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©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Apr 16, 2022; 10(11): 3389-3400
Published online Apr 16, 2022. doi: 10.12998/wjcc.v10.i11.3389
Published online Apr 16, 2022. doi: 10.12998/wjcc.v10.i11.3389
Added value of systemic inflammation markers for monitoring response to neoadjuvant chemotherapy in breast cancer patients
Zi-Rui Ke, Wei Chen, Man-Xiu Li, Shun Wu, Li-Ting Jin, Tie-Jun Wang, Department of Breast Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology and Hubei Provincial Clinical Research Center for Breast Cancer, Wuhan 430079, Hubei Province, China
Author contributions: Ke ZR and Chen W originated the idea, data analysis and writing; Li MX, Wu S, Jin LT and Wang TJ contributed to the data analysis and writing; all authors have read and approved the manuscript.
Institutional review board statement: This study was approved by the Institutional Ethics Committee of the Hubei Cancer Hospital (Reference: LLHBCH2021YN-021), in compliance with the Declaration of Helsinki.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data that were obtained after each patient agreed to treatment by written consent.
Conflict-of-interest statement: None of the authors have any conflicts of interest to declare.
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: Tie-Jun Wang, MD, Chief Doctor, Department of Breast Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology and Hubei Provincial Clinical Research Center for Breast Cancer, No. 116 Zhuodaoquan South Road, Hongshan District, Wuhan 430079, Hubei Province, China. tiejunwanghp@163.com
Received: October 25, 2021
Peer-review started: October 25, 2021
First decision: December 17, 2021
Revised: December 23, 2021
Accepted: February 27, 2022
Article in press: February 27, 2022
Published online: April 16, 2022
Peer-review started: October 25, 2021
First decision: December 17, 2021
Revised: December 23, 2021
Accepted: February 27, 2022
Article in press: February 27, 2022
Published online: April 16, 2022
Core Tip
Core Tip: For predicting response after neoadjuvant chemotherapy (rNACT), some machine learning-based models performed better than models using conventional methods, and the support vector machine model performed best. Preoperative serum lipids and serum inflammation markers have contributed to predicting rNACT in breast cancer patients. These results suggested the need to raise awareness of the importance of minimally-invasive approaches for monitoring breast cancer patients who intended to undergo neoadjuvant chemotherapy. However, the current study needs to be validated with caution and require external validation in the future.