Predicting IVF outcome in poor ovarian responders

doi:10.21203/rs.3.rs-1735403/v1

Download PDF

Research Article

Predicting IVF outcome in poor ovarian responders

https://doi.org/10.21203/rs.3.rs-1735403/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background

Poor responders to ovarian stimulation are one of the most challenging populations to treat. As a failed cycle can cause a considerable emotional and economical loss, adequate fertility counseling addressing patients’ expectations are highly important when facing patients with poor ovarian response. The study aimed to evaluate reproductive outcomes and to identify factors associated with live birth (LB) after fresh autologous IVF/ intracytoplasmic sperm injection (ICSI) cycles of patients fulfilling the Bologna criteria for poor ovarian response (POR).

Methods

A retrospective study included 751 IVF/ICSI treatment cycles which yielded up to three retrieved oocytes, at a tertiary referral hospital between January 2016 to February 2020. A logistic regression analysis was used to adjust for confounders.

Results

Clinical pregnancy and LB rate per cycle were significantly higher among women younger versus older than 40 years (9.8% and 6.8% versus 4.5% and 2.1%, p < 0.01, respectively). Patients who achieved LB were significantly younger, had higher number of oocytes retrieved, fertilization rate and top-quality embryos (P < 0.05). Multivariable regression analysis identified patient’s age (OR 0.90; 95% CI 0.845 to 0.97; p = 0.005) and mean number retrieved oocytes (OR 1.95; 95% CI 1.20 to 3.16; p = 0.007) as factors significantly associated with the probability of a LB.

Conclusions

The woman’s age and the number of retrieved oocytes are both independent predicting factors of live birth in poor ovarian responders. Considering the risks, the high financial investment and poor reproductive outcomes involved in IVF treatments, raises questions regarding the adequacy of providing treatments in these patients' population. POR younger than 40 years may represent a possible exception due to acceptable probability for a LB.

In vitro fertilization

poor ovarian response

live birth

Bologna criteria

Ovarian stimulation (OS) plays a central role in the success of in vitro fertilization (IVF) cycles. The goal of OS is to recruit and develop multiple dominant follicles. This may lead to the retrieval of many oocytes which allows many potential embryos for transfer[1]. Overall, between 10–15 oocytes are considered to be the optimal ovarian response following OS[2]. Despite great advances in assisted reproductive technology (ART), treating patients with poor ovarian response (POR) is still considered a major challenge in reproductive medicine. POR patients are less likely to conceive and moreover, will have higher risk of cycle cancellation. The definition of POR has been standardized in the Bologna criteria established by the European Society of Human Reproduction and Embryology (ESHRE) in 2011[3].

Due to the heterogeneous risk factors for POR, there is a wide variability in the incidence, estimated to be between 9%-24% of patients undergoing OS for IVF [4, 5]. However, with the persistent and pronounced trend towards delayed childbearing across the western world, the incidence may be slightly higher.

Several OS protocols have been proposed for improving the ovarian response of poor responders [6–8], yet none have demonstrated their superiority. Most of the cycle treatments end with poor outcome of fewer pregnancies and livebirth rate. Overall, poor responders require longer stimulation duration, associated with high doses of gonadotropins and higher cost. Still cycle cancellation rates are increased [9]

A cycle cancellation due to a failure of an oocyte retrieval or an available embryo to transfer is a very stressful event, given the significant emotional and financial investment involved in IVF treatment. Therefore, adequate fertility counselling addressing patients’ expectations, as well as adjusting the appropriate treatment strategy, is highly important when facing patient with POR.

Most countries do not provide insurance coverage for IVF treatments, and even those who do, offer only partial financial coverage limiting the number of treatments provided. Consequently, the financial factor significantly hinders the number of cycles that can be carried out. The situation in Israel is unique as the national health insurance provides financial coverage for repeated IVF cycles for the first two children, or up to the age of 45 years, usually regardless of the ovarian reserve.

