Abstract
Purpose
To evaluate the utilization of single-embryo transfer (SET) and preimplantation genetic testing (PGT) in gestational carrier IVF cycles in the USA with donor oocyte and examine the impact on live birth and multiple gestation.
Methods
Retrospective cohort study using the Society of Assisted Reproductive Technology (SART) clinic database of 4776 donor oocyte–recipient IVF cycles in which a GC was used. The cycles were separated into 4 groups by use of PGT and number of embryos transferred as follows: (1) PGT and single-embryo transfer (PGT-SET); (2) PGT and multiple embryo transfer (PGT-MET); (3) no PGT and SET (NoPGT-SET); (4) no PGT and MET (NoPGT-MET). Primary outcomes were live birth rate (LBR) and multiple pregnancy rate (MPR).
Results
More than one blastocyst was transferred in 48.7% (2323/4774) of the cycles. When ≥1 blastocyst was transferred, with or without the use of PGT, the MPR was 45.5% and 42.0%, respectively. In comparison, in the PGT-SET and NoPGT-SET groups, the MPR was 1.4% (8/579) and 3.3% (29/883), respectively. Live birth rates increased with the use of PGT-A and with MET.
Conclusion
This study shows that SET, with or without PGT, is associated with a significantly reduced MPR in donor oocyte–recipient GC IVF cycles while maintaining high LBR. It also demonstrates that many infertility centers in the USA are not adhering to ASRM embryo transfer guidelines. Our findings highlight an opportunity to increase GC safety, which ultimately may lead to widened access to this increasingly restricted service outside the USA.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10815-021-02112-5.
Keywords: Gestational carrier, Oocyte donation, In vitro fertilization, Single-embryo transfer, Preimplantation genetic testing
Introduction
Gestational carriers (GCs) are most often used by same sex couples or women with uterine factors or serious medical conditions that preclude them from carrying pregnancies on their own [1]. Given the improvements in pregnancy outcomes with IVF, GCs are being increasingly utilized as they present a viable alternative to adoption with the addition of allowing the intended parents to potentially maintain a genetic link with their offspring. In the case of same sex male couples, as well as in cases of women with advancing maternal age and decreased ovarian reserve, oocyte donation is typically utilized in addition to a GC. In the USA alone, involvement of GCs in IVF cycles has increased over 3-fold between 2008 and 2015, from 1 to 3.5% of all cycles [2].
It is also important to underscore that at this time, the USA is one of the few industrialized nations that permits compensated GC cycles [3]. Given these restrictions abroad, many non-US citizens travel to the USA for GCs. In fact, the number of IVF cycles done by non-US residents has increased from 2% in 2005 to 19% in 2013 [2]. With regard to cross-border reproduction, there are concerns that potential GCs are solicited from vulnerable groups of women who may accept the risks of surrogacy due to the financial incentive. While such reservations are reasonable, they also underscore the need to prioritize GC safety to help preserve the invaluable service these women provide.
GCs are typically selected based on their prior normal obstetric history. However, IVF adds unique medical and psychologic risks to the GC pregnancy. Multiple studies have shown that even in singleton IVF pregnancies, there is increased risk of obstetric complications, most notably hypertensive disorders of pregnancy [4–7]. However, much of the risk results from multiple gestations due to the transfer of more than one embryo, which is commonly performed in GC IVF cycles [2, 8]. It is widely accepted that multiple gestation is associated with increased neonatal risk of preterm deliveries, spontaneous abortion, intrauterine fetal demise, cerebral palsy, and congenital birth defects [9]. Multiple gestation also is associated with higher maternal risks, including increased risk of hypertension, cesarean section, postpartum hemorrhage, and maternal death when compared to singleton pregnancies [10–15]. GCs who undergo MET are similarly not exempt from these risks.
