Trends in the incidence of major birth defects after assisted reproductive technologies in Lombardy Region, Northern Italy

PURPOSE

The incidence of birth defects is increased in children born after assisted reproductive technologies (ART). However, changes in ART over time could influence this incidence. To investigate this issue, we present the frequency and trends of birth defects in ART and natural pregnancies in Lombardy, Northern Italy, during the period 2014-2020.

METHODS

This is a population-based study using automated system of healthcare utilization (HCU) databases. ART pregnancies included only those obtained with conventional IVF or ICSI. After identifying the total number of deliveries, the rate of newborns with birth defects was compared between natural and ART pregnancies. A logistic regression model was used to calculate the adjusted odd ratio (OR). Analyses were repeated for every calendar year.

RESULTS

Overall, 508,421 deliveries were identified, of which 14,067 (2.8%) were achieved after IVF-ICSI. A decreasing trend in birth defects over time was highlighted. The adjusted OR dropped from 1.40 (95%CI: 1.03-1.91) in 2014 to 0.92 (95%CI: 0.69-1.22) in 2020. During the study period, a significant reduction in multiple pregnancy and in the ratio of ICSI to conventional IVF was also observed, explaining at least in part the positive trend observed for birth defects.

CONCLUSION

The increased risk of birth defects in children born after IVF-ICSI is not steady over time. A decline of this risk emerged in our region. Policy changes in ART may explain this beneficial effect.

Monozygotic twin rate among ART centers: a multicenter analysis of data from 18 Italian units

PURPOSE

The risk of monozygotic twins (MZTs) is increased in couples undergoing assisted reproductive technology (ART) treatments. Several systematic reviews have investigated the possible determinants linked to ART, but results obtained have not been conclusive. The study aims to investigate whether the incidence of MZT differed among ART centers.

METHODS

This is a multicenter retrospective cohort study using the Italian ART National Registry database and involving the centers reporting data from individual ART cycles from 2015 to 2019. To investigate the incidence of MZT, only single embryo transfer cycles were considered. Women who had sex-discordant deliveries were excluded. MZT rate was calculated as the number of multiple pregnancies (more than one gestational sac at first ultrasound) out of the total number of clinical pregnancies. A binomial distribution model was used to determine the 95% CI of the frequency of MZT.

RESULTS

Eighteen centers were included, and they provided data on 10,433 pregnancies. The total number of MZT was 162, corresponding to an incidence of 1.5% (95% CI: 1.3-1.8%). The rate of MZT among centers varied between 0% (95% CI: 0.0-25.9%) and 3.2% (95% CI: 1.3-8.1%). All the 95% CIs included 1.5%, rejecting the hypothesis that the MZT rate may significantly differ among centers.

CONCLUSIONS

The rate of MZT did not significantly vary among ART centers. Local factors are unlikely to explain the increased rate of MZT in ART pregnancies.

Internal validation and comparison of predictive models to determine success rate of infertility treatments: a retrospective study of 2485 cycles

Infertility is a significant health problem and assisted reproductive technologies to treat infertility. Despite all efforts, the success rate of these methods is still low. Also, each of these methods has side effects and costs. Therefore, accurate prediction of treatment success rate is a clinical challenge. This retrospective study aimed to internally validate and compare various machine learning models for predicting the clinical pregnancy rate (CPR) of infertility treatment. For this purpose, data from 1931 patients consisting of in vitro fertilization (IVF) or intra cytoplasmic sperm injection (ICSI) (733) and intra uterine insemination (IUI) (1196) treatments were included. Also, no egg or sperm donation data were used. The performance of machine learning algorithms to predict clinical pregnancy were expressed in terms of accuracy, recall, F-score, positive predictive value (PPV), brier score (BS), Matthew correlation coefficient (MCC), and receiver operating characteristic. The significance of the features with CPR and AUCs was evaluated by Student's t test and DeLong’s algorithm. Random forest (RF) model had the highest accuracy in the IVF/ICSI treatment. The sensitivity, F1 score, PPV, and MCC of the RF model were 0.76, 0.73, 0.80, and 0.5, respectively. These values for IUI treatment were 0.84, 0.80, 0.82, and 0.34, respectively. The BS was 0.13 and 0.15 for IVF/ICS and IUI, respectively. In addition, the estimated AUCs of the RF model for IVF/ICS and IUI were 0.73 and 0.7, respectively. Some essential features were obtained based on RF ranking for the two datasets, including age, follicle stimulation hormone, endometrial thickness, and infertility duration. The results showed a strong relationship between clinical pregnancy and a woman's age. Also, endometrial thickness and the number of follicles decreased with increasing female age in both treatments.

