Predicting personalized cumulative live birth following in vitro fertilization

Improving IVF Utilization with Patient-Centric Artificial Intelligence-Machine Learning (AI/ML): A Retrospective Multicenter Experience

Objectives: In vitro fertilization (IVF) has the potential to give babies to millions more people globally, yet it continues to be underutilized. We established a globally applicable and locally adaptable IVF prognostics report and framework to support patient-provider counseling and enable validated, data-driven treatment decisions. This study investigates the IVF utilization rates associated with the usage of machine learning, center-specific (MLCS) prognostic reports (the Univfy® report) in provider-patient pre-treatment and IVF counseling. Methods: We used a retrospective cohort comprising 24,238 patients with new patient visits (NPV) from 2016 to 2022 across seven fertility centers in 17 locations in seven US states and Ontario, Canada. We tested the association of Univfy report usage and first intra-uterine insemination (IUI) and/or first IVF usage (a.k.a. conversion) within 180 days, 360 days, and "Ever" of NPV as primary outcomes. Results: Univfy report usage was associated with higher direct IVF conversion (without prior IUI), with odds ratios (OR) 3.13 (95% CI 2.83, 3.46), 2.89 (95% CI 2.63, 3.17), and 2.04 (95% CI 1.90, 2.20) and total IVF conversion (with or without prior IUI), OR 3.41 (95% CI 3.09, 3.75), 3.81 (95% CI 3.49, 4.16), and 2.78 (95% CI 2.59, 2.98) in 180-day, 360-day, and Ever analyses, respectively; p < 0.05. Among patients with Univfy report usage, after accounting for center as a factor, older age was a small yet independent predictor of IVF conversion. Conclusions: Usage of a patient-centric, MLCS-based prognostics report was associated with increased IVF conversion among new fertility patients. Further research to study factors influencing treatment decision making and real-world optimization of patient-centric workflows utilizing the MLCS reports is warranted.

Fertility clinics have a duty of care towards patients who do not have children with treatment

In medically assisted reproduction (MAR) success has mostly been measured in terms of achieving (healthy) livebirths. We argue this focus is too narrow and that success should be measured in terms of alleviating patient suffering caused by an unfulfilled child wish. The major implication is that clinics must better tailored care to effectively support patients who do not have child(ren) with treatment. First, we argue that clinics have a duty of care towards patients for whom MAR does not result in children because this is a common treatment outcome, because treatment is burdensome and creates new losses for patients, and because the field has the necessary expertise to provide support and it is part of patient-centred care. Then, we examine concerns about the adequacy of addressing the possibility that treatment may end without children, namely, that this may hinder patients' hope and put them off doing treatment, and that it may be perceived as a sign of clinical incompetence, as well as concerns about the required skill set. We end with a set of research-informed recommendations to promote healthy adjustment to ending fertility treatment without children. These focus on the need to reconceptualize 'success' and 'failure' in MAR, to promote open discussion about the possibility of treatment not resulting in children and encourage patients to develop 'plan(s) B', to support patients who end treatment without children, and to create the organizational structures needed to support clinics and healthcare professionals in this endeavour.

Predicting personalized cumulative live birth rate after a complete in vitro fertilization cycle: an analysis of 32,306 treatment cycles in China

BACKGROUND

The cumulative live birth rate (CLBR) has been regarded as a key measure of in vitro fertilization (IVF) success after a complete treatment cycle. Women undergoing IVF face great psychological pressure and financial burden. A predictive model to estimate CLBR is needed in clinical practice for patient counselling and shaping expectations.

METHODS

This retrospective study included 32,306 complete cycles derived from 29,023 couples undergoing IVF treatment from 2014 to 2020 at a university-affiliated fertility center in China. Three predictive models of CLBR were developed based on three phases of a complete cycle: pre-treatment, post-stimulation, and post-treatment. The non-linear relationship was treated with restricted cubic splines. Subjects from 2014 to 2018 were randomly divided into a training set and a test set at a ratio of 7:3 for model derivation and internal validation, while subjects from 2019 to 2020 were used for temporal validation.

