Economic evaluation of endometrial scratching before the second IVF/ICSI treatment: a cost-effectiveness analysis of a randomized controlled trial (SCRaTCH trial).

STUDY QUESTION: Is a single endometrial scratch prior to the second fresh IVF/ICSI treatment cost-effective compared to no scratch, when evaluated over a 12-month follow-up period? SUMMARY ANSWER: The incremental cost-effectiveness ratio (ICER) for an endometrial scratch was €6524 per additional live birth, but due to uncertainty regarding the increase in live birth rate this has to be interpreted with caution. WHAT IS KNOWN ALREADY: Endometrial scratching is thought to improve the chances of success in couples with previously failed embryo implantation in IVF/ICSI treatment. It has been widely implemented in daily practice, despite the lack of conclusive evidence of its effectiveness and without investigating whether scratching allows for a cost-effective method to reduce the number of IVF/ICSI cycles needed to achieve a live birth. STUDY DESIGN, SIZE, DURATION: This economic evaluation is based on a multicentre randomized controlled trial carried out in the Netherlands (SCRaTCH trial) that compared a single scratch prior to the second IVF/ICSI treatment with no scratch in couples with a failed full first IVF/ICSI cycle. Follow-up was 12 months after randomization.Economic evaluation was performed from a healthcare and societal perspective by taking both direct medical costs and lost productivity costs into account. It was performed for the primary outcome of biochemical pregnancy leading to live birth after 12 months of follow-up as well as the secondary outcome of live birth after the second fresh IVF/ICSI treatment (i.e. the first after randomization). To allow for worldwide interpretation of the data, cost level scenario analysis and sensitivity analysis was performed. PARTICIPANTS/MATERIALS, SETTING, METHODS: From January 2016 until July 2018, 933 women with a failed first IVF/ICSI cycle were included in the trial. Data on treatment and pregnancy were recorded up until 12 months after randomization, and the resulting live birth outcomes (even if after 12 months) were also recorded.Total costs were calculated for the second fresh IVF/ICSI treatment and for the full 12 month period for each participant. We included costs of all treatments, medication, complications and lost productivity costs. Cost-effectiveness analysis was carried out by calculating ICERs for scratch compared to control. Bootstrap resampling was used to estimate the uncertainty around cost and effect differences and ICERs. In the sensitivity and scenario analyses, various unit costs for a single scratch were introduced, amongst them, unit costs as they apply for the United Kingdom (UK). MAIN RESULTS AND THE ROLE OF CHANCE: More live births occurred in the scratch group, but this also came with increased costs over a 12-month period. The estimated chance of a live birth after 12 months of follow-up was 44.1% in the scratch group compared to 39.3% in the control group (risk difference 4.8%, 95% CI -1.6% to +11.2%). The mean costs were on average €283 (95% CI: -€299 to €810) higher in the scratch group so that the point average ICER was €5846 per additional live birth. The ICER estimate was surrounded with a high level of uncertainty, as indicated by the fact that the cost-effectiveness acceptability curve (CEAC) showed that there is an 80% chance that endometrial scratching is cost-effective if society is willing to pay ∼€17 500 for each additional live birth. LIMITATIONS, REASONS FOR CAUTION: There was a high uncertainty surrounding the effects, mainly in the clinical effect, i.e. the difference in the chance of live birth, which meant that a single straightforward conclusion could not be ascertained as for now. WIDER IMPLICATIONS OF THE FINDINGS: This is the first formal cost-effectiveness analysis of endometrial scratching in women undergoing IVF/ICSI treatment. The results presented in this manuscript cannot provide a clear-cut expenditure for one additional birth, but they do allow for estimating costs per additional live birth in different scenarios once the clinical effectiveness of scratching is known. As the SCRaTCH trial was the only trial with a follow-up of 12 months, it allows for the most complete estimation of costs to date. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by ZonMW, the Dutch organization for funding healthcare research. A.E.P.C., F.J.M.B., E.R.G. and C.B. L. reported having received fees or grants during, but outside of, this trial. TRIAL REGISTRATION NUMBER: Netherlands Trial Register (NL5193/NTR 5342).

Corrigendum: Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study.

[This corrects the article DOI: 10.3389/fpubh.2021.694306.].

Predicting Colorectal Cancer Recurrence and Patient Survival Using Supervised Machine Learning Approach: A South African Population-Based Study.

Background: South Africa (SA) has the highest incidence of colorectal cancer (CRC) in Sub-Saharan Africa (SSA). However, there is limited research on CRC recurrence and survival in SA. CRC recurrence and overall survival are highly variable across studies. Accurate prediction of patients at risk can enhance clinical expectations and decisions within the South African CRC patients population. We explored the feasibility of integrating statistical and machine learning (ML) algorithms to achieve higher predictive performance and interpretability in findings. Methods: We selected and compared six algorithms:- logistic regression (LR), naïve Bayes (NB), C5.0, random forest (RF), support vector machine (SVM) and artificial neural network (ANN). Commonly selected features based on OneR and information gain, within 10-fold cross-validation, were used for model development. The validity and stability of the predictive models were further assessed using simulated datasets. Results: The six algorithms achieved high discriminative accuracies (AUC-ROC). ANN achieved the highest AUC-ROC for recurrence (87.0%) and survival (82.0%), and other models showed comparable performance with ANN. We observed no statistical difference in the performance of the models. Features including radiological stage and patient's age, histology, and race are risk factors of CRC recurrence and patient survival, respectively. Conclusions: Based on other studies and what is known in the field, we have affirmed important predictive factors for recurrence and survival using rigorous procedures. Outcomes of this study can be generalised to CRC patient population elsewhere in SA and other SSA countries with similar patient profiles.

