Objective: In this study, we aimed to develop and internally validate a clinically applicable nomogram for predicting live birth following in vitro fertilization (IVF) using routinely available clinical and embryological parameters. Methods: This retrospective study was conducted at a single tertiary IVF center. Women undergoing IVF/ICSI were included if their baseline demographic and clinical data were available, they had undergone at least one fresh or frozen–thawed embryo transfer, and they had a known live birth outcome. Women with cycles without embryo transfer and those missing key outcome data were excluded from the analysis. As a result, a total of 2119 IVF/ICSI treatment cycles resulting in embryo transfer were included in the analysis. To identify independent predictors of live birth, multivariable logistic regression analysis was performed. Results: Among the 2119 treatment cycles analyzed, 541 resulted in live birth (25.5%). Multivariable logistic regression with backward stepwise selection identified female age (OR: 0.959, p < 0.001), high embryo quality (OR: 2.752, p < 0.001), day of embryo transfer (day 5 vs. day 3, OR: 1.427, p = 0.001), and endometrial thickness on the day of transfer as independent predictors of live birth (OR: 1.086, p < 0.001). These variables were incorporated into a nomogram (the Zübeyde Hanim IVF Nomogram) to estimate individualized live birth probability. The model demonstrated acceptable discrimination, with a bootstrap-corrected area under the receiver operating characteristic curve (AUC) of 0.64 (95%CI: 0.61–0.66), and it showed satisfactory calibration across deciles of predicted risk. Conclusions: The Zubeyde Hanim IVF Nomogram provides an individualized and clinically practical tool for predicting live birth following IVF treatment. Based on routinely available parameters, this model may assist clinicians in patient counseling and treatment planning.
Karaçin et al. (2026) studied this question.