The Development of Nomograms to Predict Blastulation Rate Following Cycles of In Vitro Fertilization in Patients With Tubal Factor Infertility, Polycystic Ovary Syndrome, or Endometriosis

Abstract

It is well known that the transfer of embryos at the blastocyst stage is superior to the transfer of embryos at the cleavage stage in many respects. However, the rate of blastocyst formation remains low in clinical practice. To reduce the possibility of wasting embryos and to accurately predict the possibility of blastocyst formation, we constructed a nomogram based on range of clinical characteristics to predict blastocyst formation rates in patients with different types of infertility. We divided patients into three groups based on female etiology: a tubal factor group, a polycystic ovary syndrome group, and an endometriosis group. Multiple logistic regression was used to analyze the relationship between patient characteristics and blastocyst formation. Each group of patients was divided into a training set and a validation set. The training set was used to construct the nomogram, while the validation set was used to test the performance of the model by using discrimination and calibration. The area under the curve (AUC) for the three groups indicated that the models performed fairly and that calibration was acceptable in each model.

Development of nomogram to predict the probability of blastocyst formation on day 5: a retrospective study

“…outcomes(Hariton et al, 2017). It was shown that high-quality Day 3 embryos have more potential to develop into blastocysts(Yin et al, 2014), in the present study high-quality rate of Day 3 embryos extended culture to blastocyst stage corresponded to a high point; these results were similar to the previously predicted models(Dessolle et al, 2009;Jin et al, 2021).…”

“…Dessolle et al, 2009;Jin et al, 2021). The causation of the number of Day 3 embryos extended culture to blastocyst stage rather than the number of oocytes retrieved entered in the model, may be attributed to the fact that not all Day 3 embryos cohort were cultured to blastocyst stage and usually the best one or two embryos were transferred or vitri ed in the present study.The fertilization rate, cleavage rate, high-quality rate of Day 3 embryos extended culture to blastocyst stage were residual predictors of usable blastocyst formation on Day 5.…”

“…the present study, we developed a model for predicting the individual probability of usable blastocyst formation on Day 5 based on training cohorts and then the model was validated by validation cohort. The model indicated that female age, type of fertilization, fertilization rate, cleavage rate, number of Day 3 embryos extended culture to blastocyst stage, and high-quality rate of Day 3 embryos extended culture to blastocyst stage were predictors of usable blastocysts formation on Day 5.Two previously study have developed models to predict blastocyst formation on Day 5(Dessolle et al, 2009;Jin et al, 2021), however our prediction model has some advantages compared to the two studies. First, the discrimination of our predict model was better than these previously predicted models.…”

“…A previous study has developed a nomogram for predicting the cancellation of blastocyst transfer based on training cohort of 562 cycles; however, the calibration curve of validation cohort showed poor performance (P < 0.01) (Dessolle et al, 2009). A recent study established three nomograms for predicting blastocyst formation rates according to different types of female infertility; however, these models are only suitable for IVF cycles (Jin et al, 2021).…”

Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births

“…The discrimination calibration abilities of this model were evaluated by calculating receiver operating characteristic curves (ROC), area under the ROC curve (AUC), Harrell’s concordance index (C-index), and the calibration plots in the training and validation groups ( 14 ). The value of the C-index and AUC ranges from 0 to 1, with 0.5-0.7 indicating poor performance of this model, 0.7-0.8 demonstrating fair performance, and 0.8-0.9 suggesting good performance ( 22 ). R software (version 4.0.5) was used to construct the nomogram model and analyze the ROC, AUC, C-index, and calibration curve.…”