Using Machine Learning Methods Incorporating Individual Reader Annotations to Classify Paediatric Chest Radiographs in Epidemiological Studies.

Introduction: Epidemiological studies that involve interpretation of chest radiographs (CXRs) suffer from inter-reader and intra-reader variability. Inter-reader and intra-reader variability hinder comparison of results from different studies or centres, which negatively affects efforts to track the burden of chest diseases or evaluate the efficacy of interventions such as vaccines. This study explores machine learning models that could standardize interpretation of CXR across studies and the utility of incorporating individual reader annotations when training models using CXR data sets annotated by multiple readers. Methods: Convolutional neural networks were used to classify CXRs from seven low to middle-income countries into five categories according to the World Health Organization's standardized methodology for interpreting paediatric CXRs. We compared models trained to predict the final/aggregate classification with models trained to predict how each reader would classify an image and then aggregate predictions for all readers using unweighted mean. Results: Incorporating individual reader's annotations during model training improved classification accuracy by 3.4% (multi-class accuracy 61% vs 59%). Model accuracy was higher for children above 12 months of age (68% vs 58%). The accuracy of the models in different countries ranged between 45% and 71%. Conclusions: Machine learning models can annotate CXRs in epidemiological studies reducing inter-reader and intra-reader variability. In addition, incorporating individual reader annotations can improve the performance of machine learning models trained using CXRs annotated by multiple readers.

Using self-supervised feature learning to improve the use of pulse oximeter signals to predict paediatric hospitalization.

Background: The success of many machine learning applications depends on knowledge about the relationship between the input data and the task of interest (output), hindering the application of machine learning to novel tasks. End-to-end deep learning, which does not require intermediate feature engineering, has been recommended to overcome this challenge but end-to-end deep learning models require large labelled training data sets often unavailable in many medical applications. In this study, we trained self-supervised learning (SSL) models for automatic feature extraction from raw photoplethysmography (PPG) obtained using a pulse oximeter, with the aim of predicting paediatric hospitalization.  Methods: We compared logistic regression models fitted using features extracted using SSL with models trained using both clinical and SSL features. In addition, we compared end-to-end deep learning models initialized randomly or using weights from the SSL models. We also compared the performance of SSL models trained on labelled data alone (n=1,031) with SSL trained using both labelled and unlabelled signals (n=7,578). Results: Logistic regression models were more predictive of hospitalization when trained on features extracted using labelled PPG signals only compared to SSL models trained on both labelled and unlabelled signals (AUC 0.83 vs 0.80). However, features extracted using SSL model trained on both labelled and unlabelled PPG signals were more predictive of hospitalization when concatenated with clinical features (AUC 0.89 vs 0.87). The end-to-end deep learning model had an AUC of 0.80 when initialized using the SSL model trained on all PPG signals, 0.77 when initialized using SSL trained on labelled data only, and 0.73 when initialized randomly. Conclusions: This study shows that SSL can extract features from PPG signals that are predictive of hospitalization or initialize end-to-end deep learning models. Furthermore, SSL can leverage larger unlabelled data sets to improve performance of models fitted using small labelled data sets.

Endometrial scratching in women with one failed IVF/ICSI cycle-outcomes of a randomised controlled trial (SCRaTCH).