Prompted by the aforementioned circumstances, we aimed to evaluate IVF cycle outcomes of patients with “genuine” POR, defined as those who had up to three retrieved oocytes in response to conventional control ovarian hyperstimulation, in a cost-free environment and with no restriction on the number of IVF treatment cycles. Furthermore, we sought to identify factors that are associated with a live birth in patients with POR. This may assist counselling by fertility specialists and the expectations of patients in adjusting the appropriate treatment strategy of POR patients. Our results might be of interest especially in countries in which egg donation is prohibited, or when multiple repeated IVF cycles attempts are financially affordable.

This was a historical cohort study which evaluated all consecutive medical records of infertile women who attended the Sheba Medical Center IVF unit for IVF cycle attempt from January 2016 through February 2020. Inclusion criteria were infertile women aged 18 to younger than 45 who underwent OS using autologous oocytes and yielded up to three oocytes. Excluded were patients with azoospermia or severe male factor, preimplantation genetic testing, women undergoing fertility preservation (freezing oocytes/ embryos), and patients using surrogacy.

Basic clinical characteristics, infertility treatment related variables and cycle outcomes were abstracted from the patients’ medical records.

The study was approved by the Institutional Review Board (IRB) at Sheba Medical Center. Informed consent was not required.

Ovarian stimulation was performed using mixed FSH/LH under pituitary supervision. One of the four OS protocols was used: the GnRH antagonist protocol, the long luteal phase GnRH agonist (GnRH-a) protocol, the short GnRH agonist (Flare) protocol, or the modified natural cycle-IVF (MNC-IVF) protocol. The selection of OS protocol used, and gonadotrophin dose were decided by the treating physician. In all protocol’s gonadotrophin doses were administrated in variable doses (with a minimal daily dose of 300IU), and further adjusted based on ultrasound scan and serum estradiol (E2) levels obtained every 2–3 days. Final follicular maturation was induced with one of the two trigger modes: (i) hCG (250 mcg Ovitrelle, Merck) 36 hours before oocyte retrieval, (ii) hCG (250 mcg) and GnRH- agonist (Decapeptyl 0.2 mg), 36 hours prior to oocyte retrieval, respectively (dual trigger), based on treating physician preference [10]. Retrieved oocytes were, according to sperm quality, either inseminated by conventional IVF or by intracytoplasmic sperm injection (ICSI), as previously described [11]. Luteal support was initiated one day after oocyte pick up and consist of vaginal progesterone gel 90 mg/day 8% (Crinone; Serono). In general, embryo transfer took place 2 to 3 days after oocyte retrieval. Remaining viable embryos were cryopreserved. Pregnancies were confirmed with beta-hCG levels, typically measured 14 days after embryo transfer. A Clinical pregnancy was confirmed when a gestational sac with fetal heartbeat was visible on ultrasound examination 6 weeks after embryo transfer. Delivery of a live infant was defined as any birth event where one or more live babies were born at ≥ 24 weeks’ gestation.

Cleavage embryos were defined as top quality embryos (TQE) if they had four to five blastomeres cells on day 2 and/ or 7 or 8 blastomeres on day 3, equally- sized blastomeres, contained < 15% fragmentation, and exhibited no apparent morphological abnormality [12]. Poor quality embryos consisted of all other embryos.

Statistical analysis

Statistical analysis was performed using the SPSS software package version 25 (SPSS Inc., Chicago, IL). Continuous variables were presented as means and standard deviation (SD). Categorical variables were presented as numbers and percentages. Differences in variables were statistically analyzed by Student’s t-test, Fisher exact test, and Pearson chi-square test, as appropriate. Normality of variables was assessed via Shapiro-Wilks test of normality.

To further investigate predictors for a live birth, a multivariate logistic regression analysis was used controlling for confounding effects that included the patients’ age, protocol type, stimulation duration, peak E2 level, number of dominant follicles at trigger day, and number of retrieved oocytes.

Two-sided P-values of < 0.05 were accepted as statistically significant.