2017–2018 Assisted Reproduction Cost Analysis Performance Indexes: Lombardy County Case Study

Objective: The aim of the present study was to analyze the IVF success rates and the economic cost per delivery in all the public funded IVF Units in Lombardy in the 2017–2018 period and to assess any significant difference in ART outcomes among the enrolled centers.

Methods: Analysis of costs for the 2017 and 2018 fresh transfer delivery rate (DR) and Cumulative delivery rate (CDR) considering both fresh and frozen cycles were extracted from the ART Italian Registry on oocytes retrievals, fresh and frozen embryos and oocytes embryo transfer performed in 22 Lombardy IVF Units.

Results: In 2017, 29,718 procedures were performed, resulting in 4,543 pregnancies and 3,253 deliveries. In 2018, there were 29,708 procedures, 4,665 pregnancies and 3,348 deliveries. Pregnancies lost to follow up were 5.0% with a (range of 0–67.68%) in 2017 and 3.4% (range of 0–45.1%) in 2018. The cost reimbursement for the cycles were €2,232 ($2,611) for oocyte retrieval and €2,194 ($2,567) for embryo transfer, excluding ovarian stimulation therapy and luteal phase support. 19.33 (5.80). The DR was 13.23 ± 5.69% (range 2.86–29.11%) in 2017 and 19.33 ± 5.80% in 2018 (range 11.82–34.98 %) and the CDR was 19.86 ± 9.38% (range 4.43–37.88%) in 2017 and 21.32 ± 8.84% (range 4.24–37.11%). The mean multiple pregnancy delivery rate (MDR) was 11.08 ± 5.55% (range 0.00–22.73%) in 2017 and 10.41 ± 4.99% (range 1.33–22.22%) in 2018. The mean CDR cost in euros was 26,227 ± 14,737 in 2017 and 25,018 ± 16,039 in 2018. The mean CDR cost among centers was 12,480 to 76,725 in 2017 and 12,973 to 86,203 in 2018.

Conclusions: Our findings show impressive differences in the DR and CDR among centers and the importance of cryopreservation in patients' safety and economic cost reduction suggesting the formulation of specific KPI's (Key performance indexes) and minimal performance indexes (PI) as a basis for the allocation of public or insurance resources. In particular, the reduction of multiple pregnancy rates costs, may lead to a more widespread use of ART even in lower resources countries.

A large observational data study supporting the PROsPeR score classification in poor ovarian responders according to live birth outcome

STUDY QUESTION

Can the Poor Responder Outcome Prediction (PROsPeR) score identify live birth outcomes in subpopulations of patients with poor ovarian response (POR) defined according to the ESHRE Bologna criteria (female age, anti-Müllerian hormone (AMH), number of oocytes retrieved during the previous cycle (PNO) after treatment with originator recombinant human follitropin alfa?

SUMMARY ANSWER

The PROsPeR score discriminated the probability of live birth in patients with POR using observational data with fair discrimination (AUC ≅ 70%) and calibration, and the AUC losing less than 5% precision compared with a model developed using the observational data.

WHAT IS KNOWN ALREADY

Although scoring systems for the likelihood of live birth after ART have been developed, their accuracy may be insufficient, as they have generally been developed in the general population with infertility and were not validated for patients with POR. The PROsPeR score was developed using data from the follitropin alfa (GONAL-f; Merck KGaA, Darmstadt, Germany) arm of the Efficacy and Safety of Pergoveris in Assisted Reproductive Technology (ESPART) randomized controlled trial (RCT) and classifies women with POR as mild, moderate or severe, based upon three variables: female age, serum AMH level and number of oocytes retrieved during the previous cycle (PNO).

