Predicting failed trial of labor in advanced-age primiparas: development and validation of a clinical nomogram

With rising rates of delayed childbearing in China, clinical decision-making for advanced-age primiparas (≥ 35 years) is challenging, often leading to unnecessary cesarean sections or failed labor trials. This study aimed to develop and validate a model to predict labor failure risk in term, singleton, cephalic-presenting advanced-age primiparas. A retrospective cohort of 1344 women from Peking University First Hospital (October 2019–September 2022) was used for model development. Predictors were selected using least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable logistic regression to construct the final model. Model performance was assessed by area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis. Internal validation was performed with 1000‑sample bootstrapping, and external validation was conducted on an independent cohort of 601 women from the Daxing Branch (May 2024–April 2025). The trial of labor success rates were 67.4% and 71.0% in the development and validation cohorts, respectively. Eleven predictors were identified: increased gestational weight gain, higher pre-pregnancy BMI, advanced gestational age, estimated fetal weight ≥ 4.0 kg, maternal anemia, abnormal amniotic fluid volume, premature rupture of membranes, hypertensive disorders, and labor induction were risk factors; greater maternal height and epidural analgesia were protective. The model showed good discrimination with an AUC of 0.751 in the development cohort, remained stable at 0.741 after internal validation, and achieved 0.759 in external validation, indicating strong generalizability. Calibration plots demonstrated good agreement between predicted and observed outcomes, and decision curve analysis confirmed clinical utility. This validated prediction model effectively identifies high-risk advanced-age primiparas, aiding delivery mode counseling and personalized care. Prioritizing gestational weight control, anemia correction, and epidural analgesia could improve vaginal birth rates and optimize outcomes.