During the study period, 528 patients met the inclusion criteria. The analysis included the outcomes of 751 fresh IVF/ ICSI cycles which yielded up to three oocytes. Of these, 265 cycles occurred among women \(\le\)40 years, and 486 cycles in women >40 years. Baseline characteristics, IVF cycle outcomes and final reproductive outcomes stratified according to patient’s age are presented in Table 1.

Baseline characteristics among patients younger versus older than 40 years were similar regarding gravidity, parity, body mass index (BMI) and basal FSH level. Duration of OS and the total gonadotrophins dose used were significantly higher in women older than 40 years (9.42 ± 3.65 days, and 4332.3 ± 2409.9 IU vs. 8.58 ± 3.76 days and 3307.3 ± 2245.6 IU, respectively, P < 0.01).

During the study period, 48 (9.1%) women conceived, and 28 (5.3%) gave birth to a live infant.

Pregnancy rate and live birth rate per cycle were significantly higher among patients \(\le\)40-years-old, as compared to patients above 40 years (9.8% and 6.8% versus 4.5% and 2.1%, p < 0.01, respectively; Table 1).

A further analysis comparing cycles resulted in live birth versus those which did not, is presented in Table 2. The live birth group was statistically significantly younger (mean ± SD, 37.65 ± 4.81 yrs. versus 40.37 ± 4.12 yrs., P < 0.001), had more oocytes retrieved (2.14 ± 0.79 versus 1.53 ± 0.98; P = 0.001), higher fertilization rate (0.80 ± 0.23 versus 0.51 ± 0.43; P < 0.001), and greater number of TQEs (0.65 ± 0.55 versus 0.34 ± 0.58; P < 0.01) compared with the group who did not achieve live birth.

When controlling for potential covariates in a multivariable regression analysis, however, the only statistically significant factors associated with achieving a live birth were patient's age (OR 0.90; 95% CI 0.845 to 0.97; p = 0.005) and mean number retrieved oocytes (OR 1.95; 95% CI 1.20 to 3.16; p = 0.007) (Table 3).

The present study was designed to provide women with genuine POR according to the Bologna criteria with prognostic information regarding IVF cycles outcomes and their chances of a live birth. Our data demonstrates that the probabilities of POR patients achieving a live birth are best with younger age and higher number of retrieved oocytes.

The age-related decline in ovarian reserve in women over 40 years is well documented [13, 14]. Nevertheless, for some women the physiologic decrease in ovarian function occurs earlier. The subgroup of patients termed “poor ovarian response” represents the most challenging group of patients to treat, as this population are at high risk for inadequate response during IVF treatment and lower pregnancy and live birth rates [15].

Several pretreatment diagnostic tests including basal FSH, AFC, inhibin B, and AMH have been used for prognosticating a poor responder to stimulation. More accurate prognostic information can be derived by the completion of ovarian stimulation cycle, as this “stress test” explores the capacity of the ovary to produce enough oocytes.

Previous studies found that recurrence rate of poor ovarian response during the subsequent ovarian stimulation was 54–62% [16, 17].

Dilemmas that physician may encounter while treating patients with POR may arise from the tendency to include this subgroup of patients as a homogenous group and therefore labeling similar treatment and prognosis to all patients. In fact, this is a heterogeneous group composed of different ages and various causes which led to POR. Thus, the question arises whether or not there are any prognostic factors which will mark some of the poor responders' patients with an acceptable prognosis for live birth following IVF treatment. Identifying such prognostic factors will assist fertility providers in counselling POR patients as to whether it is useful or not to start and / or to continue with IVF treatment.

A woman’s age is considered one of the most significant single determinants affecting chances of conception, either naturally or via ART [18–20]. Therefore, while counseling patients regarding their prognosis, age should be strongly considered. Hanoch et al. [21] conducted a study in which they evaluated differences in pregnancy rates of young versus older low responder patients. They reported significantly higher clinical pregnancy rate among young (20–30 yrs.) low responder patients (19.3% vs 6.5%). Accordingly, they concluded that young age protects from the deleterious effect of POR. In a literature review, Oudendijk et al. [15] concluded that older poor responders have lower pregnancy rates compared with younger poor responders (1.5%-12.7% vs. 13%-35%).