Due to the high cost of GC IVF cycles, especially in cases in which donor oocytes are being used, it is understandable why intended parents may be tempted to transfer multiple embryos. Thus, the challenge lies in how to convince intended parents to accept SET. PGT for aneuploidy and blastocyst culture has significantly improved the process of embryo selection. These advancements have also made SET a more favorable option, thereby reducing complications associated with multiple gestations without compromising LBRs [16, 17]. In cases of anonymous oocyte donation, in which LBR correlates with the age of the donor rather than the recipient and approaches 60% in many US fertility centers, one could argue that PGT should not be recommended for the marginal increase in LBR it brings [18]. Nonetheless, the standard use of PGT may still present a logical and effective way for some couples to prioritize GC safety by making SET an acceptable option for intended parents given the excellent reported LBRs [19, 20].
The purpose of this study was to perform an analysis of the SART CORS database to evaluate the current use of PGT and SET in GC IVF cycles utilizing oocyte donation in the USA. We sought to identify the differences in pregnancy outcomes, notably multiple pregnancy rate and live birth rate, in GC IVF cycles stratified by the use of PGT and number of embryos transferred. We hypothesized that the use of PGT and SET would result in a significant reduction in the incidence of multiple gestation, while still preserving a high live birth rate.
Materials and methods
This was a retrospective cohort study approved by the Research Committee of the Society of Assisted Reproductive Technology. De-identified patient data were obtained from SART CORS for reporting years 2014–2016. The SART CORS contains comprehensive data from >80% of all IVF clinics and of >90% of all IVF cycles conducted in the USA. Reporting to the CDC through SART CORS is required under the Fertility Clinic Success Rate and Certification Act of 1992. Approximately 10% of the clinics are audited each year in order to validate the accuracy of the reported data. This study was also submitted to our university’s IRB for human subject determination. Given that all data was de-identified, it was deemed as not meeting criteria for human subject research and therefore did not require IRB approval.
A total of 19,055 cycles were screened for inclusion. Donor oocyte–recipient cycles were included if embryo transfer was attempted, status of whether PGT was or was not done was known, and the pregnancy/treatment outcome was known. Cycles were excluded if autologous oocytes were used, transfer was not attempted, cleavage stage embryo(s) were transferred, and/or if only some but not all of the embryos created from a single cycle were biopsied for PGT. Autologous oocyte GC IVF cycle was excluded from this analysis due to concerns regarding the reliability of these data.
For the analysis, cycles were categorized into four groups: cycles in which (1) PGT and SET was done (PGT-SET); (2) PGT and MET was done (PGT-MET); (3) no PGT and SET was done (NoPGT-SET); (4) and no PGT and MET was done (NoPGT-MET).
Baseline cycle and demographic information was limited for oocyte donation cycles and included oocyte donor age, GC age, mean number of embryos transferred, and proportion of cycles using fresh versus thawed donor oocytes.
The primary outcomes were live birth rate (LBR) and multiple pregnancy rate (MPR). Secondary outcomes were clinical pregnancy rate (CPR) and clinical loss rate (CLR). Pregnancy outcomes were defined according to SART CORS criteria. A live birth was a cycle that resulted in at least one live-born infant. Clinical pregnancy was defined as evidence of pregnancy by ultrasound visualization of a gestational sac (excluding ectopic and biochemical pregnancies). Clinical loss was defined as a clinical pregnancy that did not result in a delivery.
Lastly, post hoc subgroup analyses were conducted stratifying data by use of fresh versus thawed oocytes as well as performance of fresh versus frozen-thawed embryo transfer (FET). We also performed a subgroup analysis limited to cycles in which intended parents had a male factor infertility diagnosis.
Statistical analysis
Statistical analyses were performed using IBM SPSS© Statistics version 26.0 (IBM; Armonk, NY). Descriptive statistics was comprised of means and standard deviations for continuous variables. Categorical variables were presented as counts and percentages.
Student’s t test was used for two-group comparisons of normally distributed, continuous variables. Analysis of variance (ANOVA) with post hoc Scheffé’s multiple range test was used for comparisons of normally distributed, continuous variables between more than two groups, while the Kruskal-Wallis H test was used for non-normally distributed variables. Chi-square tests were used for comparisons of categorical variables.