RESULTS

Predictors of pre-treatment model included female age (non-linear relationship), antral follicle count (non-linear relationship), body mass index, number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, tubal factor, male factor, and scarred uterus. Predictors of post-stimulation model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. Predictors of post-treatment model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), cumulative Day-3 embryos live-birth capacity (non-linear relationship), number of previous IVF attempts, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. The C index of the three models were 0.7559, 0.7744, and 0.8270, respectively. All models were well calibrated (p = 0.687, p = 0.468, p = 0.549). In internal validation, the C index of the three models were 0.7422, 0.7722, 0.8234, respectively; and the calibration P values were all greater than 0.05. In temporal validation, the C index were 0.7430, 0.7722, 0.8234 respectively; however, the calibration P values were less than 0.05.

CONCLUSIONS

This study provides three IVF models to predict CLBR according to information from different treatment stage, and these models have been converted into an online calculator ( https://h5.eheren.com/hcyc/pc/index.html#/home ). Internal validation and temporal validation verified the good discrimination of the predictive models. However, temporal validation suggested low accuracy of the predictive models, which might be attributed to time-associated amelioration of IVF practice.

Effectiveness of recombinant human FSH: recombinant human LH combination treatment versus recombinant human FSH alone for assisted reproductive technology in women aged 35-40 years

RESEARCH QUESTION

According to real-world data, is recombinant human FSH (r-hFSH) combined with recombinant human LH (r-hLH) or r-hFSH alone more effective for women of advanced maternal age (AMA) in terms of live birth?

DESIGN

Non-interventional study comparing the effectiveness of r-hFSH and recombinant r-hLH (2:1 ratio) versus r-hFSH alone for ovarian stimulation during ART treatment in women aged 35-40 years, using real-world data from the Deutsches IVF-Register.

RESULTS

Overall clinical pregnancy (29.8%, 95% CI 28.2 to 31.6 versus 27.8%, 95% CI 26.5 to 29.2) and live birth (20.3%, 95% CI 18.7 to 21.8 versus 18.0%, 95% CI 16.6 to 19.4) rates were not significantly different between the combined r-hFSH and r-hLH group and the r-hFSH alone group (P = 0.269 and P = 0.092, respectively). Treatment effect was significantly higher for combined r-hFSH and r-hLH compared with r-hFSH alone for clinical pregnancy (33.1%, 95% CI 31.0 to 35.0 versus 28.5%, 95% CI 26.6 to 30.4; P = 0.001, not adjusted for multiplicity) and live birth (22.5%, 95% CI 20.5 to 24.2 versus 19.4%, 95% CI 17.6 to 20.9; P = 0.014, not adjusted for multiplicity) in a post-hoc analysis of women with five to 14 oocytes retrieved (used as a surrogate for normal ovarian reserve), highlighting the potential benefits of combined r-hFSH and r-hLH for ovarian stimulation in women aged 35-40 years with normal ovarian reserve.

CONCLUSIONS

Women of AMA with normal ovarian response benefit from treatment with combined r-hFSH and r-hLH in a 2:1 ratio versus r-hFSH alone in terms of live birth rate. The effectiveness of treatments is best assessed by RCTs; however, real-world data are valuable for examining the effectiveness of fertility treatment, especially among patient groups that are not well represented in clinical trials.

Pretreatment prediction for IVF outcomes: generalized applicable model or centre-specific model?

STUDY QUESTION

What was the performance of different pretreatment prediction models for IVF, which were developed based on UK/US population (McLernon 2016 model, Luke model, Dhillon model, and McLernon 2022 model), in wider populations?

SUMMARY ANSWER

For a patient in China, the published pretreatment prediction models based on the UK/US population provide similar discriminatory power with reasonable AUCs and underestimated predictions.

WHAT IS KNOWN ALREADY

Several pretreatment prediction models for IVF allow patients and clinicians to estimate the cumulative probability of live birth in a cycle before the treatment, but they are mostly based on the population of Europe or the USA, and their performance and applicability in the countries and regions beyond these regions are largely unknown.