The findings of the present study are in line with the above-mentioned studies. Woman’s age was found to be negatively associated with the probability of achieving a live birth in lower responder’s patient population.

The distinct effect of female’s age on reproductive outcome is explained by the declining oocytes quality, which coincides with a progressive decrease in the primordial follicle number that occurs with female’s aging [22–24].

The age-induced oocyte quality impairment is closely associated with chromosomal abnormalities, and mitochondrial dysfunction [25, 26]. Women of older age are subjected to a higher number of aneuploid embryos which are more likely to arrest in extended culture [27]. This probably explains the substantially lower live birth rate of women of advanced maternal age.

The primordial follicle pool depletion is common not merely in women of advanced maternal age, but also in most poor ovarian responders, irrespective of age [28]. Thus, significantly limits the success of assisted reproduction treatment [29].

Since both group of women, advanced maternal age (AMA) and poor ovarian responders, as a subgroup, share the same physiologic follicular pool depletion, the question that arises is whether young poor responders also exhibit a reduction in oocyte quality like AMA women (i.e., high risk of aneuploidy, poor embryo development).

In attempt to address this question, a recent retrospective study published by Morin et al. [30] found that compared to normal responders, a fertilized oocyte retrieved from a young poor responder patient (< 38 years) is no less likely to form a quality blastocyst, be euploid or produce a live birth. They concluded that an oocyte retrieved from a poor responder patient performs similarly to that from age-matched controls.

The present study demonstrates a significant higher live birth rate in poor ovarian response who are younger than 40 years compared to poor responders > 40 years (7% vs 2%, respectively). This finding as well as the results of the multivariate analysis strongly suggest that a woman’s chronological age is a critical factor which affects IVF outcome and protects against the adverse effect of poor ovarian response.

Another factor which the present study found to be of relevance in determining the prospects of Bologna poor responders for a live birth is the number of oocytes retrieved.

Although the number of oocytes per se is not an indicator of their quality, yet the lower the degree of poor ovarian response, there will be more oocytes to retrieve and subsequently more embryos to transfer, which may improve the chances for pregnancy.

The results of the multivariate analysis which found the number of oocytes retrieved and not the number of dominant follicles visualized ultrasonographically as an independent predictor of live birth could be explained by the fact that oocytes could not be retrieved from some follicles during ovum pick up. The fact that this index cannot be determined in advance limits its value in counseling and preparing POR patients before embarking on IVF treatment.

Our findings are in agreement with previous studies which found positive association between the number of oocytes retrieved and pregnancy/live birth rates in poor responders [15, 31].

This study is not the first study dealing with predicting factors for successful IVF cycles in poor responder patients. However, it is important to stress that when reading through the current published literature there is a lack of uniformity regarding the definition of poor responders (from fewer than two up to five dominant follicles) [32], which explains the differences in the studies’ results. To the best of our knowledge, the current study is among the largest experiences of poor responders, defined according to the Bologna criteria, up to 3 oocytes retrievals.

The unique health care system in which this study was conducted provides financial coverage for repeated IVF cycles. This enables to collect information on a high number of cycles treatment, which in other places might have been cancelled due to poor response.

The inclusion of high number of cycles treatment strengthens the power of the study results and allows a firm assessment on the markers predicting success in the poor ovarian response population. Therefore, contributing valuable information for both fertility providers and patients alike.

The limitations of the study should also be noted. First, as this was a retrospective study, it had the inherent biases that might affect the results. Although we tried to minimize selection bias by using rigorous inclusion criteria, we cannot exclude unknown confounders that might have affected the results. In addition, AMH values could not be analysed as they are not part of the local routine testing. Of notice, FSH which is considered a reliable test marker to predict ovarian response to stimulation, according to our results was found to have no predictive value on treatment outcome of poor responders.

Improving the cycle outcome is one of the goals of fertility providers.