STUDY DESIGN, SIZE, DURATION

The external validation of the PROsPeR score was completed using data derived from eight different centres in France. In addition, the follitropin alfa data from the ESPART RCT, originally used to develop the PROsPeR score, were used as reference cohort. The external validation of the PROsPeR score l was assessed using AUC. A predetermined non-inferiority limit of 0.10 compared with a reference sample and calibration (Hosmer-Lemeshow test) were the two conditions required for evaluation.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The observational cohort included data from 8085 ART treatment cycles performed with follitropin alfa in patients with POR defined according to the ESHRE Bologna criteria (17.6% of the initial data set). The ESPART cohort included 477 ART treatment cycles with ovarian stimulation performed with follitropin alfa in patients with POR.

MAIN RESULTS AND THE ROLE OF CHANCE

The external validation of the PROsPeR score to identify subpopulations of women with POR with different live birth outcomes was shown in the observational cohort (AUC = 0.688; 95% CI: 0.662, 0.714) compared with the ESPART cohort (AUC = 0.695; 95% CI: 0.623, 0.767). The AUC difference was -0.0074 (95% CI: -0.083, 0.0689). This provided evidence, with 97.5% one-sided confidence, that there was a maximum estimated loss of 8.4% in discrimination between the observational cohort and the ESPART cohort, which was below the predetermined margin of 10%. The Hosmer-Lemeshow test did not reject the calibration when comparing observed and predicted data (Hosmer-Lemeshow test = 1.266688; P = 0.260).

LIMITATIONS, REASONS FOR CAUTION

The study was based on secondary use of data that had not been collected specifically for the analysis reported here and the number of characteristics used to classify women with POR was limited to the available data. The data were from a limited number of ART centres in a single country, which may present a bias risk; however, baseline patient data were similar to other POR studies.

WIDER IMPLICATIONS OF THE FINDINGS

This evaluation of the PROsPeR score using observational data supports the notion that the likelihood of live birth may be calculated with reasonable precision using three readily available pieces of data (female age, serum AMH and PNO). The PROsPeR score has potential to be used to discriminate expected probability of live birth according to the degree of POR (mild, moderate, severe) after treatment with follitropin alfa, enabling comparison of performance at one centre over time and the comparison between centres.

STUDY FUNDING/COMPETING INTEREST(S)

This analysis was funded by Merck KGaA, Darmstadt, Germany. P.L. received grants from Merck KGaA, outside of the submitted work. N.M. reports grants, personal fees and non-financial support from Merck KGaA outside the submitted work. T.D.H. is Vice President and Head of Global Medical Affairs Fertility, Research and Development at Merck KGaA, Darmstadt, Germany. P.A. has received personal fees from Merck KGaA, Darmstadt, Germany, outside the submitted work. C.R. has received grants and personal fees from Gedeon Richter and Merck Serono S.A.S., France, an affiliate of Merck KGaA, Darmstadt, Germany, outside the submitted work. P.S. reports congress support from Merck Serono S.A.S., France (an affiliate of Merck KGaA, Darmstadt, Germany), Gedeon Richter, TEVA and MDS outside the submitted work. C.A., J.P., G.P. and R.W. declare no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

Do Strategies Favoring Frozen-thawed Embryo Transfer Have an Impact on Differences in IVF Success Rate, Multiple Pregnancy Rate, and Cost per Live Birth Between Fertility Clinics?

The aim of this retrospective cohort study is to establish whether strategies favoring frozen-thawed embryo transfer (FET) have an impact on differences in cumulative live birth rate (CLBR), weighted mean cost per live birth, and multiple pregnancy rate (MPR) between fertility clinics. Data were extracted from the Assisted Reproductive Technology (ART) Italian National Registry and refer to classical IVF or intracytoplasmic sperm injection (ICSI) cycles performed in 2018 in public funded Lombardy region fertility clinics. Propensity to FET cycles was expressed with the so-called freezing tendency index (FTI): [(No. of FETs + No. of transfers of embryos obtained from frozen-thawed oocytes) / (No. of fresh ETs + No. of canceled IVF cycles + Numerator)] × 100. Fertility clinics were divided according to their FTI: group A (FTI: 0-20%); group B (FTI: 20-40%); and group C (FTI: 40-60%). Groups A, B, and C included 6, 8, and 8 fertility clinics, respectively. The CLBR (95% CI) per started COH cycle was 13.1% (11.8-14.5%) in group A, 19.6% (18.6-20.7%) in group B, and 27.8% (26.8-28.9%) in group C (p < 0.0001). The weighted mean live birth cost was 32,770 ± 10,662 € in group A, 25,863 ± 11,510 € in group B, and 20,426 ± 3788 € in group C (p < 0.0001). The MPR (95% CI) was 15.4% (12.1-19.4%) in group A, 10.2% (8.7-12.1%) in group B (p = 0.0065), and 6.3% (5.2-7.6%) in group C (p = 0.0001). In conclusion, our results suggest that strategies favoring FET cycles are associated with an increased CLBR, a decreased weighted mean cost per live birth, and a decreased MPR.