STUDY DESIGN, SIZE, DURATION

A total of 26 382 Chinese patients underwent oocyte pick-up cycles between January 2013 and December 2020.

PARTICIPANTS/MATERIALS, SETTING, METHODS

UK/US model performance was externally validated according to the coefficients and intercepts they provided. Centre-specific models were established with XGboost, Lasso, and generalized linear model algorithms. Discriminatory power and calibration of the models were compared as the forms of the AUC of the Receiver Operator Characteristic and calibration curves.

MAIN RESULTS AND THE ROLE OF CHANCE

The AUCs for McLernon 2016 model, Luke model, Dhillon model, and McLernon 2022 model were 0.69 (95% CI 0.68-0.69), 0.67 (95% CI 0.67-0.68), 0.69 (95% CI 0.68-0.69), and 0.67 (95% CI 0.67-0.68), respectively. The centre-specific yielded an AUC of 0.71 (95% CI 0.71-0.72) with key predictors including age, duration of infertility, and endocrine parameters. All external models suggested underestimation. Among the external models, the rescaled McLernon 2022 model demonstrated the best calibration (Slope 1.12, intercept 0.06).

LIMITATIONS, REASONS FOR CAUTION

The study is limited by its single-centre design and may not be representative elsewhere. Only per-complete cycle validation was carried out to provide a similar framework to compare different models in the sample population. Newer predictors, such as AMH, were not used.

WIDER IMPLICATIONS OF THE FINDINGS

Existing pretreatment prediction models for IVF may be used to provide useful discriminatory power in populations different from those on which they were developed. However, models based on newer more relevant datasets may provide better calibrations.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the National Natural Science Foundation of China [grant number 22176159], the Xiamen Medical Advantage Subspecialty Construction Project [grant number 2018296], and the Special Fund for Clinical and Scientific Research of Chinese Medical Association [grant number 18010360765].

TRIAL REGISTRATION NUMBER

N/A.

Oxygen concentration from days 1 to 3 after insemination affects the embryo culture quality, cumulative live birth rate, and perinatal outcomes

PURPOSE

We aimed to compare embryo development, cumulative live birth rate (CLBR), and perinatal outcomes of embryos cultured in 20% and 5% oxygen from days 1 to 3 after insemination.

METHODS

This retrospective study included patients who received in vitro fertilization (IVF) treatment between January 2015 and November 2019. Embryos of each patient were cultured at 20% or 5% oxygen from days 1-3 after insemination. The primary outcome was CLBR. Propensity score matching (PSM) was used to balance patients' baseline data in both oxygen groups.

RESULTS

In total, 31,566 patients were enrolled. After PSM, the rate of high-quality day 3 embryos was significantly lower in the 20% than in the 5% oxygen group (0.49 ± 0.33 vs 0.51 ± 0.33; adjusted β = -0.03; 95% confidence interval [CI], -0.03 to -0.02). The CLBR was significantly lower in the 20% than in the 5% oxygen group (58.6% vs. 62.4%; adjusted odds ratio = 0.85; 95% CI, 0.81-0.90). The birthweight and Z score of singletons were significantly higher in the 20% than in the 5% oxygen group (birthweight: 3.30 ± 0.50 vs. 3.28 ± 0.48; adjusted β = 0.022; 95% CI, 0.004-0.040; Z score: 0.26 ± 1.04 vs. 0.22 ± 1.01; adjusted β = 0.037; 95% CI, 0.001-0.074).

CONCLUSION

Culturing embryos at atmospheric oxygen concentrations from days 1 to 3 compromises embryo quality, reduces CLBR, and affects birthweight. The 5% oxygen concentration is more suitable for embryo culture in IVF laboratories to achieve successful outcomes.

External validation of models for predicting cumulative live birth over multiple complete cycles of IVF treatment

STUDY QUESTION

Can two prediction models developed using data from 1999 to 2009 accurately predict the cumulative probability of live birth per woman over multiple complete cycles of IVF in an updated UK cohort?

