A Clinical Predictive Model of Progesterone Elevation on the Day of Human Chorionic Gonadotropin Administration Based on Basal Progesterone, Body Mass Index, and Ovarian Induction Regimen: A Retrospective Study

Background: Progesterone elevation (PE), defined as ≥0.9 ng/mL on the day of human chorionic gonadotropin (hCG) administration, is associated with significantly lower clinical pregnancy rates following fresh embryo transfer. To mitigate the risk of PE, this study aimed to develop and validate a nomogram for predict its occurrence prior to in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) cycles, based on baseline patient characteristics. Methods: This retrospective study analyzed data from patients who underwent controlled ovarian stimulation using either a gonadotropin-releasing hormone (GnRH) antagonist or agonist protocol at the Reproductive Center of Changzhou Maternal and Child Health Care Hospital between January 1, 2017, and December 31, 2019. Patients were excluded for reasons such as advanced maternal age, male factor infertility, or known chromosomal abnormalities. The cohort was randomly divided into a training set (n = 1882) and a validation set (n = 807) at a 7:3 ratio to develop and validate the nomogram, respectively. Results: Multivariate logistic regression analysis identified the ovulation induction protocol, basal progesterone level, and body mass index (BMI) as independent predictors of PE. The resulting nomogram demonstrated good calibration and discrimination, with an area under the curve (AUC) of 0.734 (95% confidence interval [CI]: 0.713–0.754) in the training cohort and 0.732 (95% CI: 0.700–0.763) in the validation cohort. Furthermore, decision curve analysis confirmed the model’s strong clinical utility. Conclusion: We developed a user-friendly nomogram incorporating the ovulation induction protocol, basal progesterone, and BMI to predict the risk of PE on the day of hCG administration. This tool provides clinicians a simple, evidence-based method to identify high-risk patients before starting their IVF/ICSI cycles, potentially enabling proactive interventions to improve pregnancy outcomes.