STUDY QUESTION: Does endometrial scratching in women with one failed IVF/ICSI treatment affect the chance of a live birth of the subsequent fresh IVF/ICSI cycle? SUMMARY ANSWER: In this study, 4.6% more live births were observed in the scratch group, with a likely certainty range between -0.7% and +9.9%. WHAT IS KNOWN ALREADY: Since the first suggestion that endometrial scratching might improve embryo implantation during IVF/ICSI, many clinical trials have been conducted. However, due to limitations in sample size and study quality, it remains unclear whether endometrial scratching improves IVF/ICSI outcomes. STUDY DESIGN, SIZE, DURATION: The SCRaTCH trial was a non-blinded randomised controlled trial in women with one unsuccessful IVF/ICSI cycle and assessed whether a single endometrial scratch using an endometrial biopsy catheter would lead to a higher live birth rate after the subsequent IVF/ICSI treatment compared to no scratch. The study took place in 8 academic and 24 general hospitals. Participants were randomised between January 2016 and July 2018 by a web-based randomisation programme. Secondary outcomes included cumulative 12-month ongoing pregnancy leading to live birth rate. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women with one previous failed IVF/ICSI treatment and planning a second fresh IVF/ICSI treatment were eligible. In total, 933 participants out of 1065 eligibles were included (participation rate 88%). MAIN RESULTS AND THE ROLE OF CHANCE: After the fresh transfer, 4.6% more live births were observed in the scratch compared to control group (110/465 versus 88/461, respectively, risk ratio (RR) 1.24 [95% CI 0.96-1.59]). These data are consistent with a true difference of between -0.7% and +9.9% (95% CI), indicating that while the largest proportion of the 95% CI is positive, scratching could have no or even a small negative effect. Biochemical pregnancy loss and miscarriage rate did not differ between the two groups: in the scratch group 27/153 biochemical pregnancy losses and 14/126 miscarriages occurred, while this was 19/130 and 17/111 for the control group (RR 1.21 (95% CI 0.71-2.07) and RR 0.73 (95% CI 0.38-1.40), respectively). After 12 months of follow-up, 5.1% more live births were observed in the scratch group (202/467 versus 178/466), of which the true difference most likely lies between -1.2% and +11.4% (95% CI). LIMITATIONS, REASONS FOR CAUTION: This study was not blinded. Knowledge of allocation may have been an incentive for participants allocated to the scratch group to continue treatment in situations where they may otherwise have cancelled or stopped. In addition, this study was powered to detect a difference in live birth rate of 9%. WIDER IMPLICATIONS OF THE FINDINGS: The results of this study are an incentive for further assessment of the efficacy and clinical implications of endometrial scratching. If a true effect exists, it may be smaller than previously anticipated or may be limited to specific groups of women undergoing IVF/ICSI. Studying this will require larger sample sizes, which will be provided by the ongoing international individual participant data-analysis (PROSPERO CRD42017079120). At present, endometrial scratching should not be performed outside of clinical trials. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by ZonMW, the Dutch organisation for funding healthcare research. J.S.E. Laven reports grants and personal fees from AnshLabs (Webster, Tx, USA), Ferring (Hoofddorp, The Netherlands) and Ministry of Health (CIBG, The Hague, The Netherlands) outside the submitted work. A.E.P. Cantineau reports 'other' from Ferring BV, personal fees from Up to date Hyperthecosis, 'other' from Theramex BV, outside the submitted work. E.R. Groenewoud reports grants from Titus Health Care during the conduct of the study. A.M. van Heusden reports personal fees from Merck Serono, personal fees from Ferring, personal fees from Goodlife, outside the submitted work. F.J.M. Broekmans reports personal fees as Member of the external advisory board for Ferring BV, The Netherlands, personal fees as Member of the external advisory board for Merck Serono, The Netherlands, personal fees as Member of the external advisory for Gedeon Richter, Belgium, personal fees from Educational activities for Ferring BV, The Netherlands, grants from Research support grant Merck Serono, grants from Research support grant Ferring, personal fees from Advisory and consultancy work Roche, outside the submitted work. C.B. Lambalk reports grants from Ferring, grants from Merck, grants from Guerbet, outside the submitted work. TRIAL REGISTRATION NUMBER: Registered in the Netherlands Trial Register (NL5193/NTR 5342). TRIAL REGISTRATION DATE: 31 July 2015. DATE OF FIRST PATIENT'S ENROLMENT: 26 January 2016.

Age-related natural fertility outcomes in women over 35 years: a systematic review and individual participant data meta-analysis.

STUDY QUESTION: What is the rate of natural conception leading to ongoing pregnancy or livebirth over 6-12 months for infertile women of age ≥35 years? SUMMARY ANSWER: Natural conception rates were still clinically relevant in women aged 35 years and above and were significantly higher in women with unexplained infertility compared to those with other diagnoses. WHAT IS KNOWN ALREADY: In recent years, increasing numbers of women have attempted to conceive at a later age, resulting in a commensurate increase in the need for ART. However, there is a lack of data on natural fertility outcomes (i.e. no interventions) in women with increasing age. STUDY DESIGN, SIZE, DURATION: A systematic review with individual participant data (IPD) meta-analysis was carried out. PubMed, MEDLINE, EMBASE, the Cochrane Library, clinicaltrials.gov were searched until 1 July 2018 including search terms 'fertility service', 'waiting list', 'treatment-independent' and 'spontaneous conception'. Language restrictions were not imposed. PARTICIPANTS/MATERIALS, SETTING, METHODS: Inclusion criteria were studies (at least partly) reporting on infertile couples with female partner of age ≥35 years who attended fertility services, underwent fertility workup (e.g. history, semen analysis, tubal status and ovulation status) and were exposed to natural conception (e.g. independent of treatment such as IVF, ovulation induction and tubal surgery). Studies that exclusively studied only one infertility diagnosis, without including other women presenting to infertility services for other causes of infertility, were excluded. For studies that met the inclusion criteria, study authors were contacted to provide IPD, after which fertility outcomes for women of age ≥35 years were retrieved. Time to pregnancy or livebirth and the effect of increasing age on fertility outcomes after adjustment for other prognostic factors were analysed. Quality of studies was graded with the Newcastle-Ottawa Scale (non-randomised controlled trials (RCTs)) or the Cochrane Risk of Bias tool (for RCTs). MAIN RESULTS AND THE ROLE OF CHANCE: We included nine studies (seven cohort studies and two RCTs) (n = 4379 women of at least age 35 years), with the observed composite primary outcome of ongoing pregnancy or livebirth occurring in 429 women (9.8%) over a median follow-up of 5 months (25th to 75th percentile: 2.5-8.5 months). Studies were of moderate to high quality. The probability of natural conception significantly decreased with any diagnosis of infertility, when compared with unexplained infertility. We found non-linear effects of female age and duration of infertility on ongoing pregnancy and tabulated the predicted probabilities for unexplained infertile women aged 35-42 years with either primary or secondary infertility and with a duration of infertility from 1 to 6 years. For a 35-year-old woman with 2 years of primary unexplained infertility, the predicted probability of natural conception leading to ongoing pregnancy or livebirth was 0.15 (95% CI 0.11-0.19) after 6 months and 0.24 (95% CI 0.17-0.30) after 12 months. For a 42-year-old woman, this decreased to 0.08 (95% CI 0.04-0.11) after 6 months and 0.13 (95% CI 0.07-0.18) after 12 months. LIMITATIONS, REASONS FOR CAUTION: In the studies selected, there were different study designs, recruitment strategies in different centres, protocols and countries and different methods of assessment of infertility. Data were limited for women above the age of 40 years. WIDER IMPLICATIONS OF THE FINDINGS: Women attending fertility services should be encouraged to pursue natural conception while waiting for treatment to commence and after treatment if it is unsuccessful. Our results may aid in counselling women, and, in particular, for those with unexplained infertility. STUDY FUNDING/COMPETING INTEREST(S): S.J.C. received funding from the University of Adelaide Summer Research Scholarship. B.W.M. is supported by a NHMRC Investigator grant (GNT1176437), B.W.M. reports consultancy for ObsEva, Merck, Merck KGaA, iGenomix and Guerbet. B.W.M. reports research support by Merck and Guerbet. PROSPERO REGISTRATION NUMBER: CRD42018096552.