SUMMARY ANSWER

After being updated, the models were able to estimate individualized chances of cumulative live birth over multiple complete cycles of IVF with greater accuracy.

WHAT IS KNOWN ALREADY

The McLernon models were the first to predict cumulative live birth over multiple complete cycles of IVF. They were converted into an online calculator called OPIS (Outcome Prediction In Subfertility) which has 3000 users per month on average. A previous study externally validated the McLernon models using a Dutch prospective cohort containing data from 2011 to 2014. With changes in IVF practice over time, it is important that the McLernon models are externally validated on a more recent cohort of patients to ensure that predictions remain accurate.

STUDY DESIGN, SIZE, DURATION

A population-based cohort of 91 035 women undergoing IVF in the UK between January 2010 and December 2016 was used for external validation. Data on frozen embryo transfers associated with these complete IVF cycles conducted from 1 January 2017 to 31 December 2017 were also collected.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Data on IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA). The predictive performances of the McLernon models were evaluated in terms of discrimination and calibration. Discrimination was assessed using the c-statistic and calibration was assessed using calibration-in-the-large, calibration slope, and calibration plots. Where any model demonstrated poor calibration in the validation cohort, the models were updated using intercept recalibration, logistic recalibration, or model revision to improve model performance.

MAIN RESULTS AND THE ROLE OF CHANCE

Following exclusions, 91 035 women who underwent 144 734 complete cycles were included. The validation cohort had a similar distribution age profile to women in the development cohort. Live birth rates over all complete cycles of IVF per woman were higher in the validation cohort. After calibration assessment, both models required updating. The coefficients of the pre-treatment model were revised, and the updated model showed reasonable discrimination (c-statistic: 0.67, 95% CI: 0.66 to 0.68). After logistic recalibration, the post-treatment model showed good discrimination (c-statistic: 0.75, 95% CI: 0.74 to 0.76). As an example, in the updated pre-treatment model, a 32-year-old woman with 2 years of primary infertility has a 42% chance of having a live birth in the first complete ICSI cycle and a 77% chance over three complete cycles. In a couple with 2 years of primary male factor infertility where a 30-year-old woman has 15 oocytes collected in the first cycle, a single fresh blastocyst embryo transferred in the first cycle and spare embryos cryopreserved, the estimated chance of live birth provided by the post-treatment model is 46% in the first complete ICSI cycle and 81% over three complete cycles.

LIMITATIONS, REASONS FOR CAUTION

Two predictors from the original models, duration of infertility and previous pregnancy, which were not available in the recent HFEA dataset, were imputed using data from the older cohort used to develop the models. The HFEA dataset does not contain some other potentially important predictors, e.g. BMI, ethnicity, race, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count.

WIDER IMPLICATIONS OF THE FINDINGS

Both updated models show improved predictive ability and provide estimates which are more reflective of current practice and patient case mix. The updated OPIS tool can be used by clinicians to help shape couples' expectations by informing them of their individualized chances of live birth over a sequence of multiple complete cycles of IVF.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. S.B. has a commitment of research funding from Merck. D.J.M. and M.B.R. declare support for the present manuscript from Elphinstone scholarship scheme at the University of Aberdeen and Assisted Reproduction Unit at Aberdeen Fertility Centre, University of Aberdeen. D.J.M. declares grants received by University of Aberdeen from NHS Grampian, The Meikle Foundation, and Chief Scientist Office in the past 3 years. D.J.M. declares receiving an honorarium for lectures from Merck. D.J.M. is Associate Editor of Human Reproduction Open and Statistical Advisor for Reproductive BioMed Online. S.B. declares royalties from Cambridge University Press for a book. S.B. declares receiving an honorarium for lectures from Merck, Organon, Ferring, Obstetric and Gynaecological Society of Singapore, and Taiwanese Society for Reproductive Medicine. S.B. has received support from Merck, ESHRE, and Ferring for attending meetings as speaker and is on the METAFOR and CAPRE Trials Data Monitoring Committee.

TRIAL REGISTRATION NUMBER

N/A.

