ArticleHuman reproduction (Oxford, England)2023
External validation of models for predicting cumulative live birth over multiple complete cycles of IVF treatment.
Article in Human reproduction (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 25 citations in OpenAlex.
- Study of comparative performance of general-purpose LLM-based systems in predicting IVF outcomes.Journal of assisted reproduction and genetics · 2026Article
- Development and temporal validation of a prediction model for live birth in infertile women with polyendocrine metabolic ovarian syndrome: a retrospective cohort study.Frontiers in reproductive health · 2026Article
- Predictive model for live birth outcomes in single euploid frozen embryo transfers: a comparative analysis of logistic regression and machine learning approaches.Journal of assisted reproduction and genetics · 2025Article
- Machine learning center-specific models show improved IVF live birth predictions over US national registry-based model.Nature communications · 2025Article
- Potential ability of circulating INSL3 level for the prediction of ovarian reserve and IVF success as a novel theca cell-specific biomarker in women with unexplained infertility and diminished ovarian reserve.Reproductive biology and endocrinology : RB&E · 2025Article
- Development and externally validated prediction model of individualization of FSH starting dose in the depot GnRH agonist protocol for the early follicular phase.Frontiers in endocrinology · 2025Article
- Ovarian sensitivity index-based nomogram for predicting clinical pregnancy outcomes in patients with diminished ovarian reserve undergoingFrontiers in medicine · 2025Article
- Advanced KPI framework for IVF pregnancy prediction models in IVF protocols.Scientific reports · 2024Article
- Psychological aspects of infertility.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2024Article
- Improving IVF Utilization with Patient-Centric Artificial Intelligence-Machine Learning (AI/ML): A Retrospective Multicenter Experience.Journal of clinical medicine · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
study questionCan two prediction models developed using data from 1999 to 2009 accurately predict the cumulative probability of live birth per woman over multiple complete cycles of IVF in an updated UK cohort? SUMMARY ANSWER: After being updated, the models were able to estimate individualized chances of cumulative live birth over multiple complete cycles of IVF with greater accuracy. WHAT IS KNOWN ALREADY: The McLernon models were the first to predict cumulative live birth over multiple complete cycles of IVF. They were converted into an online calculator called OPIS (Outcome Prediction In Subfertility) which has 3000 users per month on average. A previous study externally validated the McLernon models using a Dutch prospective cohort containing data from 2011 to 2014. With changes in IVF practice over time, it is important that the McLernon models are externally validated on a more recent cohort of patients to ensure that predictions remain accurate. STUDY DESIGN, SIZE, DURATION: A population-based cohort of 91 035 women undergoing IVF in the UK between January 2010 and December 2016 was used for external validation. Data on frozen embryo transfers associated with these complete IVF cycles conducted from 1 January 2017 to 31 December 2017 were also collected. PARTICIPANTS/MATERIALS, SETTING,
methodsData on IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA). The predictive performances of the McLernon models were evaluated in terms of discrimination and calibration. Discrimination was assessed using the c-statistic and calibration was assessed using calibration-in-the-large, calibration slope, and calibration plots. Where any model demonstrated poor calibration in the validation cohort, the models were updated using intercept recalibration, logistic recalibration, or model revision to improve model performance. MAIN RESULTS AND THE ROLE OF CHANCE: Following exclusions, 91 035 women who underwent 144 734 complete cycles were included. The validation cohort had a similar distribution age profile to women in the development cohort. Live birth rates over all complete cycles of IVF per woman were higher in the validation cohort. After calibration assessment, both models required updating. The coefficients of the pre-treatment model were revised, and the updated model showed reasonable discrimination (c-statistic: 0.67, 95% CI: 0.66 to 0.68). After logistic recalibration, the post-treatment model showed good discrimination (c-statistic: 0.75, 95% CI: 0.74 to 0.76). As an example, in the updated pre-treatment model, a 32-year-old woman with 2 years of primary infertility has a 42% chance of having a live birth in the first complete ICSI cycle and a 77% chance over three complete cycles. In a couple with 2 years of primary male factor infertility where a 30-year-old woman has 15 oocytes collected in the first cycle, a single fresh blastocyst embryo transferred in the first cycle and spare embryos cryopreserved, the estimated chance of live birth provided by the post-treatment model is 46% in the first complete ICSI cycle and 81% over three complete cycles. LIMITATIONS, REASONS FOR CAUTION: Two predictors from the original models, duration of infertility and previous pregnancy, which were not available in the recent HFEA dataset, were imputed using data from the older cohort used to develop the models. The HFEA dataset does not contain some other potentially important predictors, e.g. BMI, ethnicity, race, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. WIDER IMPLICATIONS OF THE
findingsBoth updated models show improved predictive ability and provide estimates which are more reflective of current practice and patient case mix. The updated OPIS tool can be used by clinicians to help shape couples' expectations by informing them of their individualized chances of live birth over a sequence of multiple complete cycles of IVF. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. S.B. has a commitment of research funding from Merck. D.J.M. and M.B.R. declare support for the present manuscript from Elphinstone scholarship scheme at the University of Aberdeen and Assisted Reproduction Unit at Aberdeen Fertility Centre, University of Aberdeen. D.J.M. declares grants received by University of Aberdeen from NHS Grampian, The Meikle Foundation, and Chief Scientist Office in the past 3 years. D.J.M. declares receiving an honorarium for lectures from Merck. D.J.M. is Associate Editor of Human Reproduction Open and Statistical Advisor for Reproductive BioMed Online. S.B. declares royalties from Cambridge University Press for a book. S.B. declares receiving an honorarium for lectures from Merck, Organon, Ferring, Obstetric and Gynaecological Society of Singapore, and Taiwanese Society for Reproductive Medicine. S.B. has received support from Merck, ESHRE, and Ferring for attending meetings as speaker and is on the METAFOR and CAPRE Trials Data Monitoring Committee. TRIAL REGISTRATION NUMBER: N/A.
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