ArticleFrontiers in endocrinology2026
The development of nomograms to predict multiple pregnancy and multiple birth in frozen- thawed embryo transfer cycles: a retrospective study.
Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: This study aimed to identify key factors influencing multiple pregnancy (MP) and multiple birth (MB) rates in frozen- thawed embryo transfer (FET) cycles, and to develop and validate clinically practical prediction nomograms for MP, MB, clinical pregnancy (CP), and live birth (LB). Methods: A total of 8,687 FET cycles performed between January 2014 and January 2024 were retrospectively analyzed. Cycles were randomly divided into a training set (n=6,081) and a validation set (n=2,606). Lasso regression was applied to screen independent predictive factors for MP, MB, CP, and LB. Nomogram models were constructed, and their performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, decision curve analysis (DCA), and internal validation with bootstrapping and random splitting. Results: Seven predictors were identified for MP and MB: female age, male age, endometrial thickness on the transformation day, number of transferred embryos, number of transferred high- quality embryos, number of transferred blastocysts, and total number of remaining embryos (including cleavage-stage and blastocyst embryos of all quality grades) after transfer. For CP, predictors included female age, AMH, endometrial thickness on the transformation day, number of transferred embryos, number of transferred high-quality embryos, number of transferred blastocysts, and remaining embryos; LB predictors further included male age. The AUCs of the MP nomogram were 0.798 (training) and 0.804 (validation); those of the MB nomogram were 0.800 and 0.809, respectively. Calibration curves were close to the ideal diagonal, and DCA confirmed clinical net benefit within threshold probabilities of 1%-48% for MP and 1%-60% for MB. The CP and LB models showed moderate discriminative ability with AUCs around 0.69. Conclusion: We developed and internally validated four nomograms incorporating routine clinical and embryological indicators to estimate individual risks of MP, MB, CP and LB before FET. These tools enable personalized pre-transfer risk assessment and can serve as auxiliary references for clinicians' patient counselling. External multicenter validation and prospective trials are required to confirm their clinical value before broad routine application.
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