Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Mar 6, 2022; 10(7): 2115-2126
Published online Mar 6, 2022. doi: 10.12998/wjcc.v10.i7.2115
Develop a nomogram to predict overall survival of patients with borderline ovarian tumors
Xiao-Qin Gong, Yan Zhang
Xiao-Qin Gong, Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
Yan Zhang, Department of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
Author contributions: Gong XQ and Zhang Y designed and performed the research, collected and analyzed the data; Gong XQ wrote the manuscript; Zhang Y revised the draft; all authors have read and approved the final manuscript.
Supported by National Key Technology R&D Program of China, No. 2019YFC1005200, No. 2019YFC1005202, and No. 2018YFC1002103.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of Tongji Hospital of Tongji Medical College at Huazhong University of Science and Technology Institutional Review Board (Approval No. TJ-IRB20190321).
Conflict-of-interest statement: The authors declare there are no conflicts of interest.
Informed consent statement: The data were anonymous and analyzed retrospectively. In accordance with the rules of the ethics committee, this study applied for exemption from informed consent.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yan Zhang, MD, Doctor, Department of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jie Fang Avenue, Wuhan 430030, Hubei Province, China. 283427856@qq.com
Received: November 29, 2021
Peer-review started: November 29, 2021
First decision: January 12, 2022
Revised: January 17, 2022
Accepted: February 23, 2022
Article in press: February 23, 2022
Published online: March 6, 2022
Processing time: 92 Days and 21.5 Hours
Abstract
BACKGROUND

The prognosis of borderline ovarian tumors (BOTs) has been the concern of clinicians and patients. It is urgent to develop a model to predict the survival of patients with BOTs.

AIM

To construct a nomogram to predict the likelihood of overall survival (OS) in patients with BOTs.

METHODS

A total of 192 patients with histologically verified BOTs and 374 patients with epithelial ovarian cancer (EOC) were retrospectively investigated for clinical characteristics and survival outcomes. A 1:1 propensity score matching (PSM) analysis was performed to eliminate selection bias. Survival was analyzed by using the log-rank test and the restricted mean survival time (RMST). Next, univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors. In addition, a nomogram model was developed to predict the 1-, 3-, and 5-year overall survival of patients with BOTs. The predictive performance of the model was assessed by using the concordance index (C-index), calibration curves, and decision curve analysis (DCA).

RESULTS

For clinical data, there was no significant difference in body mass index, preoperative CA199 concentration, or tumor localization between the BOTs group and EOC group. Women with BOTs were significantly younger than those with EOC. There was a significant difference in menopausal status, parity, preoperative serum CA125 concentration, Federation International of gynecology and obstetrics (FIGO) stage, and whether patients accepted postoperative adjuvant therapy between the BOT and EOC group. After PSM, patients with BOTs had better overall survival than patients with EOC (P value = 0.0067); more importantly, the 5-year RMST of BOTs was longer than that of EOC (P value = 0.0002, 95%CI -1.137 to -0.263). Multivariate Cox regression analysis showed that diagnosed age and surgical type were independent risk factors for BOT patient OS (P value < 0.05). A nomogram was developed based on diagnosed age, preoperative serum CA125 and CA199 Levels, surgical type, FIGO stage, and tumor size. Moreover, the c-index (0.959, 95% confidence interval 0.8708–1.0472), calibration plot of 1-, 3-, and 5-year OS, and decision curve analysis indicated the accurate predictive ability of this model.

CONCLUSION

Patients with BOTs had a better prognosis than patients with EOC. The nomogram we constructed might be helpful for clinicians in personalized treatment planning and patient counseling.

Keywords: Borderline ovarian tumors; Epithelial ovarian cancer; Nomogram; Survival

Core Tip: The recurrence and overall survival of borderline ovarian tumors (BOTs) after operation have been one of the main concerns of patients and clinicians. In this research, we firstly performed a 1:1 propensity score matching analysis by applying age as a matching variable, then we found that patients with BOTs had a better overall survival as compared to patients with epithelial ovarian cancer (EOC), more importantly, the 5-year restricted mean survival time of BOTs was longer than EOC. What’s more, we conducted a nomogram that could accurately predict 1, 3, 5-year overall survival in patients with BOTs.