Effects of PGT-A on Pregnancy Outcomes for Young Women Having One Previous Miscarriage with Genetically Abnormal Products of Conception

In this retrospective study, the effect of preimplantation genetic testing for aneuploidy (PGT-A) was evaluated in women younger than 38 years with a history of one prior miscarriage and embryonic chromosomal abnormalities were detected in previous products of conception (POCs). Abnormal karyotypes were detected in POCs at our center between January 2014 and December 2017. Of the women included in this analysis, 124 continued with conventional in vitro fertilization/intracytoplasmic sperm injection cycles (non-PGT-A group) and 93 chose PGT-A cycles (PGT-A group), and the pregnancy outcomes in both groups were compared. Although the clinical pregnancy rate per embryo transfer was significantly higher in the PGT-A group (67.23% vs. 51.85%, p-adj = 0.01), no between-group differences were found in the live birth rate or miscarriage rate (45.38% vs. 40.74%, p-adj = 0.59; 16.25% vs. 14.29%, p-adj = 0.15). Women in both groups had comparative cumulative live birth rates (PGT-A vs. non-PGT-A, 58.06% vs. 53.23%, p = 0.48). The main results of this study suggest that PGT-A is not associated with an increased likelihood of a live birth or a decreased rate of miscarriage among women younger than 38 years without recurrent pregnancy loss and with a history of POCs with embryonic chromosomal abnormalities.

Predicting the chance on live birth per cycle at each step of the IVF journey: external validation and update of the van Loendersloot multivariable prognostic model

OBJECTIVE

To study the performance of the 'van Loendersloot' prognostic model for our clinic's in vitro fertilisation (IVF) in its original version, the refitted version and in an adapted version replacing previous by current cycle IVF laboratory variables.

METHODS

This retrospective cohort study in our academic tertiary fertility clinic analysed 1281 IVF cycles of 591 couples, who completed at least one 2nd-6th IVF cycle with own fresh gametes after a previous IVF cycle with the same partner in our clinic between 2010 and 2018. The outcome of interest was the chance on a live birth after one complete IVF cycle (including all fresh and frozen embryo transfers from the same episode of ovarian stimulation). Model performance was expressed in terms of discrimination (c-statistics) and calibration (calibration model, comparison of prognosis to observed ratios of five disjoint groups formed by the quintiles of the IVF prognoses and a calibration plot).

RESULTS

A total of 344 live births were obtained (26.9%). External validation of the original van Loendersloot model showed a poor c-statistic of 0.64 (95% CI: 0.61 to 0.68) and an underestimation of IVF success. The refitted and the adapted models showed c-statistics of respectively 0.68 (95% CI: 0.65 to 0.71) and 0.74 (95% CI: 0.70 to 0.77). Similar c-statistics were found with cross-validation. Both models showed a good calibration model; refitted model: intercept=0.00 (95% CI: -0.23 to 0.23) and slope=1.00 (95% CI: 0.79 to 1.21); adapted model: intercept=0.00 (95% CI: -0.18 to 0.18) and slope=1.00 (95% CI: 0.83 to 1.17). Prognoses and observed success rates of the disjoint groups matched well for the refitted model and even better for the adapted model.

CONCLUSION

External validation of the original van Loendersloot model indicated that model updating was recommended. The good performance of the refitted and adapted models allows informing couples about their IVF prognosis prior to an IVF cycle and at the time of embryo transfer. Whether this has an impact on couple's expected success rates, distress and IVF discontinuation can now be studied.

