Unveiling risk factors and developing a predictive nomogram for ectopic pregnancy in polycystic ovary syndrome...

Although assisted reproductive technology (ART) may increase the incidence of ectopic pregnancy (EP), the risk of EP and its associated risk factors in polycystic ovary syndrome (PCOS) patients, one of the target populations for ART, remain poorly understood.

This retrospective study analyzed 377 PCOS patients undergoing IVF/ICSI (2010-2017). Standard ART protocols were applied, including controlled ovarian stimulation, oocyte retrieval, and embryo transfer. LASSO regression with 10-fold cross-validation selected 13 predictive features from 26 variables. Univariate and multivariate logistic regression analyses were performed for the overall cohort. A predictive nomogram was developed and internally validated using bootstrap resampling.

Among 377 PCOS patients analyzed, LASSO regression identified 13 potential predictors including age, IVF cycles, and endometrial thickness (EMT). In women <35 years (n = 333), multivariate analysis revealed three independent EP predictors: increased IVF cycle number (aOR = 4.592, 95%CI 1.48-14.21, p = 0.008), thinner EMT (aOR = 0.587, 95%CI 0.40-0.86, p = 0.007), and frozen embryo transfer (aOR = 0.044, 95%CI 0.01-0.22, p < 0.001). The developed nomogram incorporating these factors showed good discrimination (AUC 0.82) and calibration. Notably, clinical factors like abortion history and prolactin levels, while significant in univariate analysis, lost predictive value after multivariate adjustment in younger women.

This study identifies three key predictors of ectopic pregnancy in younger PCOS (<35 year) patients undergoing ART: IVF cycle number, endometrial thickness, and frozen embryo transfer. The developed nomogram provides a validated assessment tool, particularly for younger patients. These findings highlight the need for personalized risk stratification and further research into underlying mechanism.