). A total of 1,997 STEET cycles after IVF with preimplantation genetic testing for aneuploidy (PGT-A) from 2010 to 2017 were identified; 1,151 STEET cycles utilized NGS, and 846 STEET cycles utilized aCGH. Any abortions, spontaneous or elective, in which products of conception (POCs) were collected were reviewed. Discrepancies between chorionic villus sampling, amniocentesis, or live birth results and PGT-A diagnosis were also included. Primary outcomes were clinical error rate per: ET, pregnancy with gestational sac, live birth, and spontaneous abortion with POCs available for analysis. Secondary outcomes included implantation rate (IR), spontaneous abortion rate (SABR), and ongoing pregnancy/live birth rate (OPR/LBR). The clinical error rates in the NGS cohort were: 0.7% per embryo, 1% per pregnancy with gestational sac, and 0.1% rate per OP/LB. The error rate per SAB with POCs was 13.3%. The IR was 69.1%, the OPR/LBR was 61.6%, and the spontaneous abortion rate was 10.2%. The clinical error rates in the aCGH cohort were: 1.3% per embryo, 2% per pregnancy with gestational sac, and 0.4% rate per OP/LB. The error rate per SAB with POCs was 23.3%. The IR was 63.8%, the OPR/LBR was 54.6%, and the SAB rate was 12.4%. Our findings demonstrate that, although NGS and aCGH are sensitive platforms for PGT-A, errors still occur. Appropriate patient counseling and routine prenatal screening are recommended for all patients undergoing IVF/PGT-A.

Objective: Morphologic grading of embryos has been an ART standard for nearly 4 decades. More recently, PGT-A has improved embryo selection. Data conflicts regarding whether morphological evaluation improves outcomes of euploid embryo transfers [1, 2, 3]. Our objective was to determine whether morphology is predictive of pregnancy outcomes among single thawed euploid embryo transfers (STEETs).
Design(s): Retrospective cohort study.
Material(s) and Method(s): We reviewed all STEETs at a university-based ART center from 2014-2018. STEETs were excluded if oocytes were cryopreserved, embryos were created at another facility, embryos were frozen or biopsied twice, PGT-M or -SR was used, or an oocyte donor or gestational carrier was used. Only the first STEET during the study period that did not meet any exclusion criterion from each patient was included. Embryo morphology was graded according to Gardner [4]. Outcomes included implantation rate of all transfers and live birth (LB) rate, excluding 154 ongoing pregnancies and 28 pregnancies with unknown birth outcomes. Statistical analysis included chi-square, one-way ANOVA, and 2 multivariable log-binomial regression models to determine the association of predictors (age, expansion, ICM, TE) with implantation and LB.
Result(s): We reviewed 1323 STEETs (mean age 37y; range 24-46y). Overall, implantation was 69% and LB (n=1141) was 55%. ICM and TE were bivariately associated with both implantation and LB (p<0.01), but age and expansion were not. ICM significantly predicted implantation, but TE did not. Both ICM and TE independently predicted LB (see Table for adjusted predicted probabilities of implantation and LB based on ICM and TE grades at mean levels of all covariates in the models).
Conclusion(s): Ploidy status is not the sole determinant of embryo competence. ICM and TE are strong predictors of LB and can improve selection among euploid embryos. Poor ICM is the greatest negative morphological predictor of implantation and LB. Our model can serve as a counseling tool for patients banking embryos. [Figure presented] References: 1) Chen, M., et al. (2015). "Can Comprehensive Chromosome Screening Technology Improve IVF/ICSI Outcomes? A Meta-Analysis." PLoS One10(10): e0140779. 2) Capalbo, A., et al. (2014). "Correlation between standard blastocyst morphology, euploidy and implantation: an observational study in two centers involving 956 screened blastocysts." Hum Reprod29(6): 1173-1181. 3) Irani, M., et al. (2017). "Morphologic grading of euploid blastocysts influences implantation and ongoing pregnancy rates." Fertil Steril107(3): 664-670. 4) Gardner DK, Lane M, Stevens J, Schlenker T, Schoolcraft WB. Blastocyst score affects implantation and pregnancy outcome: towards a single blastocyst transfer. Fertility and Sterility (2000) 73 (6):1155-1158.
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Objective Improvements in oocyte cryopreservation(OC) have led to successful oocyte banking and more readily available cryopreserved donor oocytes(DO). Simultaneously, preimplantation genetic screening(PGS) has increased, even with DO. Using OC, DO, and PGS together is less common, but now occurs. Reservations include increased technological and financial cost ($1,100/oocyte). Our goal was to determine whether adding PGS increases implantation and live birth rates in DOT. Design Retrospective cohort study. Material and Methods We conducted a retrospective analysis of DOT performed 10/2004-1/2017 at a university-based fertility center. To remove bias, we conducted a sub-analysis of single embryo transfers(SET). Data was mined for: number of oocytes thawed/survived/fertilized, embryo development/transfer/implantation, and ongoing pregnancy/live birth. Mood's median and Fischer's exact tests were used for statistical analysis. Results Within the 130 non-PGS DOT (118 pts, median age:26y), 1138 oocytes (median:8/cycle) were thawed. Within the 15 PGS DOT (15 pts, median age:24y), 180 oocytes (median:11/cycle) were thawed a mean of 3 blastocysts(BL) were biopsied. Oocyte survival, 2-PN fertilization, BL formation, implantation, and ongoing pregnancy/live birth rates were not significantly different between the groups. The multiple birth rate in the non-PGS group was 6% (5/84 births). When controlling for SET, no differences were found in implantation or ongoing pregnancy/live birth rates with and without PGS (p>.1). When comparing embryo quality in the non-PGS group, a higher ongoing pregnancy/live birth rate was noted among SETs with excellent-quality Gardner's >2Bb (62% 50 births/81 transfers) when compared with SETs with poor-quality Gardner's <2Bb (35% 8 births/23 transfers p=.03). Conclusions Due to this study's small sample size, it is difficult to conclude whether PGS improves implantation/live birth rates in a young donor population. In DO cycles with excellent-quality BL for transfer, morphology alone predicts a high live birth rate. Given the financial and technological burden of PGS, larger studies are needed to determine whether the costs of PGS outweigh the benefits in DO cycles