Cumulative Live-Birth Rates by Maternal Age after One or Multiple In Vitro Fertilization Cycles: An Institutional Experience

Background

The aim of this retrospective study is to investigate the cumulative live birth rate (CLBR) following one or more completed in vitro fertilization (IVF) cycles (up to 6 cycles) stratified by maternal age and type of infertility.

Materials and Methods

In this retrospective study, five hundred forty-seven women who received 736 fresh ovarian stimulation/embryo transfer cycles between January 2016 and December 2016 were included in the study at a tertiary care center located in Lebanon.

Results

In all women, the live birth rate for the first cycle was 33.0% [95% confidence interval (CI): 27.8-38.2]. The CLBR showed an increase with each successive fresh cycle to reach 56.9% (95% CI: 51.2-62.4) after 3 cycles and 67.9% (95% CI: of 62.5-73.0) after 6 cycles. The CLBR following 6 cycles reached 69.9% (95% CI: 63.8-75.6) in women younger than 35 years. In women older than 40 years, however, the live birth rate for the first cycle was significantly low at 3.1% (95% CI: 0.3-9.5) with a plateau in success rates after 4 cycles reaching 21.9% (95% CI: 9.2-40.0). Couples with different types of infertility had CLBRs ranging from 65% to 72%, with the exception of women with low ovarian reserve, where CLBRs reached 29.4% (95% CI: 10.3-56.0).

Conclusion

The CLBR at a referral center in a Middle Eastern country reached 67.9 % after 6 cycles, with variations by age and type of infertility treatment. These findings are encouraging for patients insisting to extend their treatment beyond 4 to 5 cycles.

Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective

OBJECTIVE

To develop a random forest model (RFM) to predict implantation potential of a transferred embryo and compare it with a multivariate logistic regression model (MvLRM), based on data from a large cohort including in vitro fertilization (IVF) patients treated with the use of single-embryo transfer (SET) of blastocyst-stage embryos.

DESIGN

Retrospective study of a 2-year single-center cohort of women undergoing IVF or intracytoplasmatic sperm injection (ICSI).

SETTING

Academic hospital.

PATIENT(S)

Data from 1,052 women who underwent fresh SET in IVF or ICSI cycles were included.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

The performance of both RFM and MvLRM to predict pregnancy was quantified in terms of the area under the receiver operating characteristic (ROC) curve (AUC), classification accuracy, specificity, and sensitivity.

RESULT(S)

ROC analysis resulted in an AUC of 0.74 ± 0.03 for the proposed RFM and 0.66 ± 0.05 for the MvLRM for the prediction of ongoing pregnancies of ≥11 weeks. This RFM approach and the MvLRM yielded, respectively, sensitivities of 0.84 ± 0.07 and 0.66 ± 0.08 and specificities of 0.48 ± 0.07 and 0.58 ± 0.08.

CONCLUSION(S)

The performance to predict ongoing implantation will significantly improve with the use of an RFM approach compared with MvLRM.

Cumulative live birth rate: time for a consensus?

Traditionally, IVF success rates have been reported in terms of live birth per fresh cycle or embryo transfer. With the increasing use of embryo freezing and thawing it is essential that we report not only outcomes following fresh but also those after frozen embryo transfer as a complete measure of success of an IVF treatment. Most people agree that an individual's chance of having a baby following fresh and frozen embryo transfer should be described as cumulative live birth rate. However, views on the most appropriate parameters required to calculate such an outcome have been inconsistent. There is an additional dimension-time for all frozen embryos to be used up by a couple, which can influence the outcome. Given that cumulative live birth rate is generally perceived to be the preferred reporting system in IVF, it is time to have an international consensus on how this statistic is calculated, reported and interpreted by stakeholders across the world.

External validation and calibration of IVFpredict: a national prospective cohort study of 130,960 in vitro fertilisation cycles

BACKGROUND

Accurately predicting the probability of a live birth after in vitro fertilisation (IVF) is important for patients, healthcare providers and policy makers. Two prediction models (Templeton and IVFpredict) have been previously developed from UK data and are widely used internationally. The more recent of these, IVFpredict, was shown to have greater predictive power in the development dataset. The aim of this study was external validation of the two models and comparison of their predictive ability.

