| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
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/ |
| Copyright |
© The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Estimating the survival benefit of adjuvant therapy based on bayesian network prediction model in curative resected advanced gallbladder adenocarcinoma
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Zhi-Min Geng, Zhi-Qiang Cai, Zhen Zhang, Zhao-Hui Tang, Feng Xue, Chen Chen, Dong Zhang, Qi Li, Rui Zhang, Wen-Zhi Li, Lin Wang and Shu‐Bin Si |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Natural Science Foundation of China |
81572420 |
| National Natural Science Foundation of China |
71871181 |
| Key Research and Development Program of Shaanxi Province |
2017ZDXM-SF-055 |
|
| Corresponding Author |
Shu‐Bin Si, PhD, Dean, Professor, Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an 710072, Shaanxi Province, China. sisb@nwpu.edu.cn |
| Key Words |
Gallbladder carcinoma; Bayesian network; Surgery; Adjuvant therapy; Prediction model; |
| Core Tip |
A Bayesian network model was constructed to predict the survival time for patients with advanced gallbladder carcinoma (GBC) after curative resection from the Surveillance, Epidemiology, and End Results database, with a model accuracy of 69.67%, and the area under the curve value of testing dataset was 77.72%. Adjuvant radiation, chemotherapy and T stage were ranked as the top 3 prognostic factors by importance measures. The prediction model supported the role of adjuvant therapy for advanced GBC patients after curative resection. Adjuvant chemoradiotherapy is expected to improve the survival more significantly for patients with node-positive disease. |
| Publish Date |
2019-09-30 02:14 |
| Citation |
Geng ZM, Cai ZQ, Zhang Z, Tang ZH, Xue F, Chen C, Zhang D, Li Q, Zhang R, Li WZ, Wang L, Si SB. Estimating the survival benefit of adjuvant therapy based on bayesian network prediction model in curative resected advanced gallbladder adenocarcinoma. World J Gastroenterol 2019; 25(37): 5655-5666 |
| URL |
https://www.wjgnet.com/1007-9327/full/v25/i37/5655.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v25.i37.5655 |
