Observational Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Apr 15, 2020; 12(4): 483-491
Published online Apr 15, 2020. doi: 10.4251/wjgo.v12.i4.483
Evaluation of the value of multiparameter combined analysis of serum markers in the early diagnosis of gastric cancer
Zhi-Guo Zhang, Liang Xu, Peng-Jun Zhang, Lei Han
Zhi-Guo Zhang, Lei Han, Department of Oncology, Beijing Daxing District People’s Hospital, Beijing 102600, China
Liang Xu, Peng-Jun Zhang, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Interventional Therapy Department, Peking University Cancer Hospital and Institute, Beijing 100142, China
Author contributions: Zhang ZG, Zhang PJ, and Han L designed the study; Zhang ZG and Xu L performed the research; Zhang ZG, Zhang PJ, and Han L analyzed the date; Zhang ZG wrote the paper; Zhang PJ and Han L revised the manuscript for final submission; Zhang ZG and Xu L contributed equally to this study; Zhang PJ and Han L are the co-corresponding authors.
Supported by the National Key R& D Program of China, No. 2016YFC0106604; and National Natural Science Foundation of China, No. 81502591.
Institutional review board statement: The study was reviewed and approved by the Beijing Daxing District People’s Hospital review board.
Informed consent statement: All study participants or their legal guardian provided written informed consent prior to study enrollment.
Conflict-of-interest statement: We declare that we have no financial or personal relationships with other individuals or organizations that can inappropriately influence our work and that there is no professional or other personal interest of any nature in any product, service and/or company that could be construed as influencing the position presented in or the review of the manuscript.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement – checklist of items, and the manuscript was prepared and revised according to the STROBE Statement – checklist of items.
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: Lei Han, MD, Professor, Department of Oncology, Beijing Daxing District People’s Hospital, No. 26 Huangcun West Street, Beijing 102600, China. zlk60283168@163.com
Received: December 21, 2019
Peer-review started: December 21, 2019
First decision: January 19, 2020
Revised: February 5, 2020
Accepted: March 22, 2020
Article in press: March 22, 2020
Published online: April 15, 2020
Processing time: 116 Days and 3.8 Hours
Core Tip

Core tip: In this study, we aimed to improve the diagnostic value of blood markers for gastric cancer. By comparing the binary logistic regression, discriminant analysis, classification tree and artificial neural network analysis, finally, artificial neural networks had better diagnostic value. When compared healthy control and gastric cancer, gastric polyp and gastric cancer, the area under the curve was 0.992 (0.980, 1.000) and 0.969 (0.948, 0.990), respectively. Based on artificial neural network and serum index, a novel diagnostic model for gastric cancer may be provided for clinical practice.