Clinical Characteristics Predict Recurrence in Borderline Ovarian Tumor Patients with Fertility-Preserving Surgery

Abstract

Yunan He,1,* Jiaojiao Zhong,2,* Hui Yang,3 Nianchun Shan,4 Anran Cheng5,6 1Reproductive Medical Center, Department of Gynecology and Obstetrics, Tangdu Hospital, Air Force Medical University, Xi’an, Shaanxi, People’s Republic of China; 2Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, Jiangsu, People’s Republic of China; 3Department of Gynecology and Obstetrics, The First Affiliated Hospital of Hunan University of Medicine, Huaihua, Hunan, People’s Republic of China; 4Department of Gynecology and Obstetrics, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 5Department of Gynecology and Obstetrics, Xiamen Maluanwan Hospital, Xiamen,Fujian, People’s Republic of China; 6Department of Gynecology Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Anran Cheng, Department of Gynecology and Obstetrics, Xiamen Maluanwan Hospital, Dongyao Cun, Maluanwan New Town, Haicang District, Xiamen, Fujian, 361027, People’s Republic of China, Tel/Fax [phone], Email [email protected] Nianchun Shan, No. 87 Xiangya Road, Hunan, 41008, People’s Republic of China, Tel/Fax [phone], Email [email protected]: To identify prognostic factors in patients with borderline ovarian tumor (BOT) and establish and validate a nomogram predicting recurrence in BOT patients treated with fertility-preserving surgery.Patients and Methods: Patients with BOT who underwent surgery at two institutions between January 2000 and June 2017 were included and categorized into training and validation cohorts. Univariate log rank test and Cox regression analysis were performed in the training cohort to identify prognostic factors, and a nomogram was developed to predict the recurrence rate. The model was validated by calculating the C-index and drawing the calibration curve and receiver operating curve (ROC).Conclusion: In the multivariate Cox regression analysis, practice period, past history of benign ovarian disease, past history of benign breast disease, elevated CA125 levels, elevated CA199 levels, surgical methods, greater omentum resection, FIGO stage, postoperative pregnancy, and re-operation were independently associated with recurrence-free survival (p< 0.05). The aforementioned prognostic factors were used to develop a nomogram. The nomogram demonstrated a good ability to predict the risk of recurrence (training cohort C-index: 0.866, validation cohort C-index: 0.920). The calibration curve suggested that the predicted recurrence-free survival was closely related to the actual recurrence. ROC analysis showed that the nomogram had a good discriminatory power with the area under curve between 0.776 and 0.956. The nomogram can predict the 1-, 3-, and 5-year recurrence-free survival of BOT patients undergoing fertility-preserving surgery. The predictive model can help guide surgical plans, postoperative monitoring, and prognostic evaluation of BOT patients.Keywords: borderline ovarian tumor, fertility-preserving surgery, recurrence, disease-free survival, prediction model

Keywords

• borderline ovarian tumor
• fertility-preserving surgery
• recurrence
• disease-free survival
• prediction model