A visualized clinical model predicting good quality blastocyst development in the first IVF/ICSI cycle

Abstract Research Question Can we establish a visualized clinical model predicting good quality blastocyst (GQB) formation for patients in their first in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) cycle? Design A total of 4,783 patients in their first IVF/ICSI cycle between January 2015 and December 2019 were retrospectively included and randomly divided into the training set (n=3826) and the testing set (n=957) by 8:2. The least absolute shrinkage and selection operator (LASSO) regression was adopted to select the most critical predictors for GQB formation to construct a visualized nomogram model based on the data of patients in the training set. Receiver operating characteristic and calibration curves were used to evaluate the predictive accuracy and discriminative ability. The performance of the model was also validated on independent data from patients treated in the testing set. Results Maternal age, anti-Mullerian hormone level and the number of oocytes retrieved were highlighted as critical predictors of GQB development and were incorporated into the nomogram model. Based on the area under the curve (AUC) values, the predictive ability for ≥1, ≥3 and ≥5 GQBs were 0.831, 0.734 and 0.748, respectively. The calibration curve also showed high concordance between the observed and predicted results. The AUCs for predicting ≥1, ≥3 and ≥5 GQBs in the testing set were 0.805, 0.695 and 0.707, respectively, which were similar to those for the training set. Conclusions The visualized nomogram model provides great predictive value for GQB development in patients in their first IVF/ICSI cycle and can be used to improve clinical counseling.