Oocyte donation outcomes in endometriosis patients with multiple IVF failures

RESEARCH QUESTION

What are the reproductive outcomes and the prognostic factors of live birth rates in patients with endometriosis referred to oocyte donation after multiple IVF failures?

DESIGN

Observational cohort study including all women with endometriosis-related infertility and two or more failed IVF/intracytoplasmic sperm injection (ICSI) cycles referred to oocyte donation between January 2013 and June 2022. Endometriosis was diagnosed based on published imaging criteria, and was confirmed histologically in women who had a history of surgery for endometriosis. The main outcome measured was the cumulative live birth rate (CLBR). The characteristics of women who had a live birth were compared with those who did not using univariate and multivariate analysis to identify determinant factors of fertility outcome.

RESULTS

Fifty-seven patients underwent 90 oocyte donation cycles after 244 failed autologous IVF cycles. The mean ± SD age of the population was 36.8 ± 3.3 years, with a mean duration of infertility of 3.6 ± 2.2 years, and a mean number of autologous IVF/ICSI cycles of 4.4 ± 2.3 cycles per patient. Three patients (5.3%) had superficial peritoneal endometriosis, two patients (3.5%) had ovarian endometriomas, and 52 patients (91.2%) had deep infiltrating endometriosis, among which 30 patients (57.7%) had bowel lesions. Thirty patients (52.6%) had associated adenomyosis. Overall, CLBR per patient was 36/57 (63.2%). After multivariate analysis, only being nulligravida (P=0.002) remained an independent negative predictive factor of the live birth rate. Previous surgery did not impact reproductive outcomes.

CONCLUSION

This study suggests that oocyte donation appears to be a viable option to optimize the live birth rate in women with endometriosis-related infertility and recurrent IVF failures.

Effect of the endometrial thickness on the live birth rate: insights from 959 single euploid frozen embryo transfers without a cutoff for thickness

OBJECTIVE

To investigate whether endometrial thickness (ET) independently affects the live birth rate (LBR) after embryo transfer.

DESIGN

Retrospective study.

SETTING

Private assisted reproductive technology center.

PATIENT(S)

A total of 959 single euploid frozen embryo transfers.

INTERVENTION(S)

Vitrified euploid blastocyst transfer.

MAIN OUTCOME MEASURE(S)

Live birth rate per embryo transfer.

RESULT(S)

The conditional density plots did not demonstrate either a linear relationship between the ET and LBR or a threshold below which the LBR decreased perceivably. Receiver operating characteristic curve analyses did not suggest a predictive value of the ET for the LBR. The area under the curve values were 0.55, 0.54, and 0.54 in the overall, programmed, and natural cycle transfers, respectively. Logistic regression analyses with age, embryo quality, day of trophectoderm biopsy, body mass index, and ET did not suggest an independent effect of the ET on the LBR.

CONCLUSION(S)

We did not identify a threshold of the ET that either precluded live birth or under which the LBR decreases perceivably. Common practice of cancelling embryo transfers when the ET is <7 mm may not be justified. Prospective studies, in which the management of the transfer cycle would not be altered by ET, would provide higher-quality evidence on the subject.

Infertility services integrated within the maternal health department of a public hospital in a low-income country, Rwanda

Objective

To describe the initiation, integration, and costs of reduced-cost infertility services within the maternal health department of a public hospital in a low-income country.

Design

Retrospective review of the clinical and laboratory components of patients undergoing in vitro fertilization (IVF) treatment in Rwanda from 2018 to 2020.

Setting

Academic tertiary referral hospital in Rwanda.

Patients

Patients seeking infertility services beyond the primary gynecological options.

Interventions

The national government furnished facilities and personnel, and the Rwanda Infertility Initiative, an international nongovernmental organization, provided training, equipment, and materials. The incidence of retrieval, fertilization, embryo cleavage, transfer, and conception (observed until ultrasound verification of intrauterine pregnancy with fetal heartbeat) were analyzed. Cost calculations used the government-issued tariff specifying insurers' payments and patients' copayments with projected delivery rates using early literature.

