Development and validation of a nomogram to predict symptomatic recurrence following laparoscopic adenomyomectomy

Introduction: Nomograms are intuitive graphical tools that integrate multiple prognostic variables to generate individualized risk estimates. To date, no study has developed a validated prediction model specifically for symptomatic recurrence after uterine-sparing surgery for adenomyosis. Accordingly, this study aimed to construct and validate a nomogram based on retrospective clinical data to predict symptomatic recurrence after laparoscopic adenomyomectomy and to inform individualized postoperative management. Materials and Methods: In this retrospective cohort study, 484 consecutive patients who underwent primary laparoscopic adenomyomectomy between December 1, 2017, and March 30, 2022, were included. All patients completed postoperative follow-up. Symptomatic recurrence occurred in 131 patients, while 353 remained recurrence-free. Independent predictors of recurrence were identified using multivariate Cox regression, and a nomogram was constructed. Model discrimination was evaluated using Harrell's concordance index (C-index) and internally validated using 5-fold cross-validation. Model performance was assessed via receiver operating characteristic curve, calibration curves, and decision curve analysis. A sensitivity analysis using inverse probability of treatment weighting (IPTW) confirmed the robustness of the identified predictors against residual confounding. Results: Previous surgical history of ovarian endometrioma, preoperative CA125 level, concomitant ovarian endometrioma, postoperative medication modality, and duration of postoperative therapy were independent predictors of symptomatic recurrence. The nomogram demonstrated good discriminatory ability (area under the receiver operating characteristic curve [AUC], 0.776; 95% confidence interval [CI], 0.728-0.824). The calibration curve also had a good performance, and the DCA indicated that patients achieved a high net benefit for the predicted probability thresholds between 0% and 60%. Conclusion: This nomogram provides accurate individualized risk estimation for symptomatic recurrence after laparoscopic adenomyomectomy, which requires multicenter external validation to confirm its clinical utility.