Crude odds ratios and 95% confidence intervals were also calculated. A two-sided p-value of <0.05 was considered statistically significant.
Results
A total of 4776 donor oocyte IVF cycles from the SART database in which GCs were used were ultimately included for analysis. There were 905 cycles in the PGT-SET group, 654 in the PGT-MET group, 1546 in the NoPGT-SET group, and 1671 in the NoPGT-MET group.
More than one blastocyst was transferred in 48.7% (2323/4774) of the cycles. Overall, a mean number of 1.5 ± 0.5 embryos were transferred. There was transfer of two embryos in 47.1% (2247/4776) of cycles and transfer of three or more embryos in 1.5% (76/4776) of cycles. Preimplantation genetic testing for aneuploidy (PGT-A) was done in 53.2% (829/1559) of cycles and PGT for other indications including single-gene disorders, and HLA testing or structural rearrangements were done in 33.9% (528/1559) of PGT cycles. The indication for PGT was unknown in 13.0% (202/1559) of cycles.
Limited baseline cycle and demographic information were available for donor oocyte–recipient GC cycles, which is shown in Table 1. Donor oocyte groups did significantly differ in terms of mean GC age. However, oocyte donor age did not significantly differ between groups (p=0.22). In MET groups, fewer embryos were transferred when PGT was used (2.0 ± 0.1 (PGT-MET) versus 2.1 ± 0.3 (NoPGT-MET), p<0.001). Thawed donor oocytes were used significantly more often in the NoPGT groups than in PGT groups (p<0.001), but the majority of cycles included in our analysis used fresh donor oocytes.
Table 1.
Baseline cycle and demographic characteristics for donor oocyte–recipient GC cycles
| PGT-SET (n=905) | PGT-MET (n=654) | NoPGT-SET (n=1546) | NoPGT-MET (n=1671) | p value | |
|---|---|---|---|---|---|
| Oocyte donor age, years (mean ± SD) | 25.8 ± 3.2 | 26.1 ± 3.3 | 26.1 ± 3.6 | 25.8 ± 3.5 | 0.22 |
| GC age, years (mean ± SD) | 31.1 ± 5.0 (a) | 30.9 ± 4.9 (a) | 31.8 ± 5.0 (b) | 31.9 ± 5.3 (b) | <0.001 |
| Thawed oocyte (%, n) | 0.4% (4/905) (a) | 0.2% (1/654) (a) | 6.5% (101/1546) (b) | 6.0% (101/1671) (b) | <0.001 |
Letters (a–d) indicate significant differences between groups
GC, gestational carrier; PGT-SET, preimplantion genetic testing with single-embryo transfer; PGT-MET, preimplantation genetic testing with multiple embryo transfer; NoPGT-SET, no preimplantation genetic testing and single-embryo transfer; NoPGT-MET, no preimplantation genetic testing and multiple embryo transfer
MPR was highest in the PGT-MET group (45.6% (236/518)) followed by the NoPGT-MET group (41.5% (464/1119); p<0.001). MPR was significantly lower in the SET groups: 1.4% (8/579) in the PGT-SET group and 3.3% (29/883) in the NoPGT-SET group; these two groups did not significantly differ from each other. The odds of multiple gestation in comparison to the PGT-MET group was 0.68 (95% CI 0.56–0.83, p<0.001) in the NoPGT-MET group, 0.02 (95% CI 0.01–0.03, p<0.001) in the PGT-SET group, and 0.03 (95% CI 0.02–0.05, p<0.001) in the NoPGT-SET group.