Eliminating biasing signals in lung cancer images for prognosis predictions with deep learning.

Deep learning has shown remarkable results for image analysis and is expected to aid individual treatment decisions in health care. Treatment recommendations are predictions with an inherently causal interpretation. To use deep learning for these applications in the setting of observational data, deep learning methods must be made compatible with the required causal assumptions. We present a scenario with real-world medical images (CT-scans of lung cancer) and simulated outcome data. Through the data simulation scheme, the images contain two distinct factors of variation that are associated with survival, but represent a collider (tumor size) and a prognostic factor (tumor heterogeneity), respectively. When a deep network would use all the information available in the image to predict survival, it would condition on the collider and thereby introduce bias in the estimation of the treatment effect. We show that when this collider can be quantified, unbiased individual prognosis predictions are attainable with deep learning. This is achieved by (1) setting a dual task for the network to predict both the outcome and the collider and (2) enforcing a form of linear independence of the activation distributions of the last layer. Our method provides an example of combining deep learning and structural causal models to achieve unbiased individual prognosis predictions. Extensions of machine learning methods for applications to causal questions are required to attain the long-standing goal of personalized medicine supported by artificial intelligence.

What is the prognosis for a live birth after unexplained recurrent implantation failure following IVF/ICSI?

STUDY QUESTION: What is the cumulative incidence of live birth and mean time to pregnancy (by conception after IVF/ICSI or natural conception) in women experiencing unexplained recurrent implantation failure (RIF) following IVF/ICSI treatment? SUMMARY ANSWER: In 118 women who had experienced RIF, the reported cumulative incidence of live birth during a maximum of 5.5 years follow-up period was 49%, with a calculated median time to pregnancy leading to live birth of 9 months after diagnosis of RIF. WHAT IS KNOWN ALREADY: Current definitions of RIF include failure to achieve a pregnancy following IVF/ICSI and undergoing three or more fresh embryo transfer procedures of one or two high quality embryos or more than 10 embryos transferred in fresh or frozen cycles. The causes and optimal management of this distressing condition remain uncertain and a range of empirical and often expensive adjuvant therapies is often advocated. Little information is available regarding the long-term prognosis for achieving a pregnancy. STUDY DESIGN, SIZE, DURATION: Two hundred and twenty-three women under 39 years of age who had experienced RIF without a known cause after IVF/ICSI treatment in two tertiary referral university hospitals between January 2008 and December 2012 were invited to participate in this retrospective cohort follow up study. PARTICIPANTS/MATERIALS, SETTING, METHODS: All eligible women were sent a letter requesting their consent to the anonymous use of their medical file data and were asked to complete a questionnaire enquiring about treatments and pregnancies subsequent to experiencing RIF. Medical files and questionnaires were examined and results were analysed to determine the subsequent cumulative incidence of live birth and time to pregnancy within a maximum 5.5 year follow-up period using Kaplan Meier analysis. Clinical predictors for achieving a live birth were investigated using a Cox hazard model. MAIN RESULTS AND THE ROLE OF CHANCE: One hundred and twenty-seven women responded (57%) and data from 118 women (53%) were available for analysis. During the maximum 5.5 year follow up period the overall cumulative incidence of live birth was 49% (95% CI 39-59%). Among women who gave birth, the calculated median time to pregnancy was 9 months after experiencing RIF, where 18% arose from natural conceptions. LIMITATIONS, REASONS FOR CAUTION: Since only 57% of the eligible study cohort completed the questionnaire, the risk of response bias limits the applicability of the study findings. WIDER IMPLICATIONS OF THE FINDINGS: This study reports a favorable overall prognosis for achieving live birth in women who have previously experienced RIF, especially in those who continue with further IVF/ICSI treatments. However since 51% did not achieve a live birth during the follow-up period, there is a need to distinguish those most likely to benefit from further treatment. In this study, no clinical factors were found to be predictive of those achieving a subsequent live birth. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the University Medical Center Utrecht, in Utrecht and the Academic Medical Centre, in Amsterdam. NSM has received consultancy and speaking fees and research funding from Ferring, MSD, Merck Serono, Abbott, IBSA, Gedion Richter, and Clearblue. During the most recent 5-year period BCJMF has received fees or grant support from the following organizations (in alphabetic order); Actavis/Watson/Uteron, Controversies in Obstetrics & Gynecology (COGI), Dutch Heart Foundation, Dutch Medical Research Counsel (ZonMW), Euroscreen/Ogeda, Ferring, London Womens Clinic (LWC), Merck Serono, Myovant, Netherland Genomic Initiative (NGI), OvaScience, Pantharei Bioscience, PregLem/Gedeon Richter/Finox, Reproductive Biomedicine Online (RBMO), Roche, Teva, World Health Organisation (WHO).None of the authors have disclosures to make in relation to this manuscript.

