Li KJ, Zhang ZY, Wang K, Sulayman S, Zeng XY, Liu J, Chen Y, Zhao ZL. Prognostic scoring system using inflammation- and nutrition-related biomarkers to predict prognosis in stage I-III colorectal cancer patients. World J Gastroenterol 2025; 31(14): 104588 [DOI: 10.3748/wjg.v31.i14.104588]
Corresponding Author of This Article
Ze-Liang Zhao, MD, PhD, Professor, Department of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, No. 789 Suzhou East Street, Xinshi District, Urumqi 830000, Xinjiang Uygur Autonomous Region, China. zlzhao71@163.com
Research Domain of This Article
Oncology
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 Gastroenterol. Apr 14, 2025; 31(14): 104588 Published online Apr 14, 2025. doi: 10.3748/wjg.v31.i14.104588
Prognostic scoring system using inflammation- and nutrition-related biomarkers to predict prognosis in stage I-III colorectal cancer patients
Ke-Jin Li, Zi-Yi Zhang, Kuan Wang, Subinur Sulayman, Xiang-Yue Zeng, Juan Liu, Yi Chen, Ze-Liang Zhao
Ke-Jin Li, Zi-Yi Zhang, Kuan Wang, Subinur Sulayman, Xiang-Yue Zeng, Juan Liu, Ze-Liang Zhao, Department of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, Xinjiang Uygur Autonomous Region, China
Yi Chen, Department of Breast and Thyroid Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Xinjiang Key Laboratory of Oncology, Urumqi 830000, Xinjiang Uygur Autonomous Region, China
Co-corresponding authors: Yi Chen and Ze-Liang Zhao.
Author contributions: Li KJ wrote the original draft; Li KJ, Zeng XY and Zhang ZY contributed to the data analysis; Zhao ZL led the quality assessments; Wang K, Subinur S, Liu J and Chen Y collected the data; All authors have agreed on the manuscript to be submitted. Chen Y and Zhao ZL contributed to the study design and supervision. Chen Y and Zhao ZL contribute equally to this study as co-corresponding authors.
Supported by Natural Science Foundation of Xinjiang Uygur Autonomous Region, No. 2022D01C297.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of the Affiliated Cancer Hospital of Xinjiang Medical University, Approval No. K-2024056.
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: The authors declare no conflicts of interest for this article.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at zlzhao71@163.com. Participants gave informed consent for data sharing.
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: Ze-Liang Zhao, MD, PhD, Professor, Department of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, No. 789 Suzhou East Street, Xinshi District, Urumqi 830000, Xinjiang Uygur Autonomous Region, China. zlzhao71@163.com
Received: December 25, 2024 Revised: February 22, 2025 Accepted: March 21, 2025 Published online: April 14, 2025 Processing time: 107 Days and 10.2 Hours
Abstract
BACKGROUND
Colorectal cancer (CRC) is a common malignancy that has become a global burden. The prognostic prediction of CRC patients on the basis of inflammatory biomarkers and nutritional biomarkers has shown some potential but has not been fully explored.
AIM
To develop and validate a prognostic model for CRC based on inflammation and nutrition-related biomarkers and to evaluate its predictive value for patient outcomes.
METHODS
Patients were randomized at a 3:2 ratio into a training cohort (n = 282) or a validation cohort (n = 188). To identify the optimal prognostic factors for constructing the risk score (RS), LASSO Cox regression analysis was conducted. The association between the RS and overall survival (OS) was evaluated using receiver operating characteristic (ROC) curves and Kaplan-Meier (K-M) survival analysis. Independent risk factors were screened by multivariate Cox regression analysis. Nomograms were constructed and validated on the basis of these factors.
RESULTS
In the training cohort, univariate analysis of all the inflammatory and nutritional biomarkers demonstrated some predictive value. A LASSO-Cox analysis included four biomarkers and constructed an RS. Through ROC analysis, the area under the prognostic curve was 0.795. K-M survival curve analyses revealed that the five-year OS was significantly greater in the Low-RS group than in the High-RS group (P < 0.001). Multivariate analysis demonstrated that the degree of differentiation (P = 0.001), degree of nerve invasion (P = 0.022), and RS (P < 0.001) were independent risk factors. We constructed a nomogram to predict the OS of CRC patients and validated it in a separate cohort. The calibration curve showed high accuracy. Additionally, decision curve analysis for 1-year, 3-year, and 5-year survival probabilities indicated significant clinical utility in predicting survival outcomes.
CONCLUSION
This study developed a nomogram based on the RS to predict the OS of CRC patients. This nomogram can guide treatment decisions and enable the formulation of personalized follow-up strategies on the basis of predicted recurrence risk, aiming to improve long-term prognosis.
Core Tip: This study developed a nomogram incorporating inflammatory and nutritional biomarkers to predict the overall survival of patients with colorectal cancer (CRC). The nomogram, which is based on a risk score derived from four selected biomarkers, demonstrated high prognostic accuracy and clinical utility. This information can help guide treatment decisions and personalize follow-up strategies, ultimately improving long-term outcomes for CRC patients.
