| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| 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/ |
| Copyright |
© The Author(s) 2025. 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 |
Oncology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Predicting chemotherapy-induced myelosuppression in colorectal cancer: An interpretable, machine learning-based nomogram
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Yu-Ming Liu, Yan-Yuan Du, Ying Song, Hong-Tai Xiong, Hui-Bo Yu, Bai-Hui Li, Liu Cai, Su-Su Ma, Jin Gao, Han-Yue Zhang, Rui-Ying Fang, Rui Cai and Hong-Gang Zheng |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Beijing Municipal Natural Science Foundation |
No. 7252262 |
| High Level Chinese Medical Hospital Promotion Project |
No. HLCMHPP2023085 |
| National Natural Science Foundation of China |
No. 82174463 |
| National Administration of Traditional Chinese Medicine |
No. ZYYCXTD-C-C202205 |
| China Academy of Chinese Medical Sciences |
No. CI2021A01804 |
| China Academy of Chinese Medical Sciences |
No. 2022S469 |
|
| Corresponding Author |
Hong-Gang Zheng, Department of Oncology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, No. 5 Beixiange, Xicheng District, Beijing 100053, China. honggangzheng@126.com |
| Key Words |
Colorectal cancer; Chemotherapy-induced myelosuppression; Machine learning; Nomogram; Risk factors |
| Core Tip |
This study developed and validated the first clinic-machine learning (ML) nomogram for predicting chemotherapy-induced myelosuppression in colorectal cancer patients receiving first-line chemotherapy. By integrating clinical variables with multiple ML algorithms through a feature mapping algorithm, the model achieved high discrimination, good calibration, and consistent net clinical benefit. Unlike conventional nomograms or single-algorithm approaches, this clinic-ML nomogram combines interpretability with robust predictive accuracy, providing a practical decision-support tool to optimize individualized treatment strategies. |
| Publish Date |
2025-11-13 06:51 |
| Citation |
<p>Liu YM, Du YY, Song Y, Xiong HT, Yu HB, Li BH, Cai L, Ma SS, Gao J, Zhang HY, Fang RY, Cai R, Zheng HG. Predicting chemotherapy-induced myelosuppression in colorectal cancer: An interpretable, machine learning-based nomogram. <i>World J Gastroenterol</i> 2025; 31(42): 112180</p> |
| URL |
https://www.wjgnet.com/1007-9327/full/v31/i42/112180.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v31.i42.112180 |