Incorporating repeated measurements into prediction models in the critical care setting: a framework, systematic review and meta-analysis.

BACKGROUND: The incorporation of repeated measurements into multivariable prediction research may greatly enhance predictive performance. However, the methodological possibilities vary widely and a structured overview of the possible and utilized approaches lacks. Therefore, we [1] propose a structured framework for these approaches, [2] determine what methods are currently used to incorporate repeated measurements in prediction research in the critical care setting and, where possible, [3] assess the added discriminative value of incorporating repeated measurements. METHODS: The proposed framework consists of three domains: the observation window (static or dynamic), the processing of the raw data (raw data modelling, feature extraction and reduction) and the type of modelling. A systematic review was performed to identify studies which incorporate repeated measurements to predict (e.g. mortality) in the critical care setting. The within-study difference in c-statistics between models with versus without repeated measurements were obtained and pooled in a meta-analysis. RESULTS: From the 2618 studies found, 29 studies incorporated multiple repeated measurements. The annual number of studies with repeated measurements increased from 2.8/year (2000-2005) to 16.0/year (2016-2018). The majority of studies that incorporated repeated measurements for prediction research used a dynamic observation window, and extracted features directly from the data. Differences in c statistics ranged from - 0.048 to 0.217 in favour of models that utilize repeated measurements. CONCLUSIONS: Repeated measurements are increasingly common to predict events in the critical care domain, but their incorporation is lagging. A framework of possible approaches could aid researchers to optimize future prediction models.

Associations of preconception Body Mass Index in women with PCOS and BMI and blood pressure of their offspring.

Women with polycystic ovary syndrome (PCOS) have unfavorable metabolic profiles. Their offspring may be affected by such risks. The objective of the current study was to disclose associations between preconception health of these women and health of their offspring. 74 women diagnosed with PCOS according to the Rotterdam criteria were screened systematically before conception. Cardiovascular health of their offspring was assessed at 2.5-4 (n = 42) or at 6-8 years of age (n = 32). Multivariate linear regression analysis was performed with adjustments for potential confounders. In the primary analyses the association between preconception Body Mass index (BMI) and offspring BMI was evaluated. Secondly associations between preconception blood pressure, androgens, insulin-resistance (HOMA-IR), and LDL-cholesterol in women with PCOS and BMI and blood pressure of offspring were assessed. Results show that preconception BMI of women with PCOS was positively associated with sex- and age-adjusted BMI of their offspring at 6-8 years of age (ß = 0.55 (95% CI: 0.12 to 0.97), p = .012). No other significant associations were found. In conclusion, our data suggest that preconception BMI in PCOS is significantly associated with offspring BMI at 6-8 year of age. If this suggestion could be confirmed this may provide an opportunity for improving the future health of these children.

Does endometrial scratching increase the rate of spontaneous conception in couples with unexplained infertility and a good prognosis (Hunault > 30%)? Study protocol of the SCRaTCH-OFO trial: a randomized controlled trial.

BACKGROUND: In the Netherlands, couples with unexplained infertility and a good prognosis to conceive spontaneously (i.e. Hunault > 30%) are advised to perform timed intercourse for at least another 6 months. If couples fail to conceive within this period, they will usually start assisted reproductive technology (ART). However, treatment of unexplained infertility by ART is empirical and can involve significant burdens. Intentional endometrial injury, also called 'endometrial scratching', has been proposed to positively affect the chance of embryo implantation in patients undergoing in vitro fertilization (IVF). It might also be beneficial for couples with unexplained infertility as defective endometrial receptivity may play a role in these women. The primary aim of this study is to determine whether endometrial scratching increases live birth rates in women with unexplained infertility. METHOD: A multicentre randomized controlled trial will be conducted in Dutch academic and non-academic hospitals starting from November 2017. A total of 792 women with unexplained infertility and a good prognosis for spontaneous conception < 12 months (Hunault > 30%) will be included, of whom half will undergo endometrial scratching in the luteal phase of the natural cycle. The women in the control group will not undergo endometrial scratching. According to Dutch guidelines, both groups will subsequently perform timed intercourse for at least 6 months. The primary endpoint is cumulative live birth rate. Secondary endpoints are clinical and ongoing pregnancy rate; miscarriage rate; biochemical pregnancy loss; multiple pregnancy rate; time to pregnancy; progression to intrauterine insemination (IUI) or IVF; pregnancy complications; complications of endometrial scratching; costs and endometrial tissue parameters associated with reproductive success or failure. The follow-up duration is 12 months. DISCUSSION: Several small studies show a possible beneficial effect of endometrial scratching in women with unexplained infertility trying to conceive naturally or through IUI. However, the quality of this evidence is very low, making it unclear whether these women will truly benefit from this procedure. The SCRaTCH-OFO trial aims to investigate the effect of endometrial scratching on live birth rate in women with unexplained infertility and a good prognosis for spontaneous conception < 12 months. TRIAL REGISTRATION: NTR6687 , registered August 31st, 2017. PROTOCOL VERSION: Version 2.6, November 14th, 2018.

Predicting the cumulative chance of live birth over multiple complete cycles of in vitro fertilization: an external validation study.