However, taking into consideration the balance between risks, costs (financial and emotional) and benefits involved in providing IVF treatment for POR, the question emerges is whether additional cycles using the women’s autologous oocytes are justified or continuation of treatment should be discouraged.

Given the present study data, it appears that continuation with IVF treatments seems reasonable in patients younger than 40 years, since in these poor responder’s pregnancy rates were 10%, and live birth rates were 7% per cycle. Yet, for poor responders’ women \(>\)40 there appeared to be hardly any justification for any further IVF treatment, due to very poor outcome (4.5% pregnancy rate, and 2% live birth rate per cycle).

In conclusion, the woman’s age and the number of retrieved oocytes are both independent predicting factors of live birth in poor ovarian responders according to the Bologna criteria.

All poor ovarian responders should be informed regarding the meager probability of achieving a live birth. Specifically, POR women \(>\)40 years should be encouraged to apply for the process of egg donation, which will improve their chances of a live birth substantially.

IVF: In vitro fertilization; ICSI: Intracytoplasmic sperm injection; LB: Live birth; POR: Poor ovarian response; OS: Ovarian stimulation; ART: Assisted reproductive technology; GnRH-a: Gonadotropin releasing hormone agonist; MNC- Modified natural cycle; TQE: Top quality embryo; E2: Estradiol; BMI: Body mass index; AMA: Advanced maternal age.

Acknowledgments: Not applicable.

Author contributions: OL: Conceptualized the idea, contributed to the design, analysed the data, and manuscript writing. JH, RO: Contributed to the study design, interpretation of the data and manuscript editing. NM: Data collection. EZ, AA, MK, RN: Interpretation of data, and manuscript editing. All authors read and approved the final manuscript.

Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Availability of data and materials: The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate: The study was approved by the institutional Review Broad at Sheba Medical Center according to the principles of the declaration of Helsinki (study reference number 6978-20-SMC). All methods were carried out in accordance with relevant guidelines and regulations. As a retrospective study, informed consent was exempted by the ethics committee of Sheba Medical Center. Patients’ data were used anonymously.

Consent for publication: Not applicable.

Competing interests: The authors declare that they have no competing interests.

