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
ARTICLE HIGHLIGHTS
Research background

Although patients with borderline ovarian tumors (BOTs) have been reported to have a better survival outcome as compared to patients with epithelial ovarian cancer (EOC), there are many risk factors of BOTs. Nomogram has been successfully applied to predict the prognosis of many cancers based on some meaningful prognostic factors, but there is no such model to study the 1, 3, 5 years’ survival of BOTs.

Research motivation

Served as “semi-malignant ovarian tumors”, the overall survival of BOTs after the operation has been paid high attention by the clinicians and patients. It was necessary to construct a prognostic model to assess the survival outcome of patients with BOTs.

Research objectives

This research aimed to develop a nomogram to predict the possibility of OS in patients with BOTs, thus contributing to making individualized treatment recommendations.

Research methods

Totally 192 patients with BOTs and 374 patients with EOC were involved. Based on meaningful independent prognostic factors identified by univariate and multivariate Cox regression analyses, a nomogram model was developed to predict the 1-, 3-, and 5-year overall survival of patients with BOTs.

Research results

Compared to patients with EOC, patients with BOTs had better overall survival after 1:1 propensity score matching analysis (P value = 0.0067). We established a nomogram to predict the 1-, 3-, and 5-year OS of BOT patients. The C-index (0.959, 95% confidence interval 0.8708-1.0472) and calibration plots at 1, 3, and 5 years showed that the nomogram was a valid tool.

Research conclusions

The current research constructed a nomogram that could accurately give a personalized prediction of the prognosis of patients with BOTs. The outcome gained from our study might provide convenience to patients and clinicians.

Research perspectives

The nomogram developed by this study is the first to predict the 1-, 3-, and 5-year OS of women with BOTs. Moreover, it has been precisely assessed by internal validation. The results gained from our study will provide advice to make treatment planning.