STUDY QUESTION: Are the published pre-treatment and post-treatment McLernon models, predicting cumulative live birth rates (LBR) over multiple complete IVF cycles, valid in a different context? SUMMARY ANSWER: With minor recalibration of the pre-treatment model, both McLernon models accurately predict cumulative LBR in a different geographical context and a more recent time period. WHAT IS KNOWN ALREADY: Previous IVF prediction models have estimated the chance of a live birth after a single fresh embryo transfer, thereby excluding the important contribution of embryo cryopreservation and subsequent IVF cycles to cumulative LBR. In contrast, the recently developed McLernon models predict the cumulative chance of a live birth over multiple complete IVF cycles at two certain time points: (i) before initiating treatment using baseline characteristics (pre-treatment model) and (ii) after the first IVF cycle adding treatment related information to update predictions (post-treatment model). Before implementation of these models in clinical practice, their predictive performance needs to be validated in an independent cohort. STUDY DESIGN, SIZE, DURATION: External validation study in an independent prospective cohort of 1515 Dutch women who participated in the OPTIMIST study (NTR2657) and underwent their first IVF treatment between 2011 and 2014. Participants underwent a total of 2881 complete treatment cycles, with a complete cycle defined as all fresh and frozen thawed embryo transfers resulting from one episode of ovarian stimulation. The follow up duration was 18 months after inclusion, and the primary outcome was ongoing pregnancy leading to live birth. PARTICIPANTS/MATERIALS, SETTING, METHODS: Model performance was externally validated up to three complete treatment cycles, using the linear predictor as described by McLernon et al. to calculate the probability of a live birth. Discrimination was expressed by the c-statistic and calibration was depicted graphically in a calibration plot. In contrast to the original model development cohort, anti-Müllerian hormone (AMH), antral follicle count (AFC) and body weight were available in the OPTIMIST cohort, and evaluated as potential additional predictors for model improvement. MAIN RESULTS AND THE ROLE OF CHANCE: Applying the McLernon models to the OPTIMIST cohort, the c-statistic of the pre-treatment model was 0.62 (95% CI: 0.59-0.64) and of the post-treatment model 0.71 (95% CI: 0.69-0.74). The calibration plot of the pre-treatment model indicated a slight overestimation of the cumulative LBR. To improve calibration, the pre-treatment model was recalibrated by subtracting 0.35 from the intercept. The post-treatment model calibration plot revealed accurate cumulative LBR predictions. After addition of AMH, AFC and body weight to the McLernon models, the c-statistic of the updated pre-treatment model improved slightly to 0.66 (95% CI: 0.64-0.68), and of the updated post-treatment model remained at the previous level of 0.71 (95% CI: 0.69-0.73). Using the recalibrated pre-treatment model, a woman aged 30 years with 2 years of primary infertility who starts ICSI treatment for male factor infertility has a chance of 40% of a live birth from the first complete cycle, increasing to 72% over three complete cycles. If this woman weighs 70 kg, has an AMH of 1.5 ng/mL and an AFC of 10 measured at the beginning of her treatment, the updated pre-treatment model revises the estimated chance of a live birth to 30% in the first complete cycle and 59% over three complete cycles. If this woman then has five retrieved oocytes, no embryos cryopreserved and a single fresh cleavage stage embryo transfer in her first ICSI cycle, the post-treatment model estimates the chances of a live birth at 28 and 58%, respectively. LIMITATIONS, REASONS FOR CAUTION: Two randomized controlled trials (RCT) evaluating the effectiveness of gonadotropin dose individualization on basis of the AFC were nested within the OPTIMIST study. The strict dosing regimens, the RCT in- and exclusion criteria and the limited follow up time of 18 months might have influenced model performance in this independent cohort. Also, consistent with the original model development study, external validation was performed using the optimistic assumption that the cumulative LBR in couples who discontinue treatment without a live birth would have been equal to that of those who continue treatment. WIDER IMPLICATIONS OF THE FINDINGS: After national recalibration to account for geographical differences in IVF treatment, the McLernon prediction models can be introduced as new counselling tools in clinical practice to inform patients and to complement clinical reasoning. These models are the first to offer an objective and personalized estimate of the cumulative probability of a live birth over multiple complete IVF cycles. STUDY FUNDING/COMPETING INTEREST(S): No external funds were obtained for this study. M.J.C.E., D.J.M. and S.B. have nothing to disclose. J.A.L, S.C.O, T.C.v.T. and H.LT. received an unrestricted personal grant from Merck BV. B.W.M. is supported by a NHMRC Practitioner Fellowship (GNT1082548) and reports consultancy for ObsEva, Merck and Guerbet. F.J.M.B. receives monetary compensation as a member of the external advisory board for Merck BV (the Netherlands) and Ferring pharmaceutics BV (the Netherlands), for consultancy work for Gedeon Richter (Belgium) and Roche Diagnostics on automated AMH assay development, and for a research cooperation with Ansh Labs (USA). TRIAL REGISTRATION NUMBER: Not applicable.

Does AMH relate to timing of menopause? Results of an Individual Patient Data meta- analysis.

