Development and internal validation of a nomogram for predicting endometrial polyp recurrence after hysteroscopic polypectomy

Abstract

Endometrial polyps (EP) are common, and hysteroscopic polypectomy is the reference treatment, but recurrence is frequent. This study aimed to identify risk factors for recurrence and to develop and internally validate a nomogram for individual postoperative risk stratification. In this single-center retrospective study, women with a histologically confirmed benign EP treated by hysteroscopic polypectomy between May 2023 and May 2025 and followed for at least 12 months were analyzed. The primary outcome was recurrence within 12 months. Variables were selected by least absolute shrinkage and selection operator (LASSO) regression and entered into multivariable logistic regression to build a nomogram. Performance was assessed by discrimination (area under the curve, AUC), calibration, and decision curve analysis (DCA), with internal validation by 1000 bootstrap resamples. Of 240 women (median follow-up 18.0 months), 43 (17.9%) had recurrence. Multiple polyps (odds ratio [OR] 3.75, 95% confidence interval [CI] 1.73–8.11), higher body mass index (BMI; OR 1.17, 95% CI 1.05–1.29), and uterine leiomyoma (OR 2.38, 95% CI 1.04–5.45) were independently associated with increased recurrence, whereas postoperative medical management was associated with lower odds (OR 0.35, 95% CI 0.17–0.75). The nomogram showed an apparent AUC of 0.784 (bootstrap-corrected 0.750), good calibration (Hosmer–Lemeshow P = 0.304), and positive net benefit on DCA. Multiple polyps, higher BMI, and uterine leiomyoma were independently associated with recurrence after hysteroscopic polypectomy, whereas postoperative medical management was associated with a lower likelihood of recurrence. On internal validation the nomogram showed acceptable discrimination and calibration and might assist in postoperative risk stratification, pending external validation.