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©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Aug 27, 2024; 16(8): 2602-2611
Published online Aug 27, 2024. doi: 10.4240/wjgs.v16.i8.2602
Published online Aug 27, 2024. doi: 10.4240/wjgs.v16.i8.2602
Construction of a predictive model for gastric cancer neuroaggression and clinical validation analysis: A single-center retrospective study
Yu-Yin Lan, Department of Stomatology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200071, China
Jing Han, Department of Biobank, Zhejiang Cancer Hospital, Hangzhou 310005, Zhejiang Province, China
Yan-Yan Liu, Department of General Surgery, Peking University First Hospital, Beijing 100034, China
Lei Lan, Department of Oncology, Zhejiang Hospital, Hangzhou 310013, Zhejiang Province, China
Author contributions: Lan YY wrote the manuscript; Han J and Liu YY collected the data and Lan L guided the study; All authors reviewed, edited, and approved the final manuscript and revised it critically for important intellectual content, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work.
Institutional review board statement: This study was approved by the Medical Research Ethics Committee of Peking University First Hospital, No. GYZL-ZN-2023-049.
Informed consent statement: This study has obtained the informed consent of the patients and their families for treatment, and signed the informed consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: All data used in this study came from a single-center retrospective analysis that had passed appropriate ethical approval and patient privacy safeguards. The sharing of data will be in strict compliance with relevant laws, regulations and ethical guidelines to ensure that the use of data is limited to scientific research purposes and shall not be used for any commercial purposes or infringe on patient privacy.
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: Lei Lan, MM, Doctor, Department of Oncology, Zhejiang Hospital, No. 1229 Gudun Road, Xihu District, Hangzhou 310013, Zhejiang Province, China.
Received: May 13, 2024
Revised: June 8, 2024
Accepted: June 27, 2024
Published online: August 27, 2024
Processing time: 95 Days and 6.5 Hours
Revised: June 8, 2024
Accepted: June 27, 2024
Published online: August 27, 2024
Processing time: 95 Days and 6.5 Hours
Core Tip
Core Tip: By collecting clinical data of patients with single-center gastric cancer, a predictive model of neuroaggression was constructed and analyzed for clinical validation. The research included screening for relevant factors affecting gastric cancer neuroaggression, building predictive models using statistical and machine learning methods, and evaluating the accuracy and usefulness of the models through cross-validation and external validation. Finally, the performance of the model in clinical practical application is analyzed to provide clinicians with a reliable predictive tool aimed at optimizing the diagnosis and treatment strategies of gastric cancer and improving the prognosis and survival rate of patients.