CONTEXT: Anti-Müllerian hormone based (AMH) age at menopause predictions remain cumbersome due to predictive inaccuracy. OBJECTIVE: To perform an Individual Patient Data (IPD) meta-analysis, regarding AMH based menopause prediction. DATA SOURCES: A systematic literature search was performed using PubMed, Embase and Cochrane databases. STUDY SELECTION: Prospective cohort studies regarding menopause prediction using serum AMH levels were selected by consensus discussion. DATA SELECTION: Individual cases were included if experiencing a regular cycle at baseline. Exclusion criteria were hormone use and gynecological surgery. DATA SYNTHESIS: 2596 women were included, 1077 experienced menopause. A multivariable Cox regression analysis assessed time to menopause (TTM) using age and AMH. AMH predicted TTM, however, added value on top of age was poor (age alone C-statistic 84%; age + AMH HR 0.66 95% CI 0.61-0.71, C-statistic 86%). Moreover, the capacity of AMH to predict early (≤45 years) and late menopause (≥55 years) was assessed. An added effect of AMH was demonstrated for early menopause (age alone C-statistic 52%; age + AMH HR 0.33, 95% CI 0.24-0.45, C-statistic 80%). A Weibull regression model calculating individual age at menopause revealed that predictive inaccuracy remained present and increased with decreasing age at menopause. Lastly, a check of non-proportionality of the predictive effect of AMH demonstrated a reduced predictive effect with increasing age. CONCLUSION: AMH was a significant predictor of TTM and especially of time to early menopause. However, individual predictions of age at menopause demonstrated a limited precision, particularly when concerning early age at menopause, making clinical application troublesome.

Natural conception rates in couples with unexplained or mild male subfertility scheduled for fertility treatment: a secondary analysis of a randomized controlled trial.

STUDY QUESTION: What is the natural conception rate over the course of 12 months in couples with unexplained or mild male subfertility who are scheduled for fertility treatment and have a predicted unfavourable prognosis for natural conception? SUMMARY ANSWER: The natural conception rate over the course of 12 months in couples who were allocated to treatment was estimated to be 24.5% (95% CI: 20-29%). WHAT IS KNOWN ALREADY: After starting treatment, couples often perceive unsuccessful cycles as evidence of definitive failure even though they are still able to conceive naturally in between and after treatment. The magnitude of the natural conception rate for couples who chose to commence treatment is unknown, as is whether the calculated prognosis before commencing treatment is still applicable. STUDY DESIGN, SIZE, DURATION: We performed a secondary analysis of a randomized controlled trial including couples with unexplained or mild male subfertility and an unfavourable prognosis for natural conception. Couples were allocated to either three cycles IVF with single embryo transfer (SET), six cycles of IVF in a modified natural cycle (MNC) or six cycles of IUI with controlled ovarian hyperstimulation (IUI-COH). The detailed data collection in this trial allowed us to study the conception rates in periods that couples were not receiving treatment. PARTICIPANTS/MATERIALS, SETTINGS, METHODS: We split the dataset into periods during which couples were treated and periods during which they were not treated. Couples could conceive naturally in the periods before, in between and after treatment cycles. The outcome was ongoing pregnancy, thus natural conception rate refers to natural conception leading to ongoing pregnancy. We performed a Cox proportional hazards analysis with female age, duration of subfertility and a time-varying covariate with four categories: IVF-SET, IVF-MNC, IUI-COH and no treatment. We used this Cox model to estimate the natural conception rate over 12 months of no treatment. MAIN RESULTS AND THE ROLE OF CHANCE: Out of 602 included couples, there were 342 ongoing pregnancies, of which 77 (23%) resulted from natural conception. The estimated natural conception rate over 12 months was 24.5% (95% CI: 20-29%) on cohort level. Estimated rates for female age varying between 18 and 38 years and duration of subfertility between 1 and 3 years ranged from 22 to 35%. LIMITATIONS, REASONS FOR CAUTION: We considered couples at risk for natural conception when not receiving treatment, whereas they might not have had periovulatory sexual intercourse. As couples were scheduled for treatment, it is possible that these couples were less inclined to try to conceive naturally, potentially leading to an underestimation of their natural conception rate if they kept trying to conceive. WIDER IMPLICATIONS OF THE FINDINGS: Couples with unexplained subfertility who are about to start fertility treatment, still have about a one in four chance of ongoing pregnancy due to natural conception over 12 months. This information can add to the counselling of couples who commenced fertility treatment after failed cycles and to emphasize not to cease their natural attempts. STUDY FUNDING/COMPETING INTEREST(S): The INeS trial was supported by a grant from ZonMW, the Dutch Organization for Health Research and Development (120620027), and a grant from Zorgverzekeraars Nederland, the Dutch association of health care insurers (09-003). The funders had no role in study design, collection, analysis and interpretation of the data. B.W.M. is supported by a NHMRC Practitioner Fellowship (GNT1082548). B.W.M. reports consultancy for ObsEva, Merck and Guerbet. No other potential conflicts of interest reported. TRIAL REGISTRATION NUMBER: The INeS trial was registered at the Dutch trial registry (NTR 939).

Endometrial scratching in women with implantation failure after a first IVF/ICSI cycle; does it lead to a higher live birth rate? The SCRaTCH study: a randomized controlled trial (NTR 5342).