Main Outcome Measures

Assessment of functional clinical and laboratory infertility services and costs.

Results

A total of 207 IVF cycles were initiated, 60 of which led to transfer of ≥1 high-grade embryo and 5 to ongoing pregnancies. The projected average cost per cycle was 1,521 USD. Using optimistic and conservative assumptions, the estimated costs per delivery for women <35 years were 4,540 and 5,156 USD, respectively.

Conclusions

Reduced-cost infertility services were initiated and integrated within a maternal health department of a public hospital in a low-income country. This integration required commitment, collaboration, leadership, and a universal health financing system. Low-income countries, such as Rwanda, might consider infertility treatment and IVF for younger patients as part of an equitable and affordable health care benefit.

Comparative effectiveness of gonadotropins used for ovarian stimulation during assisted reproductive technologies (ART) in France: A real-world observational study from the French nationwide claims database (SNDS)

This comparative non-interventional study using data from the French National Health Database (Système National des Données de Santé) investigated real-world (cumulative) live birth outcomes following ovarian stimulation, leading to oocyte pickup with either originator recombinant human follicle-stimulating hormone (r-hFSH) products (alfa or beta), r-hFSH alfa biosimilars, or urinaries including mainly HP-hMG (menotropins), and marginally u-hFSH-HP (urofollitropin). Using data from 245,534 stimulations (153,600 women), biosimilars resulted in a 19% lower live birth (adjusted odds ratio (OR) 0.81, 95% confidence interval (CI) 0.76-0.86) and a 14% lower cumulative live birth (adjusted hazard ratio (HR) 0.86, 95% CI 0.82-0.89); and urinaries resulted in a 7% lower live birth (adjusted OR 0.93, 95% CI 0.90-0.96) and an 11% lower cumulative live birth (adjusted HR 0.89, 95% CI 0.87-0.91) versus originator r-hFSH alfa. Results were consistent across strata (age and ART strategy), sensitivity analysis using propensity score matching, and with r-hFSH alfa and beta as the reference group.

Effectiveness of recombinant human follicle-stimulating hormone (r-hFSH): recombinant human luteinizing hormone versus r-hFSH alone in assisted reproductive technology treatment cycles among women aged 35-40 years: A German database study

This non-interventional study compared the effectiveness of recombinant human follicle-stimulating hormone (r-hFSH) and recombinant human luteinizing hormone (r-hLH) (2:1 ratio) versus r-hFSH alone for ovarian stimulation (OS) during assisted reproductive technology treatment in women aged 35-40 years, using real-world data from the Deutsches IVF-Register (D·I·R). Numerically higher clinical pregnancy (29.8% [95% CI 28.2, 31.6] vs. 27.8% [26.5, 29.2]) and live birth (20.3% [18.7, 21.8] vs. 18.0% [16.6, 19.4]) rates were observed with r-hFSH:r-hLH versus r-hFSH alone. The treatment effect was consistently higher for r-hFSH:r-hLH compared with r-hFSH alone in terms of clinical pregnancy (relative risk [RR] 1.16 [1.05, 1.26]) and live birth (RR 1.16 [1.02, 1.31]) in a post-hoc analysis of women with 5-14 oocytes retrieved (used as a surrogate for normal ovarian reserve), highlighting the potential benefits of r-hFSH:r-hLH for OS in women aged 35-40 years with normal ovarian reserve.

Predicted probabilities of live birth following assisted reproductive technology using United States national surveillance data from 2016 to 2018

BACKGROUND

As the use of in vitro fertilization continues to increase in the United States, up-to-date models that estimate cumulative live birth rates after multiple oocyte retrievals and embryo transfers (fresh and frozen) are valuable for patients and clinicians weighing treatment options.

OBJECTIVE

This study aimed to develop models that generate predicted probabilities of live birth in individuals considering in vitro fertilization based on demographic and reproductive characteristics.