All groups significantly differed from each other in terms of LBR (p<0.001). LBR was highest in the PGT-MET group (70.0% (458/654)). This was followed by the NoPGT-MET group (58.8% (983/1671)) and then the PGT-SET group (54.4% (492/905)). The lowest LBR was in the NoPGT-SET group (47.3% (732/1546)). The odds of live birth in comparison to the PGT-MET group was 0.61 (95% CI 0.50–0.74, p<0.001) in the NoPGT-MET group, 0.51 (95% CI 0.41–0.63, p<0.001) in the PGT-SET group, and 0.39 (95% CI 0.32–0.47 p<0.001) in the NoPGT-SET group. The results for MPR and LBR across groups are depicted in Fig. 1.
Fig. 1.
Live birth rate and multiple pregnancy rate by group in donor oocyte recipient gestational carrier IVF cycles
Similar findings were seen with CPR. Again, CPR was highest in the PGT-MET group (79.2% (518/654)). This was followed by the NoPGT-MET group (67.0% (1119/1671)) and then the PGT-SET group (64.0% (579/905)), which did not significantly differ from each other. The CPR was lowest in the NoPGT-SET group (57.1% (883/1546); p<0.001). The odds of clinical pregnancy in comparison to the PGT-MET group was 0.53 (95% CI 0.43–0.66, p<0.001) in the NoPGT-MET group, 0.47 (95% CI 0.37–0.59, p<0.001) in the PGT-SET group, and 0.34 (95% CI 0.28–0.43, p<0001) in the NoPGT-SET group.
CLR did not significantly differ across groups. All aforementioned outcomes are shown in Table 2.
Table 2.
Pregnancy outcomes by group for donor oocyte recipient GC IVF cycles
| Pregnancy outcome | PGT-SET | PGT-MET | NoPGT-SET | NoPGT-MET | p value |
|---|---|---|---|---|---|
| CPR (%, n) | 64.0% (a) (579/905) | 79.2% (b) (518/654) | 57.1% (c) (883/1546) | 67.0% (a) (1119/1671) | <0.001 |
| LBR (%, n) | 54.5% (a) (492/905) | 70.0% (b) (458/654) | 47.3% (c) (732/1546) | 58.8% (d) (983/1671) | <0.001 |
| CLR (%,n) | 15.0% (87/579) | 11.6% (60/518) | 17.1% (151/883) | 12.1% (135/1119) | 0.36 |
| MPR (%, n) | 1.4% (a) (8/579) | 45.6% (b) (236/518) | 3.3% (a) (29/883) | 41.5% (c) (464/1119) | <0.001 |
Letters (a–d) indicate significant differences between groups
GC, gestational carrier; PGT-SET, preimplantion genetic testing with single-embryo transfer; PGT-MET, preimplantation genetic testing with multiple embryo transfer; NoPGT-SET, no preimplantation genetic testing and single-embryo transfer; NoPGT-MET, no preimplantation genetic testing and multiple embryo transfer; CPR, clinical pregnancy rate; LBR, live birth rate; CLR, clinical loss rate; MPR, multiple pregnancy rate
Lastly, there were 10 pregnancies that yielded high order multiples (HOM), 3 in the PGT-MET group, and 7 in the NoPGT-MET group.
In the post hoc subgroup analysis of groups stratified by fresh versus thawed oocytes, as stated above, the majority of cycles used fresh donor oocytes. There remained significantly higher MPR among PGT-MET and NoPGT-MET groups compared to PGT-SET and NoPGT-SET groups (p<0.01). Similarly, LBR remained highest in the PGT-MET group (70.0%), followed by the NoPGT-MET group (59.0%), PGT-SET group (54.5%), and then the NoPGT-SET group (47.3%) (p<0.01). These results are shown in supplementary table 1.
In a second post hoc subgroup analysis of groups stratified by performance of fresh versus frozen-thawed embryo transfer, there again remained significantly higher MPR among PGT-MET and NoPGT-MET groups compared to the PGT-SET and NoPGT-SET groups for both fresh embryo transfers and FETs (p<0.01). Similarly, among FET cycles, LBR was highest in the PGT-MET group (70.1%), followed by the PGT-SET (54.6%) and NoPGT-MET (54.4%) groups which did not significantly differ from each other, and then the NoPGT-SET group (43.5%), p<0.01. These results are shown in supplementary table 2.
