Li HY, Zhou JT, Wang YN, Zhang N, Wu SF. Establishment and application of three predictive models of anastomotic leakage after rectal cancer sphincter-preserving surgery. World J Gastrointest Surg 2023; 15(10): 2201-2210 [PMID: 37969722 DOI: 10.4240/wjgs.v15.i10.2201]
Corresponding Author of This Article
Shao-Fen Wu, BSc, Nurse, Department of Gastroenterology, Jincheng People’s Hospital of Shanxi Province, No. 1168 Baishui East Street, Jincheng 048026, Shanxi Province, China. wushaofen3322@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/
World J Gastrointest Surg. Oct 27, 2023; 15(10): 2201-2210 Published online Oct 27, 2023. doi: 10.4240/wjgs.v15.i10.2201
Establishment and application of three predictive models of anastomotic leakage after rectal cancer sphincter-preserving surgery
Hui-Yuan Li, Jiang-Tao Zhou, Ya-Nan Wang, Ning Zhang, Shao-Fen Wu
Hui-Yuan Li, Jiang-Tao Zhou, Ya-Nan Wang, Ning Zhang, Department of General Surgery, Jincheng People’s Hospital of Shanxi Province, Jincheng 048026, Shanxi Province, China
Shao-Fen Wu, Department of Gastroenterology, Jincheng People’s Hospital of Shanxi Province, Jincheng 048026, Shanxi Province, China
Author contributions: Li HY designed the study and wrote the manuscript; Wu SF designed the study and reviewed the manuscript; Zhou JT, Wang YN, and Zhang N provided clinical advice.
Institutional review board statement: The study was reviewed and approved by the Jincheng People’s Hospital of Shanxi Province (JCPH.No20230407001).
Informed consent statement: All study participants or their legal guardians provided written informed consent for personal and medical data collection before study enrolment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Dataset available from the corresponding author at wushaofen3322@163.com.
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: Shao-Fen Wu, BSc, Nurse, Department of Gastroenterology, Jincheng People’s Hospital of Shanxi Province, No. 1168 Baishui East Street, Jincheng 048026, Shanxi Province, China. wushaofen3322@163.com
Received: July 12, 2023 Peer-review started: July 12, 2023 First decision: August 2, 2023 Revised: August 9, 2023 Accepted: August 18, 2023 Article in press: August 18, 2023 Published online: October 27, 2023 Processing time: 107 Days and 6.7 Hours
Abstract
BACKGROUND
Anastomotic leakage (AL) occurs frequently after sphincter-preserving surgery for rectal cancer and has a significant mortality rate. There are many factors that influence the incidence of AL, and each patient’s unique circumstances add to this diversity. The early identification and prediction of AL after sphincter-preserving surgery are of great significance for the application of clinically targeted preventive measures. Developing an AL predictive model coincides with the aim of personalised healthcare, enhances clinical management techniques, and advances the medical industry along a more precise and intelligent path.
AIM
To develop nomogram, decision tree, and random forest prediction models for AL following sphincter-preserving surgery for rectal cancer and to evaluate the predictive efficacy of the three models.
METHODS
The clinical information of 497 patients with rectal cancer who underwent sphincter-preserving surgery at Jincheng People’s Hospital of Shanxi Province between January 2017 and September 2022 was analyzed in this study. Patients were divided into two groups: AL and no AL. Using univariate and multivariate analyses, we identified factors influencing postoperative AL. These factors were used to establish nomogram, decision tree, and random forest models. The sensitivity, specificity, recall, accuracy, and area under the receiver operating characteristic curve (AUC) were compared between the three models.
RESULTS
AL occurred in 10.26% of the 497 patients with rectal cancer. The nomogram model had an AUC of 0.922, sensitivity of 0.745, specificity of 0.966, accuracy of 0.936, recall of 0.987, and accuracy of 0.946. The above indices in the decision tree model were 0.919, 0.833, 0.862, 0.951, 0.994, and 0.955, respectively and in the random forest model were 1.000, 1.000, 1.000, 0.951, 0.994, and 0.955, respectively. The DeLong test revealed that the AUC value of the decision-tree model was lower than that of the random forest model (P < 0.05).
CONCLUSION
The random forest model may be used to identify patients at high risk of AL after sphincter-preserving surgery for rectal cancer owing to its strong predictive effect and stability.
Core Tip: Anastomotic leakage (AL) is a very dangerous complication of rectal cancer surgery, which not only increases the recurrence rate of the tumor but also lowers the quality of life of affected patients. We examined the clinical data of 497 patients with rectal cancer to determine variables that influence AL. We established nomogram, decision tree, and random forest models to identify a prediction model tool for forecasting AL after rectal cancer surgery.
