Individualized versus standard FSH dosing in women starting IVF/ICSI:An RCT. Part 2: The predicted hyper responder

STUDY QUESTION: Does a reduced FSH dose in women with a predicted hyper response, apparent from a high antral follicle count (AFC), who are scheduled for IVF/ICSI lead to a different outcome with respect to cumulative live birth rate and safety? SUMMARY ANSWER: Although in women with a predicted hyper response (AFC > 15) undergoing IVF/ICSI a reduced FSH dose (100 IU per day) results in similar cumulative live birth rates and a lower occurrence of any grade of ovarian hyperstimulation syndrome (OHSS) as compared to a standard dose (150 IU/day), a higher first cycle cancellation rate and similar severe OHSS rate were observed. WHAT IS KNOWN ALREADY: Excessive ovarian response to controlled ovarian stimulation (COS) for IVF/ICSI may result in increased rates of cycle cancellation, the occurrence of OHSS and suboptimal live birth rates. In women scheduled for IVF/ICSI, an ovarian reserve test (ORT) can be used to predict response to COS. No consensus has been reached on whether ORT-based FSH dosing improves effectiveness and safety in women with a predicted hyper response. STUDY DESIGN SIZE, DURATION: Between May 2011 and May 2014, we performed an open-label, multicentre RCT in women with regular menstrual cycles and an AFC > 15. Women with polycystic ovary syndrome (Rotterdam criteria) were excluded. The primary outcome was ongoing pregnancy achieved within 18 months after randomization and resulting in a live birth. Secondary outcomes included the occurrence of OHSS and cost-effectiveness. Since this RCT was embedded in a cohort study assessing over 1500 women, we expected to randomize 300 predicted hyper responders. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women with an AFC > 15 were randomized to an FSH dose of 100 IU or 150 IU/day. In both groups, dose adjustment was allowed in subsequent cycles (maximum 25 IU in the reduced and 50 IU in the standard group) based on pre-specified criteria. Both effectiveness and cost-effectiveness were evaluated from an intention-to-treat perspective. MAIN RESULTS AND THE ROLE OF CHANCE: We randomized 255 women to a daily FSH dose of 100 IU and 266 women to a daily FSH dose of 150 IU. The cumulative live birth rate was 66.3% (169/255) in the reduced versus 69.5% (185/266) in the standard group (relative risk (RR) 0.95 [95%CI, 0.85-1.07], P = 0.423). The occurrence of any grade of OHSS was lower after a lower FSH dose (5.2% versus 11.8%, RR 0.44 [95%CI, 0.28-0.71], P = 0.001), but the occurrence of severe OHSS did not differ (1.3% versus 1.1%, RR 1.25 [95%CI, 0.38-4.07], P = 0.728). As dose reduction was not less expensive (€4.622 versus €4.714, delta costs/woman €92 [95%CI, -479-325]), there was no dominant strategy in the economic analysis. LIMITATIONS, REASONS FOR CAUTION: Despite our training programme, the AFC might have suffered from inter-observer variation. Although strict cancellation criteria were provided, selective cancelling in the reduced dose group (for poor response in particular) cannot be excluded as observers were not blinded for the FSH dose and small dose adjustments were allowed in subsequent cycles. However, as first cycle live birth rates did not differ from the cumulative results, the open design probably did not mask a potential benefit for the reduced dosing group. As this RCT was embedded in a larger cohort study, the power in this study was unavoidably lower than it should be. Participants had a relatively low BMI from an international perspective, which may limit generalization of the findings. WIDER IMPLICATIONS OF THE FINDINGS: In women with a predicted hyper response scheduled for IVF/ICSI, a reduced FSH dose does not affect live birth rates. A lower FSH dose did reduce the incidence of mild and moderate OHSS, but had no impact on severe OHSS. Future research into ORT-based dosing in women with a predicted hyper response should compare various safety management strategies and should be powered on a clinically relevant safety outcome while assessing non-inferiority towards live birth rates. STUDY FUNDING/COMPETING INTEREST(S): This trial was funded by The Netherlands Organization for Health Research and Development (ZonMW, Project Number 171102020). SCO, TCvT and HLT received an unrestricted research grant from Merck Serono (the Netherlands). CBL receives grants from Merck, Ferring and Guerbet. BWJM is supported by a NHMRC Practitioner Fellowship (GNT1082548) and reports consultancy for OvsEva, Merck and Guerbet. FJMB receives monetary compensation as a member of the external advisory board for Ferring pharmaceutics BV and Merck Serono for consultancy work for Gedeon Richter (Belgium) and Roche Diagnostics (Switzerland) and for a research cooperation with Ansh Labs (USA). All other authors have nothing to declare. TRIAL REGISTRATION NUMBER: Registered at the ICMJE-recognized Dutch Trial Registry (www.trialregister.nl). Registration number: NTR2657. TRIAL REGISTRATION DATE: 20 December 2010. DATE OF FIRST PATIENT’S ENROLMENT: 12 May 2011