In a final post hoc subgroup analysis, we limited the cohort to only those cycles in which the intended parents carried a diagnosis of male factor infertility. There was a significant difference between groups in the diagnosis of male factor infertility with the highest proportions seen in the PGT-SET group (8.2% (74/905)) and NoPGT-MET group (8.8% (147/1671)), followed by the NoPGT-SET group (7.2% (111/1546)), and finally the PGT-MET group (5.2% (34/564); p=0.02). When analysis was restricted to cycles with male factor diagnosis, there was no significant difference seen between groups in CPR or CLR. There was also no significant difference between groups in LBR (PGT-SET 55.4% (41/74), PGT-MET 58.8% (20/34), NoPGT-SET 43.2% (48/111), NoPGT-MET 57.1% (84/147); p=0.12). With regard to MPR, there remained a clinically relevant significant difference between the SET groups (PGT-SET 0.0% (0/49), NoPGT-SET 1.6% (1/61)) and MET groups (PGT-MET 41.7% (10/24), NoPGT-MET 44.3% (43/97); p<0.01) in regard to MPR.
Discussion
This study demonstrates that the use of SET, with or without the use of PGT, increases the safety of IVF for GCs by significantly reducing the risk of multiple gestations. It also results in excellent live birth rates of approximately 50% in donor oocyte–recipient GC IVF cycles. In addition, our results highlight that nearly half of the included IVF cycles involved transfer of more than one blastocyst in donor oocyte GC IVF cycles, which conflicts with current ASRM guidelines on criteria for number of embryos to transfer [21].
Our results demonstrate that SET live birth outcomes are excellent with or without the use of PGT in donor oocyte GC IVF cycles. However, the LBR was highest in the PGT-MET group (70.0%), but at the cost of an exceptionally high MPR (45.6%). This is particularly notable in comparison to the very low MPR in the SET groups. While LBR in the PGT-SET group (54.5%) was significantly lower in comparison to the PGT-MET group, it was still respectable, and the MPR was only 1.4%. Similarly, in the LBR for the NoPGT-SET group (47.3%) was significantly lower than the PGT-SET group, the MPR remained low for both groups, 3.3% and 1.4%, respectively. Previous literature has been mixed about the benefit of PGT in donor oocyte IVF cycles. An earlier study with SART data from 2005 to 2013 showed no significant difference in LBR with or without PGT in donor oocyte–recipient cycles [22]. In contrast, a more recent SART analysis showed a slight significant improvement in good birth outcomes in donor oocyte frozen-embryo transfer cycles with PGT (RR 1.12, 95% CI 1.02–1.22, p=0.02) [23]. To determine the cost-effectiveness of PGT in donor oocyte IVF cycles, Antero et al. (2020) showed that on average approximately $120,000 was required to achieve an additional live birth with the addition of PGT to donor oocyte cycles. This cost includes the cost of monitoring, IVF, donor oocytes, PGT, and medical and legal fees. Still, our data shows that PGT may offer a slight advantage in LBR in donor-recipient GC IVF cycles [24]. Thus, despite the additional cost of PGT, it represents a potentially powerful means to encourage SET use in GC IVF cycles.
