Li SQ, Zhang KC, Li JY, Liang WQ, Gao YH, Qiao Z, Xi HQ, Chen L. Establishment and validation of a nomogram to predict the risk of ovarian metastasis in gastric cancer: Based on a large cohort. World J Clin Cases 2020; 8(19): 4331-4341 [PMID: 33083392 DOI: 10.12998/wjcc.v8.i19.4331]
Corresponding Author of This Article
Lin Chen, MD, PhD, Chief Doctor, Professor, Department of General Surgery, the First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing 100853, China. chenlin@301hospital.com.cn
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Cohort Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
Shao-Qing Li, Ke-Cheng Zhang, Ji-Yang Li, Wen-Quan Liang, Yun-He Gao, Zhi Qiao, Hong-Qing Xi, Lin Chen, Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
Shao-Qing Li, Ke-Cheng Zhang, Ji-Yang Li, Lin Chen, Institute of General Surgery, Chinese PLA General Hospital, Beijing 100853, China
Author contributions: Chen L, Xi HQ, Li SQ, Zhang KC and Li JY designed the study; Li SQ, Zhang KC and Li JY wrote the manuscript; Li SQ, Liang WQ and Gao YH collected the clinical data; Qiao Z, Li JY and Chen L contributed to data analysis and validation. Li SQ, Zhang KC and Li JY contributed equally to this work.
Supported byNational Nature Science Foundation of China, No. 81972790; and Beijing Nova Program, No. Z181100006218011.
Institutional review board statement: The study was reviewed and approved for publication by Chinese PLA General Hospital Institutional Review Board.
Conflict-of-interest statement: All Authors have no conflict of interest related to the manuscript.
Data sharing statement: The original anonymous dataset is available on request from the corresponding author at chenlin@301hospital.com.cn.
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: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Lin Chen, MD, PhD, Chief Doctor, Professor, Department of General Surgery, the First Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing 100853, China. chenlin@301hospital.com.cn
Received: May 29, 2020 Peer-review started: May 29, 2020 First decision: July 25, 2020 Revised: August 8, 2020 Accepted: August 26, 2020 Article in press: August 26, 2020 Published online: October 6, 2020 Processing time: 121 Days and 7.5 Hours
ARTICLE HIGHLIGHTS
Research background
Ovarian metastasis is a special type of distant metastasis unique to female patients with gastric cancer. A prediction model based on risk factors is needed to improve the rate of detection and diagnosis.
Research motivation
Gastric cancer with ovarian metastasis is rarely reported and no study has shown the relationship between the clinicopathologic features and the occurrence of ovarian metastasis. We attempted to structure a visual model to help us predict the risk of ovarian metastasis in gastric cancer.
Research objectives
The present study aimed to analyze risk factors of ovarian metastasis in women with gastric cancer and establish a nomogram to predict the probability of occurrence based on different clinicopathological features.
Research methods
A total of 1696 female patients diagnosed with gastric cancer were included. Potential risk factors for ovarian metastasis were analyzed using univariate and multivariable logistic regression. Independent risk factors were chosen to construct a nomogram which received internal validation.
Research results
Ovarian metastasis occurred in 83 of 1696 female patients. This study found that age ≤ 50 years, Lauren typing of non-intestinal, gastric cancer lesions containing signet-ring cell components, N stage > N2, positive expression of ER, serum CA125 > 35 U/mL, and a NLR > 2.16 were independent risk factors (all P < 0.05). A nomogram was constructed to quantitate the probability of the occurrence of ovarian metastasis which was internally validated.
Research conclusions
The nomogram model performed well in the prediction of ovarian metastasis. Attention should be paid to the possibility of ovarian metastasis in high-risk populations during re-examination, to ensure early detection and treatment.
Research perspectives
We will conduct a multi-center retrospective study and include more cases for analysis in the near future. External data from the SEER database will be used for further validation.
