A nomogram-based prediction model for assessing the risk of vain and stump cancer recurrence following radical surgery for cervical cancer

Abstract This study aimed to construct a nomogram model to predict the risk of recurrent Vaginal Stump lesions after radical Cervical Cancer (CC) surgery, including Vaginal Intraepithelial Neoplasia (VaIN) and Stump Carcinoma. 79 patients were selected from January 2013 to November 2024, and the patient information and follow-ups were retrospectively analyzed. Branched-strand DNA hybrid capture technology was performed to analyze the expression level of HPV E6/E7 mRNA. Univariate/multivariate Cox hazards regression analyses were used to identify risk factors for recurrence, in order to develop nomograms for predicting the recurrence. The clinical usefulness of the predictive models was determined through Receiver Operating Characteristic (ROC) curve. VaIN and Stump Cancer occurred in 21 (26.6%) among 79 patients with radical treatment of CC (VaIN1 = 12, VaIN2-3 = 4, Cancer = 5), and the positive expression rate of HPV E6/E7 mRNA in relapsed patients was significantly higher than that in non-relapsed patients (P < 0.05). Cox regression analysis identified these independent risk factors for recurrence: invasion of cervical canal, tumor width, HPV E6/E7 mRNA expression. The nomogram constructed by these factors demonstrated good predictive ability, with an Area Under the Curve (AUC) of 0.852 (95% CI 0.806–0.899). The calibration chart showed that the predicted values agreed well with the measured values on the nomogram. We developed and validated a nomogram based on HPV E6/E7 mRNA and clinical characteristics, which could help to screen patients at high risk for vaginal stump recurrence after cervical cancer surgery.