METHODS AND FINDINGS

130,960 IVF cycles undertaken in the UK in 2008-2010 were used to validate and compare the Templeton and IVFpredict models. Discriminatory power was calculated using the area under the receiver-operator curve and calibration assessed using a calibration plot and Hosmer-Lemeshow statistic. The scaled modified Brier score, with measures of reliability and resolution, were calculated to assess overall accuracy. Both models were compared after updating for current live birth rates to ensure that the average observed and predicted live birth rates were equal. The discriminative power of both methods was comparable: the area under the receiver-operator curve was 0.628 (95% confidence interval (CI): 0.625-0.631) for IVFpredict and 0.616 (95% CI: 0.613-0.620) for the Templeton model. IVFpredict had markedly better calibration and higher diagnostic accuracy, with calibration plot intercept of 0.040 (95% CI: 0.017-0.063) and slope of 0.932 (95% CI: 0.839-1.025) compared with 0.080 (95% CI: 0.044-0.117) and 1.419 (95% CI: 1.149-1.690) for the Templeton model. Both models underestimated the live birth rate, but this was particularly marked in the Templeton model. Updating the models to reflect improvements in live birth rates since the models were developed enhanced their performance, but IVFpredict remained superior.

CONCLUSION

External validation in a large population cohort confirms IVFpredict has superior discrimination and calibration for informing patients, clinicians and healthcare policy makers of the probability of live birth following IVF.

To what extent does Anti-Mullerian Hormone contribute to a better prediction of live birth after IVF?

OBJECTIVE

We assessed the predictive value added by Anti-Mullerian Hormone (AMH) to currently validated live birth (LB) prediction models.

METHODS

Based on recent data from our center, we compared the external validity of the Templeton Model (TM) and its recent improvement (TMA) to select our model of reference. The added predictive value of AMH was assessed in testing the likelihood ratio significance and the Net Reclassification Index (NRI). The surrogate utility of AMH was tested by conducting an exploratory stepwise logistic regression.

RESULTS

Based on 715 cycles, the original TM had poor performances (auROC C = 0.61 [0.58, 0.66], improving by fitting TM to our data (C = 0.71[0.66, 0.75]. TMA fitting proved better (C = 0.76; 95 %CI: 0.71, 0.80) and was selected as model of reference. Adding AMH to TMA or TM had no effect on discrimination (C = 0.76; 95 %CI: 0.72, 0.80), the likelihood ratio test was significant (p = 0.023), but the NRI was not (6.7 %; p = 0.055). A stepwise exploratory logistic regression identified the effects of age, previous IVF resulting in LB, time trend and AMH, leading to a prediction model reduced to four predictors (C = 0.75 [0.70, 0.81]).

CONCLUSION

The added predictive value of AMH is limited. A possible surrogate/simplifying effect of AMH was found in eliminating 9/13 predictors from the model of reference. We conclude that whereas AMH does not add significant predictive value to the existing model, it contributes to simplifying the equation to reliable, easy to collect, and available in all databases predictors: age, AMH, time trend and female previous fertility history.

Comparison of two models predicting IVF success; the effect of time trends on model performance

STUDY QUESTION

How well does the recently developed UK model predicting the success rate of IVF treatment (the 2011 Nelson model) perform in comparison with a UK model developed in the early 1990s (the Templeton model)?

SUMMARY ANSWER

Both models showed similar performance, after correction for the increasing success rate over time of IVF.

WHAT IS KNOWN ALREADY

For counselling couples undergoing IVF treatment it is of paramount importance to be able to predict success. Several prediction models for the chance of success after IVF treatment have been developed. So far, the Templeton model has been recommended as the best approach after having been validated in several independent patient data sets. The Nelson model, developed in 2011 and characterized by the largest development sample containing the most recently treated couples, may well perform better.

