Article Text
Abstract
Introduction/Background Almost 30% of patients diagnosed with atypical endometrial hyperplasia before surgery (preoperative-AEH) are found to have concurrent endometrial cancer (EC) at definitive hysterectomy, leading to incomplete primary surgery and delayed adjuvant treatment. This study aimed to investigate whether preoperative level of human epididymis protein 4 (HE4) could predict concurrent EC for preoperative-AEH patients and help to establish a nomogram for better clinical management.
Methodology Preoperative-AEH patients who underwent hysterectomy in a tertiary hospital from Jan 2020 to Dec 2022 were retrospectively analyzed. Independent predictive factors determined by multivariate logistic regression model were used to establish nomogram and internal validation was performed by a bootstrap resampling method.
Results A total of 455 preoperative-AEH patients were included, 23.4% of whom had concurrent EC. HE4 level significantly increased in concurrent-EC patients compared with final-diagnosed AEH patients (median 50.5 vs 43.7 pmol/L, p<0.001). ROC curve also showed good predictive potential of HE4 for concurrent EC (AUC = 0.696, 95%CI=0.633–0.760, p<0.001) and concurrent intermediate-high-risk EC (AUC = 0.713, 95%CI=0.563–0.863, p=0.005). Multivariate analysis revealed the independent predictive factors for concurrent EC were HE4 level (OR = 3.84; 95% CI =2.07–7.13), postmenopausal status (OR = 5.25; 95% CI = 2.26–12.22) and BMI (OR = 2.09, 95% CI = 1.12–3.91). The three factors were used to create the nomogram that showed a better goodness-of-fit for predicting concurrent EC. The bootstrap-corrected of concordance index of nomogram was 0.725 (95% CI=0.665–0.784), which was higher than that of each factor alone. The nomogram also displayed good consistency between the probabilities and observed values and potential clinical usefulness.
Conclusion HE4 showed good predictive potential for concurrent EC in preoperative-AEH patients. The nomogram based on HE4, postmenopausal status and BMI might improve this predictive value to stratify high-risk patients for better clinical strategy.
Disclosures The authors declared that they had no competing interests.