Macklon NS, Stouffer RL, Giudice LC, Fauser BC. The science behind 25 years of ovarian stimulation for in vitro fertilization. Endocr Rev. 2006;27(2):170–207.
Sunkara SK, Rittenberg V, Raine-Fenning N, Bhattacharya S, Zamora J, Coomarasamy A. Association between the number of eggs and live birth in IVF treatment: an analysis of 400 135 treatment cycles. Hum Reprod. 2011;26(7):1768–74.
Ferraretti AP, La Marca A, Fauser BC, Tarlatzis B, Nargund G, Gianaroli L, et al. ESHRE consensus on the definition of 'poor response' to ovarian stimulation for in vitro fertilization: the Bologna criteria. Hum Reprod. 2011;26(7):1616–24.
Keay SD, Liversedge NH, Mathur RS, Jenkins JM. Assisted conception following poor ovarian response to gonadotrophin stimulation. Br J Obstet Gynaecol. 1997;104(5):521–7.
Ubaldi F, Vaiarelli A, D'Anna R, Rienzi L. Management of poor responders in IVF: is there anything new? Biomed Res Int. 2014;2014:352098.
Fasouliotis SJ, Simon A, Laufer N. Evaluation and treatment of low responders in assisted reproductive technology: a challenge to meet. J Assist Reprod Genet. 2000;17(7):357–73.
Mohamed KA, Davies WA, Allsopp J, Lashen H. Agonist "flare-up" versus antagonist in the management of poor responders undergoing in vitro fertilization treatment. Fertil Steril. 2005;83(2):331–5.
Orvieto R, Kirshenbaum M, Galiano V, Zilberberg E, Haas J, Nahum R. Stop GnRH-Agonist Combined with Multiple-Dose GnRH-Antagonist for Patients with Elevated Peak Serum Progesterone Levels Undergoing Ovarian Stimulation for IVF: A Proof of Concept. Gynecol Obstet Invest. 2020;85(4):357–61.
Ben-Rafael Z, Orvieto R, Feldberg D. The poor-responder patient in an in vitro fertilization-embryo transfer (IVF-ET) program. Gynecol Endocrinol. 1994;8(4):277–86.
Orvieto R. Triggering final follicular maturation–hCG, GnRH-agonist or both, when and to whom? J Ovarian Res. 2015;8:60.
Simon A, Holzer H, Hurwitz A, Revel A, Zentner BS, Lossos F, et al. Comparison of cryopreservation outcome following intracytoplasmic sperm injection and conventional in vitro fertilization. J Assist Reprod Genet. 1998;15(7):431–7.
Ziebe S, Lundin K, Janssens R, Helmgaard L, Arce JC, Group M. Influence of ovarian stimulation with HP-hMG or recombinant FSH on embryo quality parameters in patients undergoing IVF. Hum Reprod. 2007;22(9):2404–13.
Sozou PD, Hartshorne GM. Time to pregnancy: a computational method for using the duration of non-conception for predicting conception. PLoS One. 2012;7(10):e46544.
Malchau SS, Henningsen AA, Loft A, Rasmussen S, Forman J, Nyboe Andersen A, et al. The long-term prognosis for live birth in couples initiating fertility treatments. Hum Reprod. 2017;32(7):1439–49.
Oudendijk JF, Yarde F, Eijkemans MJ, Broekmans FJ, Broer SL. The poor responder in IVF: is the prognosis always poor?: a systematic review. Hum Reprod Update. 2012;18(1):1–11.
Klinkert ER, Broekmans FJ, Looman CW, Te Velde ER. A poor response in the first in vitro fertilization cycle is not necessarily related to a poor prognosis in subsequent cycles. Fertil Steril. 2004;81(5):1247–53.
Penarrubia J, Fabregues F, Manau D, Creus M, Carmona F, Casamitjana R, et al. Previous cycle cancellation due to poor follicular development as a predictor of ovarian response in cycles stimulated with gonadotrophin-releasing hormone agonist-gonadotrophin treatment. Hum Reprod. 2005;20(3):622–8.
Creus M, Penarrubia J, Fabregues F, Vidal E, Carmona F, Casamitjana R, et al. Day 3 serum inhibin B and FSH and age as predictors of assisted reproduction treatment outcome. Hum Reprod. 2000;15(11):2341–6.
Broer SL, van Disseldorp J, Broeze KA, Dolleman M, Opmeer BC, Bossuyt P, et al. Added value of ovarian reserve testing on patient characteristics in the prediction of ovarian response and ongoing pregnancy: an individual patient data approach. Hum Reprod Update. 2013;19(1):26–36.
van Loendersloot LL, van Wely M, Limpens J, Bossuyt PM, Repping S, van der Veen F. Predictive factors in in vitro fertilization (IVF): a systematic review and meta-analysis. Hum Reprod Update. 2010;16(6):577–89.
Hanoch J, Lavy Y, Holzer H, Hurwitz A, Simon A, Revel A, et al. Young low responders protected from untoward effects of reduced ovarian response. Fertil Steril. 1998;69(6):1001–4.
Navot D, Bergh PA, Williams MA, Garrisi GJ, Guzman I, Sandler B, et al. Poor oocyte quality rather than implantation failure as a cause of age-related decline in female fertility. Lancet. 1991;337(8754):1375–7.
Broekmans FJ, Soules MR, Fauser BC. Ovarian aging: mechanisms and clinical consequences. Endocr Rev. 2009;30(5):465–93.
Cimadomo D, Fabozzi G, Vaiarelli A, Ubaldi N, Ubaldi FM, Rienzi L. Impact of Maternal Age on Oocyte and Embryo Competence. Front Endocrinol (Lausanne). 2018;9:327.
Bartmann AK, Romao GS, Ramos Eda S, Ferriani RA. Why do older women have poor implantation rates? A possible role of the mitochondria. J Assist Reprod Genet. 2004;21(3):79–83.
de Bruin JP, Dorland M, Spek ER, Posthuma G, van Haaften M, Looman CW, et al. Age-related changes in the ultrastructure of the resting follicle pool in human ovaries. Biol Reprod. 2004;70(2):419–24.
Vega M, Breborowicz A, Moshier EL, McGovern PG, Keltz MD. Blastulation rates decline in a linear fashion from euploid to aneuploid embryos with single versus multiple chromosomal errors. Fertil Steril. 2014;102(2):394–8.
Farhi J, Homburg R, Ferber A, Orvieto R, Ben Rafael Z. Non-response to ovarian stimulation in normogonadotrophic, normogonadal women: a clinical sign of impending onset of ovarian failure pre-empting the rise in basal follicle stimulating hormone levels. Hum Reprod. 1997;12(2):241–3.
Alviggi C, Conforti A, Caprio F, Gizzo S, Noventa M, Strina I, et al. In Estimated Good Prognosis Patients Could Unexpected "Hyporesponse" to Controlled Ovarian Stimulation be Related to Genetic Polymorphisms of FSH Receptor? Reprod Sci. 2016;23(8):1103–8.
Morin SJ, Patounakis G, Juneau CR, Neal SA, Scott RT, Seli E. Diminished ovarian reserve and poor response to stimulation in patients < 38 years old: a quantitative but not qualitative reduction in performance. Hum Reprod. 2018;33(8):1489–98.
Polyzos NP, Nwoye M, Corona R, Blockeel C, Stoop D, Haentjens P, et al. Live birth rates in Bologna poor responders treated with ovarian stimulation for IVF/ICSI. Reprod Biomed Online. 2014;28(4):469–74.
Polyzos NP, Devroey P. A systematic review of randomized trials for the treatment of poor ovarian responders: is there any light at the end of the tunnel? Fertil Steril. 2011;96(5):1058-61 e7.