This study also brings to light that more than one blastocyst was transferred in nearly 50% of the cycles included in our analysis. Our results agree with prior research on the subject. In an outcomes survey of CDC National ART Surveillance System data, Perkins et al. (2016) determined that among 30,297 GC IVF cycles reviewed between 1999 and 2013, 78.6% had more than one embryo transferred with an average of 2.1 embryos transferred per cycle. This study also reported that of the 13,380 deliveries from GC cycles, 34% were twins and 2% were HOM [2]. Similar results were reported by another group using SART CORS data from 2004 to 2013 of autologous GC IVF cycles, with rates of twins nearly representing a third of the live births and HOM representing 1.3% [25]. Our findings and these previous studies elucidate that many clinics are not following current ASRM and SART’s guidelines for embryo transfer, which states, “In patients of any age, transfer of a euploid embryo has the most favorable prognosis and should be limited to one” as well as “In donor oocyte cycles, the age of the donor should be used to determine the appropriate number of embryos to transfer. For example, when the donor is <35 years of age and other favorable criteria exist, single-embryo transfer should be planned.” [21] Granted, our data is from the time period preceding the most recent ASRM guidelines on criteria for number of embryos to transfer. However, even the earlier guidelines stated that in donor-egg cycles, the age of the donor should determine the appropriate number of embryos to transfer, which in most cases is less than 35 years [26]. Unsurprisingly, the high MPR in the MET groups in this study emphasizes the very need for these ASRM guidelines.
There is an obvious disparity when comparing the significantly higher multiple pregnancy rate seen in these donor oocyte–recipient GC IVF cycles with MET to that of naturally conceived pregnancies in the USA, which have an incidence of twins and higher order multiples (HOM) of 1.5% and 0.03%, respectively [27]. There are also data which further support that birth outcomes following SET are equivalent to those following naturally conceived singleton pregnancies [19, 28]. In addition, due to the increased incidence of multiples, there are increased maternal and neonatal complications including higher rates of infant prematurity (with its associated co-morbidities), fetal growth restriction, and neonatal mortality [9]. Furthermore, there are reports of catastrophic complications in the setting of multiple gestation in GC IVF cycles, such as a case of postpartum hysterectomy due to placenta accreta in a triplet pregnancy. In this case, the GC sustained multiple cerebral infarcts and blindness while one triplet also died secondary to complications of prematurity [29]. Finally, it is worth noting that multiples also cost the healthcare system. The average cost of a delivery with a singleton in the USA is $21,458 compared to $104,831 for twins and $407,199 for triplets, which is likely due to the high risk of preterm delivery in multiple gestations and the resulting complications leading to NICU admission [30]. Yet, despite these facts, the challenge remains in convincing intended parents to accept SET.
The results of this study highlight a need for strategies to better promote SET in IVF centers among GCs. Should IVF centers make internal policies that prohibit MET in donor oocyte–recipient GC IVF cycles? Should ASRM enforce its policies using program review letters highlighting practice deviations, as it does to prevent high order multiples with autologous IVF? Our data strongly suggest that these discussions are warranted. Instituting a mandatory SET policy can dramatically reduce MPR without impacting LBR [31]. However, short of that, other tactics need to be considered. Clinics may consider more unified counseling from health professionals, the use of prediction tools, and provision of educational materials that contain testimonials from parents with twins or multiples [19]. Studies indicate providing simple educational materials to improve knowledge of the risks of multiple pregnancies may lead to better patient acceptance of SET [32]. Additionally, providers may decide to promote PGT as a way to balance the goals of the GC and the intended parents as transfer of PGT tested single euploid embryo, screened with modern molecular technologies such as next-generation sequencing, yields comparable live birth rates to MET regardless of the oocyte’s chronologic age [33]. One may argue that PGT should not be recommended for IVF cycles utilizing anonymous oocyte donation, given multiple studies have not shown significant improvements in LBR with the addition of PGT [22, 23, 34, 35]. Yet, as evidenced by the high occurrence of MET and resulting MPR in the GC IVF cycles analyzed in this study as well as the slight improvement in LBR with PGT in SET cycles, it may be more strongly considered for GC IVF cycles utilizing oocyte donation in order to make SET a more suitable choice.
