A predictive model for recurrence after hysteroscopic endometrial polypectomy: a combined analysis of clinical and ultrasound parameters.

Abstract

Objective: To develop and validate a predictive model using clinical characteristics and ultrasound parameters to assess the 12-month recurrence risk following hysteroscopic endometrial polypectomy, and to explore the potential association between inflammation-related variables and recurrence.

Methods: This single-center retrospective study enrolled 170 patients who underwent hysteroscopic endometrial polypectomy between March 2023 and December 2024 and completed 12 months of follow-up. Patients were divided into a recurrence group (n = 43) and a non-recurrence group (n = 127). Clinical characteristics, ultrasound parameters, and inflammation-related indicators were collected. Multivariate logistic regression was employed to identify independent risk factors for recurrence. Receiver operating characteristic curve analysis was conducted to assess the predictive performance of individual markers and the integrated model. Risk stratification was performed using the Youden index.

Results: Multivariate analysis revealed that a history of polycystic ovary syndrome, increased endometrial thickness, and a higher number of polyps were independent predictors of postoperative recurrence (all P < 0.05). The combined predictive model demonstrated good performance, with an area under the curve of 0.8216. Following risk stratification, the high-risk group exhibited a substantially higher recurrence rate than the low-risk group (46.8% vs. 7.5%).

Conclusion: The predictive model, integrating clinical and ultrasound-related factors, performed well in assessing recurrence risk after hysteroscopic endometrial polypectomy. It may serve as a useful tool for postoperative risk stratification and individualized follow-up management.