STUDY DESIGN

Our population-based cohort study used data from the National Assisted Reproductive Technology Surveillance System 2016 to 2018, including 196,916 women who underwent 207,766 autologous embryo transfer cycles and 25,831 women who underwent 36,909 donor oocyte transfer cycles. We used data on autologous in vitro fertilization cycles to develop models that estimate a patient's cumulative live birth rate after all embryo transfers (fresh and frozen) within 12 months after 1, 2, and 3 oocyte retrievals in new and returning patients. Among patients using donor oocytes, we estimated the cumulative live birth rate after their first, second, and third embryo transfers. Multinomial logistic regression models adjusted for age, prepregnancy body mass index (imputed for 18% of missing values), parity, gravidity, and infertility diagnoses were used to estimate the cumulative live birth rate.

RESULTS

Among new and returning patients undergoing autologous in vitro fertilization, female age had the strongest association with cumulative live birth rate. Other factors associated with higher cumulative live birth rates were lower body mass index and parity or gravidity ≥1, although results were inconsistent. Infertility diagnoses of diminished ovarian reserve, uterine factor, and other reasons were associated with a lower cumulative live birth rate, whereas male factor, tubal factor, ovulatory disorders, and unexplained infertility were associated with a higher cumulative live birth rate. Based on our models, a new patient who is 35 years old, with a body mass index of 25 kg/m2, no previous pregnancy, and unexplained infertility diagnoses, has a 48%, 69%, and 80% cumulative live birth rate after the first, second, and third oocyte retrieval, respectively. Cumulative live birth rates are 29%, 48%, and 62%, respectively, if the patient had diminished ovarian reserve, and 25%, 41%, and 52%, respectively, if the patient was 40 years old (with unexplained infertility). Very few recipient characteristics were associated with cumulative live birth rate in donor oocyte patients.

CONCLUSION

Our models provided estimates of cumulative live birth rate based on demographic and reproductive characteristics to help inform patients and providers of a woman's probability of success after in vitro fertilization.

Quality of clinical prediction models in in vitro fertilisation: Which covariates are really important to predict cumulative live birth and which models are best?

The improvement in IVF cryopreservation techniques over the last 20 years has led to an increase in elective single embryo transfer, thus reducing multiple pregnancy rates. This strategy of successive transfers of fresh followed by frozen embryos has resulted in the acceptance of using cumulative live birth over complete cycles of IVF as a critical measure of success. Clinical prediction models are a useful way of estimating the cumulative chances of success for couples tailored to their individual clinical factors, which help them prepare for and plan future treatment. In this review, we describe several models that predict cumulative live birth and recommend which should be used by couples and/or their clinicians and when they should be used. We also discuss the most relevant predictors to consider when either developing new IVF prediction models or updating existing models.

Association of the Cumulative Live Birth Rate with the Factors in Assisted Reproductive Technology: A Retrospective Study of 16,583 Women

The cumulative live birth rate (CLBR) can better reflect the overall treatment effect by successive treatments, and continuous rather than categorical variables as exposure variables can increase the statistical power in detecting the potential correlation. Therefore, the dose-response relationships might find an optimal dose for the better CLBR, offering evidence-based references for clinicians. To determine the dose-response relationships of the factors and the optimal ranges of the factors in assisted reproductive technology (ART) associated with a higher CLBR, this study retrospectively analyzed 16,583 patients undergoing the first in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) from January 2017 to January 2019. Our study demonstrated the optimal ranges of age with a higher CLBR were under 32.10 years. We estimated the CLBR tends to increase with increased levels of AMH at AMH levels below 1.482 ng/mL, and the CLBR reaches a slightly high level at AMH levels in the range from 2.58-4.18 ng/mL. The optimal ranges of basal FSH with a higher CLBR were less than 9.13 IU. When the number of cryopreserved embryos was above 1.055 and the number of total transferred embryos was 2, the CLBR was significantly higher. In conclusion, there is a non-linear dose-response relationship between the CLBR with age, AMH, basal FSH, and the number of cryopreserved embryos and total transferred embryos. We proposed the optimal ranges of the five factors that were correlated with a higher CLBR in the first oocyte retrieval cycle, which may help consultation at IVF clinics.