STUDY DESIGN, SIZE, DURATION

We tested both models in couples that were included in a national cohort study carried out in the Netherlands between the beginning of January 2002 and the end of December 2004.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We analysed the IVF cycles of Dutch couples with primary infertility (n = 5176). The chance of success was calculated using the two UK models that had been developed using the information collected in the Human Fertilisation and Embryology Authority database. Women were treated in 1991-1994 (Templeton) or 2003-2007 (Nelson). The outcome of success for both UK models is the occurrence of a live birth after IVF but the outcome in the Dutch data is an ongoing pregnancy. In order to make the outcomes compatible, we used a factor to convert the chance of live birth to ongoing pregnancy and use the overall terms 'success or no success after IVF'. The discriminative ability and the calibration of both models were assessed, the latter before and after adjustment for time trends in IVF success rates.

MAIN RESULTS AND THE ROLE OF CHANCE

The two models showed a similarly limited degree of discriminative ability on the tested data (area under the receiver operating characteristic curve 0.597 for the Templeton model and 0.590 for the Nelson model). The Templeton model underestimated the success rate (observed 21% versus predicted 14%); the Nelson model overestimated the success rate (observed 21% versus predicted 29%). When the models were adjusted for the changing success rates over time, the calibration of both models considerably improved (Templeton observed 21% versus predicted 20%; Nelson observed 21% versus predicted 24%).

LIMITATIONS, REASONS FOR CAUTION

We could only test the models in couples with primary infertility because detailed information on secondary infertile couples was lacking in the Dutch data. This shortcoming may have negatively influenced the performance of the Nelson model.

WIDER IMPLICATIONS OF THE FINDINGS

The changes in success rates over time should be taken into account when assessing prediction models for estimating the success rate of IVF treatment. In patients with primary infertility, the choice to use the Templeton or Nelson model is arbitrary.

Predicting live birth chances for women with multiple consecutive failing IVF cycles: a simple and accurate prediction for routine medical practice

BACKGROUND

Women having experienced several consecutive failing IVF cycles constitute a critical and particular subset of patients, for which growing perception of irremediable failure, increasing costs and IVF treatment related risks necessitate appropriate decision making when starting or not a new cycle. Predicting chances of LB might constitute a useful tool for discussion between the patient and the clinician. Our essential objective was to dispose of a simple and accurate prediction model for use in routine medical practice. The currently available predictive models applicable to general populations cannot be considered as accurate enough for this purpose.

METHODS

Patients with at least four consecutive Failing cycles (CFCs) were selected. We constructed a predictive model of LB occurrence during the last cycle, by using a stepwise logistic regression, using all the baseline patient characteristics and intermediate stage variables during the four first cycles.

RESULTS

On as set of 151 patients, we identified five determinant predictors: the number of previous cycles with at least one gestational sac (NGS), the mean number of good-quality embryos, age, male infertility (MI) aetiology and basal FSH. Our model was characterized by a much higher discrimination as the existing models (C-statistics=0.76), and an excellent calibration.

CONCLUSIONS

Couples having experienced multiple IVF failures need precise and appropriate information to decide to resume or interrupt their fertility project. Our essential objective was to dispose of a simple and accurate prediction model to allow a routine practice use. Our model is adapted to this purpose: It is very simple, combines five easily collected variables in a short calculation; it is more accurate than existing models, with a fair discrimination and a well calibrated prediction.

Joint modeling of success and treatment discontinuation in in vitro fertilization programs: a retrospective cohort study

BACKGROUND

As discontinuation in in vitro fertilization (IVF) programs has been associated with a poor prognosis, one hypothesis is that some couple-specific predictive factors in IVF may be shared with opposite effect by both success (i.e. live birth) and treatment discontinuation processes. Our objective was to perform a joint analysis of these two processes to examine the hypothesis of a link between the two processes.

METHODS

Analyses were conducted on a retrospective cohort of 3,002 women who began IVF between 1998 and 2002 in two French IVF centers: a Parisian center and a center in a medium-sized city in central France. A shared random effects model based on a joint modelization of IVF treatment success and discontinuation was used to study the link between the two processes.

RESULTS

Success and discontinuation processes were significantly linked in the medium-sized city center, whereas they were not linked in the Parisian center. The center influenced risk of treatment discontinuation but not chance of success. The well-known inverse-J relation between the woman's age and chance of success was observed, as expected. Risk of discontinuation globally increased as the woman's age increased.

CONCLUSIONS

The link between success and discontinuation processes could depend on the fertility center. In particular, the woman's decision to pursue or to discontinue IVF in a particular center could depend on the presence of other IVF centers in the surrounding area.

