Reproductive medicine and biology · 2026
Transfer Strategy Minimizing Twin Risk of Double Blastocyst Transfers Based on Prediction Models.
СтатьяНазвание и аннотация: Перевод в очереди
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Onishi Kazuma, Inoue Daichi, Kida Yuta, Kojima Masae, Fukunaga Noritaka, Asada Yoshimasa
Аннотация
PURPOSE: To develop a simulation model to guide single embryo transfer (SET) versus double embryo transfer (DET) decisions by minimizing twin risk per transfer while maintaining treatment efficiency.
METHODS: This retrospective observational study included individuals undergoing SET or DET with frozen blastocysts in hormone replacement therapy. Three generalized estimating equation-based models were developed: ongoing pregnancy after SET (Model 1) and DET (Model 2), and twin pregnancy after DET (Model 3). Model 1 was constructed using propensity score-matched SETs comparable to DETs. The simulation aimed to identify the optimal transfer sequence for patients with multiple blastocysts using a stepwise optimization that selects SET or DET at each transfer while maximizing pregnancy probability and constraining twin risk below predefined thresholds.
RESULTS: 5721 DET and 5719 matched SET cycles were included in the analysis. The ongoing pregnancy rate was 20.1% in matched SET and 25.1% in DET, while the ongoing twin pregnancy rate following DET was 5.5%. Area under the curve was 0.77, 0.73, and 0.82 for Model 1-3, respectively. Simulation demonstrated an optimal sequence combining SET/DET under the individualized twin risk in a variety of scenarios (https://sites.google.com/view/det-simulator/).
CONCLUSIONS: This model supports individualized embryo transfer planning by balancing treatment efficiency and twin risk.
METHODS: This retrospective observational study included individuals undergoing SET or DET with frozen blastocysts in hormone replacement therapy. Three generalized estimating equation-based models were developed: ongoing pregnancy after SET (Model 1) and DET (Model 2), and twin pregnancy after DET (Model 3). Model 1 was constructed using propensity score-matched SETs comparable to DETs. The simulation aimed to identify the optimal transfer sequence for patients with multiple blastocysts using a stepwise optimization that selects SET or DET at each transfer while maximizing pregnancy probability and constraining twin risk below predefined thresholds.
RESULTS: 5721 DET and 5719 matched SET cycles were included in the analysis. The ongoing pregnancy rate was 20.1% in matched SET and 25.1% in DET, while the ongoing twin pregnancy rate following DET was 5.5%. Area under the curve was 0.77, 0.73, and 0.82 for Model 1-3, respectively. Simulation demonstrated an optimal sequence combining SET/DET under the individualized twin risk in a variety of scenarios (https://sites.google.com/view/det-simulator/).
CONCLUSIONS: This model supports individualized embryo transfer planning by balancing treatment efficiency and twin risk.