Cumulative live birth rates in low-prognosis women

No external funds were obtained for the present study. The OPTIMIST study was funded by The Netherlands Organization for Health Research and Development (ZonMW number 171102020).Peer reviewedPublisher PD

PCOS: Backgrounds, evidence and problems in diagnosing the syndrome

PCOS constitutes a heterogeneous clinical picture harbouring different subsets of patients. Recently an attempt was made to define the diagnosis of PCOS based on existing clinical evidence. Oligo- or anovulation, clinical or biochemical hyperandrogenism and polycystic ovaries constitute the key clinical features on which the diagnosis should be based. No single diagnostic criterion is sufficient for clinical diagnosis. Based on this new consensus the spectrum of women with PCOS has been considerably broadened. The purpose of this paper is to review the evidence for this new classification and to address problems in diagnosing PCOS using these new criteria.</p

Using the embryo-uterus statistical model to predict pregnancy chances by using cleavage stage morphokinetics and female age: two centre-specific prediction models and mutual validation

BACKGROUND: The predictive capability of time-lapse monitoring (TLM) selection algorithms is influenced by patient characteristics, type and quality of data included in the analysis and the used statistical methods. Previous studies excluded DET cycles of which only one embryo implanted, introducing bias into the data. Therefore, we wanted to develop a TLM prediction model that is able to predict pregnancy chances after both single- and double embryo transfer (SET and DET). METHODS: This is a retrospective study of couples (n = 1770) undergoing an in vitro fertilization cycle at the Erasmus MC, University Medical Centre Rotterdam (clinic A) or the Reinier de Graaf Hospital (clinic B). This resulted in 2058 transferred embryos with time-lapse and pregnancy outcome information. For each dataset a prediction model was established by using the Embryo-Uterus statistical model with the number of gestational sacs as the outcome variable. This process was followed by cross-validation. RESULTS: Prediction model A (based on data of clinic A) included female age, t3-t2 and t5-t4, and model B (clinic B) included female age, t2, t3-t2 and t5-t4. Internal validation showed overfitting of model A (calibration slope 0.765 and area under the curve (AUC) 0.60), and minor overfitting of model B (slope 0.915 and AUC 0.65). External validation showed that model A was capable of predicting pregnancy in the dataset of clinic B with an AUC of 0.65 (95% CI: 0.61-0.69; slope 1.223, 95% CI: 0.903-1.561). Model B was less accurate in predicting pregnancy in the dataset of clinic A (AUC 0.60, 95% CI: 0.56-0.65; slope 0.671, 95% CI: 0.422-0.939). CONCLUSION: Our study demonstrates a novel approach to the development of a TLM prediction model by applying the EU statistical model. With further development and validation in clinical practice, our prediction model approach can aid in embryo selection and decision making for SET or DET