Table 1

Patients’ characteristics and cycle outcomes by woman’s age group.
	< 40Y	> 40Y	p
Number of cycles	265	486
Age (years), mean ± SD	35.81 ± 3.86	42.70 ± 1.42	< 0.001
BMI (kg/m²), mean ± SD	25.64 ± 6.11	26.31 ± 6.19	0.1789
Gravity, mean ± SD	1.15 ± 1.49	1.27 ± 1.53	0.2991
Parity, mean ± SD	0.44 ± 0.78	0.46 ± 0.64	0.7150
Protocol Antagonist, n (%) MNC, n (%) Short agonist, n (%) Long agonist, n (%)	184 (69.4%) 67 (25.3%) 9 (3.4%) 5 (1.9%)	352 (72.4%) 88 (18.1%) 27 (5.6%) 19 (3.9%)	0.0391
Day 3 FSH levels (IU/L), mean ± SD	12.97 ± 8.97	13.60 ± 11.38	0.5261
Duration of stimulation (days), mean ± SD	8.58 ± 3.76	9.42 ± 3.65	0.003
Total dose of gonadotropins (IU), mean ± SD	3307.3 ± 2245.6	4332.3 ± 2409.9	< 0.001
No. of follicles ≥ 15 mm, mean ± SD	1.68 ± 0.76	1.66 ± 0.74	0.7976
Leading follicle size (mm), mean ± SD	18.53 ± 2.17	18.10 ± 2.04	0.006
E₂ level at the trigger day (pmol/L), mean ± SD	1750.3 ± 1115.5	1769.4 ± 939.6	0.802
Trigger hCG, n (%) Dual trigger, n (%)	192 (72.5%) 73 (27.5%)	338 (69.6%) 148 (30.4%)	0.403
Progesterone levels at the trigger day (nmol/L), mean ± SD	1.43 ± 1.04	1.50 ± 1.21	0.435
No. of retrieved oocytes, mean ± SD	1.55 ± 0.99	1.54 ± 0.97	0.9217
Cycles with no oocytes, n (%)	41 (15.47%)	78 (16.05%)	0.852
Top quality embryos, mean ± SD	0.37 ± 0.59	0.33 ± 0.55	0.391
Fertilization rate, mean ± SD	0.63 ± 0.40	0.62 ± 0.4	0.6315
Pregnancy rate per cycle, n (%)	26/265(9.81%)	22/486 (4.53%)	0.004
Live birth per cycle, n (%)	18/265 (6.79%)	10/486 (2.06%)	0.001

