Development of an IVF prediction model for donor oocytes: a retrospective analysis of 10 877 embryo transfers

• Published in: Human reproduction (Oxford) 2024-10, Vol.39 (10), p.2274-2286
• Main Authors: Fitzgerald, Oisin, Newman, Jade, Rombauts, Luk, Polyakov, Alex, Chambers, Georgina M
• Format: Article
• Language: English
• Subjects: Adult; Australia; Embryo Transfer - methods; Embryo Transfer - statistics & numerical data; Female; Fertilization in Vitro - methods; Humans; Live Birth; Middle Aged; New Zealand; Oocyte Donation; Pregnancy; Pregnancy Rate; Retrospective Studies
• ISSN: 0268-1161; 1460-2350; 1460-2350
• DOI: 10.1093/humrep/deae174

Abstract STUDY QUESTION Can we develop a prediction model for the chance of a live birth following the transfer of an embryo created using donated oocytes? SUMMARY ANSWER Three primary models that included patient, past treatment, and cycle characteristics were developed using Australian data to predict the chance of a live birth following the transfer of an embryo created using donated oocytes; these models were well-calibrated to the population studied, achieved reasonable predictive power and generalizability when tested on New Zealand data. WHAT IS KNOWN ALREADY Nearly 9% of ART embryo transfer cycles performed globally use embryos created using donated oocytes. This percentage rises to one-quarter and one-half in same-sex couples and women aged over 45 years, respectively. STUDY DESIGN, SIZE, DURATION This study uses population-based Australian clinical registry data comprising 9384 embryo transfer cycles that occurred between 2015 and 2021 for model development, with an external validation cohort of 1493 New Zealand embryo transfer cycles. PARTICIPANTS/MATERIALS, SETTING, METHODS Three prediction models were compared that incorporated patient characteristics, but differed in whether they considered use of prior autologous treatment factors and current treatment parameters. We internally validated the models on Australian data using grouped cross-validation and reported several measures of model discrimination and calibration. Variable importance was measured through calculating the change in predictive performance that resulted from variable permutation. The best-performing model was externally validated on data from New Zealand. MAIN RESULTS AND THE ROLE OF CHANCE The best-performing model had an internal validation AUC-ROC of 0.60 and Brier score of 0.20, and external validation AUC-ROC of 0.61 and Brier score of 0.23. While these results indicate ∼15% less discriminatory ability compared to models assessed on an autologous cohort from the same population the performance of the models was clearly statistically significantly better than random, demonstrated generalizability, and was well-calibrated to the population studied. The most important variables for predicting the chance of a live birth were the oocyte donor age, the number of prior oocyte recipient embryo transfer cycles, whether the transferred embryo was cleavage or blastocyst stage and oocyte recipient age. Of lesser importance were the oocyte-recipient parity, whether donor or partner s