Zhang XY, Li YK, Tian ZB, Guo QY, Liu JN, Liu RQ, Ren KY. Predictive model for vedolizumab efficacy in moderate-to-severe ulcerative colitis based on computed tomography-derived body compositions and nutritional inflammatory markers. World J Radiol 2026; 18(3): 117599 [DOI: 10.4329/wjr.v18.i3.117599]
Corresponding Author of This Article
Ke-Yu Ren, Department of Gastroenterology, The Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Qingdao 266000, Shandong Province, China. renkeyuqd@126.com
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Medicine, General & Internal
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Retrospective Study
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Mar 28, 2026 (publication date) through Mar 26, 2026
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World Journal of Radiology
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1949-8470
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Zhang XY, Li YK, Tian ZB, Guo QY, Liu JN, Liu RQ, Ren KY. Predictive model for vedolizumab efficacy in moderate-to-severe ulcerative colitis based on computed tomography-derived body compositions and nutritional inflammatory markers. World J Radiol 2026; 18(3): 117599 [DOI: 10.4329/wjr.v18.i3.117599]
World J Radiol. Mar 28, 2026; 18(3): 117599 Published online Mar 28, 2026. doi: 10.4329/wjr.v18.i3.117599
Predictive model for vedolizumab efficacy in moderate-to-severe ulcerative colitis based on computed tomography-derived body compositions and nutritional inflammatory markers
Xiao-Yan Zhang, Yu-Kun Li, Zi-Bin Tian, Ke-Yu Ren, Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
Qing-Yu Guo, Department of Gastroenterology, School of Nursing, Qingdao University, Qingdao 266000, Shandong Province, China
Jing-Nong Liu, Department of Gastroenterological Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
Rui-Qing Liu, Department of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
Co-first authors: Xiao-Yan Zhang and Yu-Kun Li.
Co-corresponding authors: Rui-Qing Liu and Ke-Yu Ren.
Author contributions: Zhang XY and Li YK contributed equally to this article, they are the co-first authors of this manuscript; Zhang XY, Tian ZB, Liu RQ, and Ren KY designed the research study; Zhang XY, Li YK, Guo QY, and Liu JN performed the research; Liu RQ and Ren KY contributed equally to this article, they are the co-corresponding authors of this manuscript; and all authors thoroughly reviewed and endorsed the final manuscript.
Institutional review board statement: This study was approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University, approval No. QYFYWZLL30641.
Informed consent statement: Informed consent was waived by the Ethics Committee of the Affiliated Hospital of Qingdao University due to the retrospective design and the use of de-identified patient data that could not be linked to individuals.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The datasets analyzed during the current study are not publicly available due to patient privacy concerns but are available from the corresponding author on reasonable request.
Corresponding author: Ke-Yu Ren, Department of Gastroenterology, The Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Qingdao 266000, Shandong Province, China. renkeyuqd@126.com
Received: December 11, 2025 Revised: January 20, 2026 Accepted: March 5, 2026 Published online: March 28, 2026 Processing time: 105 Days and 13.9 Hours
Abstract
BACKGROUND
Vedolizumab (VDZ) is a key biologic for moderate-to-severe ulcerative colitis (UC), but therapeutic response varies widely among patients. The combined predictive value of computed tomography (CT)-derived body composition (e.g., intramuscular adipose tissue, skeletal muscle mass), inflammatory markers [C-reactive protein (CRP)], and anemia status for VDZ efficacy remains under-investigated.
AIM
To develop a predictive model for VDZ response in moderate-to-severe UC patients, based on CT-derived body composition and nutritional/inflammatory markers, and to clarify their clinical implications.
METHODS
A retrospective study was conducted on UC patients treated with VDZ at the Affiliated Hospital of Qingdao University. CT images were analyzed to quantify intramuscular adipose tissue and skeletal muscle mass. Clinical data including CRP levels and hemoglobin (HB) were collected. Multivariate logistic regression was used to identify independent predictors of treatment response, and a predictive model was constructed.
RESULTS
IMAT accumulation (odds ratio = 2.35, 95% confidence interval: 1.21-4.57, P = 0.012) and elevated CRP (odds ratio = 1.89, 95% confidence interval: 1.03-3.49, P = 0.041) were confirmed as independent predictors of poor VDZ response. Preserved skeletal muscle mass and normal HB levels were associated with better therapeutic outcomes. The combined predictive model demonstrated good discriminative ability (area under the curve = 0.78).
CONCLUSION
This study demonstrates that CT-derived body composition parameters (IMAT and skeletal muscle mass), combined with inflammatory markers (CRP) and HB levels, can effectively predict VDZ response in UC patients. The predictive model we developed offers a practical tool for identifying high-risk non-responders early, enabling clinicians to optimize individualized treatment strategies and improve clinical outcomes.
Core Tip: Combined assessment of intramuscular adipose tissue, C-reactive protein levels, skeletal muscle mass and hemoglobin status can effectively predict vedolizumab response in ulcerative colitis patients. Routine screening of these markers helps identify potential non-responders early, optimize individualized treatment regimens, and improve clinical management efficiency of ulcerative colitis.