BMI- body mass index, MNC- modified natural cycle

Table 2

Comparison between cycles resulted in live birth versus no live birth.
	Live birth (n = 28)	No live birth (n = 723)	P
Age (years), mean ± SD	37.65 ± 4.81	40.37 ± 4.12	0.0006
BMI (kg/m²), mean ± SD	25.13 ± 6.23	26.09 ± 6.16	0.467
Protocol Antagonist, n (%) MNC, n (%) Short agonist, n (%) Long agonist, n (%)	26 (92.9%) 2 (7.1%) 0 (0%) 0 (0%)	510 (70.5%) 153 (21.2%) 36 (5.0%) 24 (3.3%)	0.147
Day-3 FSH (IU/L), mean ± SD	12.05 ± 5.64	13.54 ± 10.82	0.552
Duration of stimulation (days), mean ± SD	8.97 ± 2.63	9.12 ± 3.75	0.83
Total dose of gonadotropins (IU), mean ± SD	3310.33 ± 1720.23	3987.13 ± 2420.71	0.136
No. of follicles ≥ 15 mm, mean ± SD	1.79 ± 0.77	1.66 ± 0.75	0.364
Leading follicle size (mm), mean ± SD	18.69 ± 1.95	18.24 ± 2.10	0.254
E₂ level at the trigger day (pmol/L), mean ± SD	1873.62 ± 806.21	1756.7 ± 1010.74	0.538
Trigger hCG, n (%) Dual trigger, n (%)	19 (65.5%) 10 (34.5%)	511 (70.8%) 211 (29.2%)	0.542
No. of retrieved oocytes, mean ± SD	2.14 ± 0.79	1.53 ± 0.98	0.001
Fertilization rate, mean ± SD	0.80 ± 0.23	0.51 ± 0.43	0.0004
Top quality embryos, mean ± SD	0.65 ± 0.55	0.34 ± 0.58	0.004
No. of embryos transferred 0, n (%) 1, n (%) 2, n (%) 3, n (%)	---- 17 (60.7%) 11 (39.3%) ----	341 (47.2%) 258(35.7%) 114 (15.8%) 10 (1.4%)	< 0.001

BMI- body mass index, MNC- modified natural cycle

Table 3

Multivariable regression analysis for factors associated with live birth in POR patient’s undergoing IVF.
Predictor	Odds ratio	95% CI	P value
Age (years)	0.905	0.84–0.97	0.005
Type of protocol NS
Antagonist	Reference
MNC	0.31	0.07–1.39	NS
Short agonist	0	0	NS
Long agonist	0	0	NS
Stimulation duration (days)	0.91	0.78–1.06	NS
No. of follicles ≥ 15 mm	0.96	0.53–1.75	NS
E₂ level at the trigger day (pmol/L)	0.96	0.60–1.55	NS
No. of retrieved oocytes	1.95	1.21–3.16	0.007

MNC- modified natural cycle, NS- not significant

No competing interests reported.

Download PDF

Editorial decision: Major revision
18 Jul, 2022
Reviews received at journal
16 Jun, 2022
Reviewers agreed at journal
15 Jun, 2022
Reviewers invited by journal
11 Jun, 2022
Editor assigned by journal
11 Jun, 2022
Editor invited by journal
10 Jun, 2022
Submission checks completed at journal
10 Jun, 2022
First submitted to journal
07 Jun, 2022

You are reading this latest preprint version

Predicting IVF outcome in poor ovarian responders

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Introduction

Patients And Methods

Statistical analysis

Results

Discussion

Abbreviations

Declarations

References

Tables

Additional Declarations

Status:

Version 1