The volume of donor oocyte–recipient GC IVF cycles evaluated underscores one of the greatest strengths of our study. The SART CORS database includes IVF cycles performed at over 400 IVF centers in the USA. Our analysis is also restricted to only cycles from 2014 to 2016; therefore, it is likely that the results reflect modern practice such as use of vitrification and current molecular techniques for PGT. Conversely, it also introduces some limitations to our study. Unfortunately, we are limited by what information is requested by SART from IVF centers. There are also missing data for some of the variables collected, which may bias our results. As stated earlier, only a limited number of baseline characteristics for donor oocyte–recipient GC cycles were available for analysis. We believe that oocyte donors and gestational carriers are generally from a pool of young and healthy women without significant past medical history; however, it remains an assumption that could bias our results. Additionally, while maternal baseline characteristics were controlled for by the use of a presumably healthy gestational carrier and oocyte donor, little was known regarding the intended male partner such as paternal age. We did perform a subgroup analysis for male factor infertility and there was not a difference in LBR between groups. However, this result is likely limited by small sample size. Similarly, indication for PGT may have impacted the results, but only a very small percentage of patients were designated as undergoing PGT-M (0.9%). However, this may be an accurate reflection of the cohort as one would not expect a significant number of oocyte donors to be carriers or have a family history of genetic disorders as those candidates are typically not eligible. Finally, we do not have information about maternal and neonatal outcomes, which would be important endpoints to consider.
Furthermore, when collecting such a large sum of data from IVF centers across the USA, some variables may be inconsistently reported. For example, in supplementary table 2, in the subgroup analysis of fresh ET versus FET cycles, we find that fresh transfers were performed in only 5.1% (81/1559) of PGT cycles. Given that PGT-tested embryos are typically cryopreserved and transferred in subsequent FET cycles, the 5% of cycles with fresh transfer may reflect data from clinics that have on site genetic testing capability or may reflect inaccuracies in data reporting.
Although the data on one hand represent a more generalizable view of IVF outcomes across the USA, there is likely marked variability between practice patterns, embryology lab procedures, and outcomes from center to center. For example, the LBR in donor oocyte cycles is slightly lower than what has been reported in previous studies. Similarly, CLR is significantly higher with transfer of euploid blastocysts than we have found in our own center’s data. We do not have information regarding specifically how many cycles came from each individual IVF clinic that reported to SART, but it is possible that if cycles analyzed in this study originated from a small number of select clinics, that could skew some of the trends we have described. It may also explain why so few cycles utilized thawed donor oocytes, as shown in the subgroup analysis (supplementary table 1). Yet, it is more likely that our results reflect the variability in the large number of centers that report to SART.
Conclusions
In conclusion, the results of this study support that single-embryo transfer, with or without PGT, is a highly effective method of reducing multiple pregnancy rate in donor-egg recipient gestational carrier IVF cycles. In intended parents, who are keen to maximize their odds of live birth and avoid paying for additional cycles, SET with PGT presents a solution that allows intended parents to maximize their chances of success without jeopardizing the health of the GC.
Supplementary Information
(DOCX 13 kb)
(DOCX 14 kb)
Acknowledgements
We would like to thank the physicians and nursing staff at CARS for their support.
Availability of data and material
The data underlying this article will be shared on reasonable request to the corresponding author.
Code availability
Not applicable.
Authors’ contribution
R Makhijani: participated in study conception and design and execution, data analysis, manuscript drafting and critical discussion, and final approval of manuscript.
M Coulter: participated in study conception and design, critical discussion, and final approval of manuscript.
A Taggar: participated in study conception and design, critical discussion, and final approval of manuscript.
P Godiwala: participated in study conception and design, critical discussion, and final approval of manuscript.
D O’Sullivan: participated in study conception and design, data analysis, critical discussion, and final approval of manuscript.
J Nulsen: participated in study conception and design, critical discussion, and final approval of manuscript.
L Engmann: participated in study conception and design, critical discussion, and final approval of manuscript.
C Benadiva: participated in study conception and design, critical discussion, and final approval of manuscript.
D Grow: participated in study conception and design and execution, data analysis, manuscript drafting and critical discussion, and final approval of manuscript.
All authors approved the final version and agree to be accountable for all aspects of the work.
Declarations
Ethics approval
This study was deemed as not meeting criteria for human subject research and therefore did not require IRB approval.
Consent to participate
Not applicable.
Conflict of interest
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.