Simple adaptations to the Templeton model for IVF outcome prediction make it current and clinically useful

STUDY QUESTION

What is the validity of the Templeton model (TM) in predicting live birth (LB) for a couple starting an IVF/ICSI cycle?

SUMMARY ANSWER

A centre-specific model based on the original predictors of the TM may reach a sufficient level of accuracy to be used in every day practice, with a few simple adaptations.

WHAT IS KNOWN AND WHAT THIS PAPER ADDS

The TM seems the best predictive model of LB in IVF. However, previous validations of the TM suggest a lack of discrimination and calibration which means that it is not used in regular practice. We confirm this finding, and argue that such results are predictable, and essentially due to a strong centre effect. We provide evidence that the TM constitutes a useful reference reflecting a high proportion of the patient-mix effect since the parameters of the model remain invariant among centres, but also across various cultures, countries and types of hospitals. The only difference was the intercept value, interpreted as the measurement of the global performance of one centre, in particular, for a population of reference.

STUDY DESIGN

The validity of the TM was tested by a retrospective analysis all IVF/ICSI cycles (n = 12 901) in our centre since 2000.

PARTICIPANTS, SETTING AND METHODS

All IVF/ICSI cycles were included in the analysis. The model discrimination was evaluated by C-statistics, calculated as the area under the curve of an ROC curve. The TM was then adjusted for our data and additional variables were assessed.

MAIN RESULTS AND THE ROLE OF CHANCE

Poor calibration and discrimination (C = 0.64) was observed in conformity with previous external validations. Fitting the TM to our centre constituted the first substantial improvement in prediction accuracy of discrimination (C = 0.69) and calibration. We identified an important linear time trend effect and the added value of three other predictors (FSH, smoking habits and BMI) that significantly improved the model (C = 0.71).

BIAS, CONFOUNDING AND OTHER REASONS FOR CAUTION

Bias due to missing data handling was assessed through sensitivity analyses.

GENERALIZABILITY TO OTHER POPULATIONS

Neither the TM nor any other models based on some centres are directly applicable to other centres. However, the TM constitutes a useful basis to build an accurate centre-specific model.

STUDY FUNDING/COMPETING INTEREST(S)

There were no commercial relationships (i.e. consultancies, patent-licensing agreements) that might pose a conflict of interest in connection with the submitted manuscript. The objective of this research was not directed toward any treatment effects.

Comparison of IVF cycles reported in a voluntary ART registry with a mandatory registry in Spain

BACKGROUND

Monitoring assisted reproductive technology (ART) is essential to evaluate the performance of fertility treatment and its impact on birth rates. In Europe, there are two kinds of ART registers: voluntary and mandatory. The validity of register data is very important with respect to the quality of register-based observational studies. The aim of this paper is to determine the degree of agreement between voluntary and mandatory ART registers.

METHODS

The two sources for the data compared in this study (referring to 2005 and 2006) were FIVCAT.NET (an official compulsory Assisted Reproduction Registry within the Health Ministry of the Regional Government of Catalonia, to which all authorized clinics, both public and private, performing assisted reproduction in the region are obliged to report) and the register of the Spanish Fertility Society (SEF), to which data are provided on a voluntary basis. The SEF register data were divided into two groups: (i) data from clinics in Catalonia (SEF-CAT); (ii) data from the rest of Spain, excluding Catalonia (SEF-wCAT). The techniques compared were IVF cycle using patients' own eggs (IVF cycle) versus donor egg cycles.

RESULTS

For IVF cycles, the voluntary ART register reflected 77.2% of those on the official one, but the corresponding figure was only 34.4% with respect to donated eggs. The variables analysed in the IVF cycle (insemination technique used, patients' age, number of embryos transferred, pregnancy rates, multiple pregnancies and deliveries) were similar in the three groups studied. However, we observed significant differences in donor egg cycles with regard to the insemination technique used, pregnancy rates and multiple pregnancies between the voluntary and the official register.

CONCLUSIONS

Data from the voluntary ART register for IVF cycles are valid, but those for donor egg cycles are not. Further study is necessary to determine the reasons for this difference.