Predicting cumulative live birth for couples beginning their second complete cycle of in vitro fertilization treatment

STUDY QUESTION

Can we develop an IVF prediction model to estimate individualized chances of a live birth over multiple complete cycles of IVF in couples embarking on their second complete cycle of treatment?

SUMMARY ANSWER

Yes, our prediction model can estimate individualized chances of cumulative live birth over three additional complete cycles of IVF.

WHAT IS KNOWN ALREADY

After the completion of a first complete cycle of IVF, couples who are unsuccessful may choose to undergo further treatment to have their first child, while those who have had a live birth may decide to have more children. Existing prediction models can estimate the overall chances of success in couples before commencing IVF but are unable to revise these chances on the basis of the couple’s response to a first treatment cycle in terms of the number of eggs retrieved and pregnancy outcome. This makes it difficult for couples to plan and prepare emotionally and financially for the next step in their treatment.

STUDY DESIGN, SIZE, DURATION

For model development, a population-based cohort was used of 49 314 women who started their second cycle of IVF including ICSI in the UK from 1999 to 2008 using their own oocytes and their partners’ sperm. External validation was performed on data from 39 442 women who underwent their second cycle from 2010 to 2016.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Data about all UK IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA) database. Using a discrete time logistic regression model, we predicted the cumulative probability of live birth from the second up to and including the fourth complete cycles of IVF. Inverse probability weighting was used to account for treatment discontinuation. Discrimination was assessed using c-statistic and calibration was assessed using calibration-in-the-large and calibration slope.

MAIN RESULTS AND THE ROLE OF CHANCE

Following exclusions, 49 314 women with 73 053 complete cycles were included. 12 408 (25.2%) had a live birth resulting from their second complete cycle. Cumulatively, 17 394 (35.3%) had a live birth over complete cycles two to four. The model showed moderate discriminative ability (c-statistic: 0.65, 95% CI: 0.64 to 0.65) and evidence of overprediction (calibration-in-the-large = −0.08) and overfitting (calibration slope 0.85, 95% CI: 0.81 to 0.88) in the validation cohort. However, after recalibration the fit was much improved. The recalibrated model identified the following key predictors of live birth: female age (38 versus 32 years—adjusted odds ratio: 0.59, 95% CI: 0.57 to 0.62), number of eggs retrieved in the first complete cycle (12 versus 4 eggs; 1.34, 1.30 to 1.37) and outcome of the first complete cycle (live birth versus no pregnancy; 1.78, 1.66 to 1.91; live birth versus pregnancy loss; 1.29, 1.23 to 1.36). As an example, a 32-year-old with 2 years of non-tubal infertility who had 12 eggs retrieved from her first stimulation and had a live birth during her first complete cycle has a 46% chance of having a further live birth from the second complete cycle of IVF and an 81% chance over a further three cycles.

LIMITATIONS, REASONS FOR CAUTION

The developed model was updated using validation data that was 6 to 12 years old. IVF practice continues to evolve over time, which may affect the accuracy of predictions from the model. We were unable to adjust for some potentially important predictors, e.g. BMI, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. These were not available in the linked HFEA dataset.

WIDER IMPLICATIONS OF THE FINDINGS

By appropriately adjusting for couples who discontinue treatment, our novel prediction model will provide more realistic chances of live birth in couples starting a second complete cycle of IVF. Clinicians can use these predictions to inform discussion with couples who wish to plan ahead. This prediction tool will enable couples to prepare emotionally, financially and logistically for IVF treatment.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. The authors have no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

When ART fails: figures, experiences, interventions and a plea for the 'plan B'

Infertility is perceived by many of those affected by it as one of the most stressful episodes in life. Assisted reproduction can help only some of the people with a desire for children to experience the birth of a biological child. Most people who remain involuntarily childless eventually come to terms with the situation; their psychological well-being is not lastingly affected. However, they should envisage a ‘plan B’ as early as possible. The prospect of permanent childlessness should not be an unmentionable topic, neither for couples themselves nor for the doctors treating them.