BACKGROUND: Success rates of assisted reproductive techniques (ART) are approximately 30%, with the most important limiting factor being embryo implantation. Mechanical endometrial injury, also called 'scratching', has been proposed to positively affect the chance of implantation after embryo transfer, but the currently available evidence is not yet conclusive. The primary aim of this study is to determine the effect of endometrial scratching prior to a second fresh in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) cycle on live birth rates in women with a failed first IVF/ICSI cycle. METHOD: Multicenter randomized controlled trial in Dutch academic and non-academic hospitals. A total of 900 women will be included of whom half will undergo an endometrial scratch in the luteal phase of the cycle prior to controlled ovarian hyperstimulation using an endometrial biopsy catheter. The primary endpoint is the live birth rate after the 2nd fresh IVF/ICSI cycle. Secondary endpoints are costs, cumulative live birth rate (after the full 2nd IVF/ICSI cycle and over 12 months of follow-up); clinical and ongoing pregnancy rate; multiple pregnancy rate; miscarriage rate and endometrial tissue parameters associated with implantation failure. DISCUSSION: Multiple studies have been performed to investigate the effect of endometrial scratching on live birth rates in women undergoing IVF/ICSI cycles. Due to heterogeneity in both the method and population being scratched, it remains unclear which group of women will benefit from the procedure. The SCRaTCH trial proposed here aims to investigate the effect of endometrial scratching prior to controlled ovarian hyperstimulation in a large group of women undergoing a second IVF/ICSI cycle. TRIAL REGISTRATION: NTR 5342 , registered July 31st, 2015. PROTOCOL VERSION: Version 4.10, January 4th, 2017.

Anti-Müllerian hormone does not predict time to pregnancy: results of a prospective cohort study.

In order to study whether ovarian reserve tests (ORTs) can predict time to ongoing pregnancy, we conducted a prospective cohort study in a cohort of healthy pregnancy planners. A total of 102 pregnancy planners were followed for 1 year, or until ongoing pregnancy occurred, after cessation of contraceptives). A baseline measurement of anti-Müllerian hormone (AMH), follicle-stimulating hormone (FSH) and antral follicle count (AFC) was conducted. At the end of follow-up, a semen analysis was performed and chlamydia antibody titres were assessed. A univariate prediction model demonstrated age and the AFC to be significantly capable of predicting time to pregnancy (hazard ratio 0.92, 95% CI 0.87-0.98, p = 0.01; 1.04, 95% CI 1.01-1.07, p = 0.02 respectively). In the multivariate model, however, correcting for female age, we found no predictive effect of AMH, basal FSH or the AFC for time to ongoing pregnancy (hazard ratios 1.43, 95% CI 0.84-2.46, p = 0.36; 0.96, 95% CI 0.86-1.06, p = 0.43; 1.03, 95% CI 1.00-1.07, p = 0.08, respectively). This was confirmed by the low C-statistic. We therefore concluded that baseline AMH, AFC or FSH levels do not predict time to ongoing pregnancy in a cohort of healthy pregnancy planners. These results limit the usability of these ORTs in the assessment of current fertility.

IVF or IUI as first-line treatment in unexplained subfertility: the conundrum of treatment selection markers.

STUDY QUESTION: Are there treatment selection markers that could aid in identifying couples, with unexplained or mild male subfertility, who would have better chances of a healthy child with IVF with single embryo transfer (IVF-SET) than with IUI with ovarian stimulation (IUI-OS)? SUMMARY ANSWER: We did not find any treatment selection markers that were associated with better chances of a healthy child with IVF-SET instead of IUI-OS in couples with unexplained or mild male subfertility. WHAT IS KNOWN ALREADY: A recent trial, comparing IVF-SET to IUI-OS, found no evidence of a difference between live birth rates and multiple pregnancy rates. It was suggested that IUI-OS should remain the first-line treatment instead of IVF-SET in couples with unexplained or mild male subfertility and female age between 18 and 38 years. The question remains whether there are some couples that may have higher pregnancy chances if treated with IVF-SET instead of IUI. STUDY DESIGN, SIZE, DURATION: We performed our analyses on data from the INeS trial, where couples with unexplained or mild male subfertility and an unfavourable prognosis for natural conception were randomly allocated to IVF-SET, IVF in a modified natural cycle or IUI-OS. In view of the aim of this study, we only used data of the comparison between IVF-SET (201 couples) and IUI-OS (207 couples). PARTICIPANTS/MATERIALS, SETTING, METHODS: We pre-defined the following baseline characteristics as potential treatment selection markers: female age, ethnicity, smoking status, type of subfertility (primary/secondary), duration of subfertility, BMI, pre-wash total motile count and Hunault prediction score. For each potential treatment selection marker, we explored the association with the chances of a healthy child after IVF-SET and IUI-OS and tested if there was an interaction with treatment. Given the exploratory nature of our analysis, we used a P-value of 0.1. MAIN RESULTS AND THE ROLE OF CHANCE: None of the markers were associated with higher chances of a healthy child from IVF-SET compared to IUI-OS (P-value for interaction >0.10). LIMITATIONS, REASONS FOR CAUTION: Since this is the first large study that looked at potential treatment selection markers for IVF-SET compared to IUI-OS, we had no data on which to base a power calculation. The sample size was limited, making it difficult to detect any smaller associations. WIDER IMPLICATIONS OF THE FINDINGS: We could not identify couples with unexplained or mild male subfertility who would have had higher chances of a healthy child from immediate IVF-SET than from IUI-OS. As in the original trial IUI-OS had similar effectiveness and was less costly compared to IVF-SET, IUI-OS should remain the preferred first-line treatment in these couples. STUDY FUNDING/COMPETING INTEREST(S): The study was supported by a grant from the Netherlands Organization for Health Research and Development, and a grant from the Netherlands' association of health care insurers. There are no conflicts of interest. TRIAL REGISTRATION NUMBER: The trial was registered at the Dutch trial registry (NTR939).