Guan SH, Wang Q, Ma XM, Qiao WJ, Li MZ, Lai MG, Wang C. Development of an innovative nomogram of risk factors to predict postoperative recurrence of gastrointestinal stromal tumors. World J Gastrointest Surg 2022; 14(9): 940-949 [PMID: 36185569 DOI: 10.4240/wjgs.v14.i9.940]
Corresponding Author of This Article
Cheng Wang, MM, Chief Doctor, Professor, Department of Gastrointestinal Tumor Surgery, The Affiliated Hospital of Qinghai University, No. 29 Tongren Road, Xining 810001, Qinghai Province, China. cheng_wang_vip@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective 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/
Shi-Hao Guan, Department of General Surgery, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai 201700, China
Shi-Hao Guan, Medical College, Qinghai University, Xining 810001, Qinghai Province, China
Qiong Wang, Department of Medical Oncology, The Affiliated Hospital of Qinghai University, Xining 810001, Qinghai Province, China
Xiao-Ming Ma, Wen-Jie Qiao, Ming-Zheng Li, Ming-Gui Lai, Cheng Wang, Department of Gastrointestinal Tumor Surgery, The Affiliated Hospital of Qinghai University, Xining 810001, Qinghai Province, China
Author contributions: Guan SH is the author of the main idea, conceived and designed the study, collected and analyzed the data, and wrote and revised the manuscript; Wang C conceived and designed the study, collected and analyzed the data and wrote the manuscript; Wang Q and Ma XM participated in drafting and revising the manuscript, and collected the data; Qiao WJ, Li MZ and Lai MG revised the manuscript and analyzed the data. All authors approved the final version of the manuscript.
Institutional review board statement: This study was approved by the Institutional Research Ethics Board of Qinghai University Affiliated Hospital (Xining, China) and followed the Declaration of Helsinki.
Informed consent statement: All patients signed informed consent forms.
Conflict-of-interest statement: Each author in this paper declares no conflict of interest.
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: Cheng Wang, MM, Chief Doctor, Professor, Department of Gastrointestinal Tumor Surgery, The Affiliated Hospital of Qinghai University, No. 29 Tongren Road, Xining 810001, Qinghai Province, China. cheng_wang_vip@163.com
Received: April 14, 2022 Peer-review started: April 14, 2022 First decision: June 10, 2022 Revised: July 2, 2022 Accepted: August 7, 2022 Article in press: August 7, 2022 Published online: September 27, 2022
ARTICLE HIGHLIGHTS
Research background
There are many staging systems for gastrointestinal stromal tumors (GISTs), and the risk indicators selected are also different; thus, it is not possible to quantify the risk of recurrence among individual patients.
Research motivation
To develop a nomogram of postoperative recurrence risk factors in GIST patients to further guide individualized treatment.
Research objectives
To investigate the risk factors for postoperative recurrence in GIST patients.
Research methods
We retrospectively analyzed the clinical and pathological data of 130 patients with GIST. The least absolute shrinkage and selection operator regression model and multivariable logistic regression analysis were used to develop a prediction model. The index of concordance (C-index), calibration curve, receiver operating characteristic curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predictive model.
Research results
The nomogram included tumor site, lesion size, mitotic rate/50 high power fields, Ki-67 index, intracranial necrosis, and age as predictors. The model presented a perfect discrimination with a reliable C-index. The receiver operating characteristic curve indicated a good predictive value. Decision curve analysis showed that the predicting recurrence nomogram was clinically feasible.
Research conclusions
This recurrence nomogram combines tumor site, lesion size, mitotic rate, Ki-67 index, intracranial necrosis, and age and can easily predict patient prognosis.
Research perspectives
We look forward to conducting a multicenter large-sample prospective controlled study in the future to further explore risk factors after GIST surgery, to better guide individualized treatment.
