Development and validation of a predictive model for early blastocyst formation on day 4 post-fertilization

Objective: To develop and validate a predictive model for early blastocyst formation on Day 4 post-fertilization using clinically accessible parameters. Methods: This retrospective cohort of 2,557 patients scheduled for fresh Day 4 embryo transfer was randomly divided into training (n=1,789) and validation (n=768) sets at Xingtai MeiHe Reproductive and Genetic Hospital from January 2021 to December 2025. Early blastocyst formation occurred in 44.9% (training) and 44.1% (validation) of cases. Multivariable logistic regression and nomogram modeling were employed, with model performance assessed via AUC, calibration curves, and decision curve analysis. Results: After multivariable adjustment, the number of Day 3 embryos with >10 blastomeres (aOR=1.668, 95% CI: 1.374~2.025, P<0.001) and those with iDAScore >4.8 (aOR=1.369, 95% CI: 1.190 ~ 1.575, P<0.001) were the only independent predictors of Day 4 early blastocyst formation, while 15 covariates including ovarian reserve markers and sperm parameters showed no significant association (P>0.05). The nomogram integrating Day 3 embryos with >10 blastomeres and iDAScore>4.8 demonstrated robust discrimination (training AUC = 0.782, 95% CI: 0.738 ~ 0.826; validation AUC = 0.773, 95% CI: 0.705 ~ 0.841) with sensitivity of 65.4~65.9% and specificity of 79.6 ~ 81.7%. Calibration curves indicated minimal prediction deviation, and decision curve analysis confirmed clinical net benefits across 18~80% threshold probabilities in the training cohort and 20~93% in the validation cohort. Clinically, early blastocyst formation was associated with superior embryo quality parameters (P<0.001), higher single embryo transfer rates (50.90% vs. 13.96%, P<0.001), and increased clinical (67.65% vs. 59.32%, P<0.001) and ongoing pregnancy rates (59.59% vs. 52.89%, P = 0.006), alongside a lower multiple pregnancy rate (22.50% vs. 31.93%, P<0.001). Multivariable regression confirmed early blastocyst formation as an independent predictor of pregnancy success (clinical pregnancy aOR=1.675, 95% CI: 1.287 ~ 2.180, P<0.001; ongoing pregnancy aOR=1.612, 95% CI: 1.249 ~ 2.080, P<0.001). Conclusion: The validated nomogram accurately predicts Day 4 early blastocyst formation using Day 3 embryo parameters. The presence of early blastocyst formation on Day 4 might indicate suitability for selective Day 4 embryo transfer.

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Journal
Frontiers in Endocrinology
Published
2026-04-01
DOI
https://doi.org/10.3389/fendo.2026.1752963
Primary Topic
Reproductive Biology and Fertility
Type
article
Field-Weighted Citation Impact
0.00

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article

Development and validation of a predictive model for early blastocyst formation on day 4 post-fertilization

Yasong Geng, Linlin Tao, Haoyang Dai, Jing Ma et al.
Frontiers in Endocrinology
Reproductive Biology and Fertility
article

Development and validation of a predictive model for early blastocyst formation on day 4 post-fertilization

Yasong Geng, Linlin Tao, Haoyang Dai, Jing Ma, Jiayi Yin, Fangfang Dai, Bo Zheng
article en

Abstract

Objective: To develop and validate a predictive model for early blastocyst formation on Day 4 post-fertilization using clinically accessible parameters. Methods: This retrospective cohort of 2,557 patients scheduled for fresh Day 4 embryo transfer was randomly divided into training (n=1,789) and validation (n=768) sets at Xingtai MeiHe Reproductive and Genetic Hospital from January 2021 to December 2025. Early blastocyst formation occurred in 44.9% (training) and 44.1% (validation) of cases. Multivariable logistic regression and nomogram modeling were employed, with model performance assessed via AUC, calibration curves, and decision curve analysis. Results: After multivariable adjustment, the number of Day 3 embryos with >10 blastomeres (aOR=1.668, 95% CI: 1.374~2.025, P<0.001) and those with iDAScore >4.8 (aOR=1.369, 95% CI: 1.190 ~ 1.575, P<0.001) were the only independent predictors of Day 4 early blastocyst formation, while 15 covariates including ovarian reserve markers and sperm parameters showed no significant association (P>0.05). The nomogram integrating Day 3 embryos with >10 blastomeres and iDAScore>4.8 demonstrated robust discrimination (training AUC = 0.782, 95% CI: 0.738 ~ 0.826; validation AUC = 0.773, 95% CI: 0.705 ~ 0.841) with sensitivity of 65.4~65.9% and specificity of 79.6 ~ 81.7%. Calibration curves indicated minimal prediction deviation, and decision curve analysis confirmed clinical net benefits across 18~80% threshold probabilities in the training cohort and 20~93% in the validation cohort. Clinically, early blastocyst formation was associated with superior embryo quality parameters (P<0.001), higher single embryo transfer rates (50.90% vs. 13.96%, P<0.001), and increased clinical (67.65% vs. 59.32%, P<0.001) and ongoing pregnancy rates (59.59% vs. 52.89%, P = 0.006), alongside a lower multiple pregnancy rate (22.50% vs. 31.93%, P<0.001). Multivariable regression confirmed early blastocyst formation as an independent predictor of pregnancy success (clinical pregnancy aOR=1.675, 95% CI: 1.287 ~ 2.180, P<0.001; ongoing pregnancy aOR=1.612, 95% CI: 1.249 ~ 2.080, P<0.001). Conclusion: The validated nomogram accurately predicts Day 4 early blastocyst formation using Day 3 embryo parameters. The presence of early blastocyst formation on Day 4 might indicate suitability for selective Day 4 embryo transfer.

Frontiers in EndocrinologyVol. 17
Hebei Medical University (CN), Xingtai People's Hospital (CN), Hebei Academy of Sciences (CN), Hebei Mental Health Center (CN)
Health Commission of Hebei Province
Gender equality
Openalex Percentile: Top 31%
Reproductive Biology and Fertility
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