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Published on: May 16, 2025
Predictive value of the Chinese Visceral Adiposity Index for disease activity and vedolizumab response in ulcerative
Yibing Hu1, Jiaojiao Wei1, Minlihu Hu1
1Department of Gastroenterology. Affiliated Jinhua Hospital. Zhejiang University School of Medicine.
Introduction:
Objective: ulcerative colitis (UC) is characterized by chronic nonspecific inflammation of the intestinal tract. The identification of non-invasive biomarkers that can reflect intestinal inflammation and predict therapeutic response is vital. This study aimed to assess the predictive value of the Chinese Visceral Adiposity Index (CVAI) for the assessment of both disease activity and response to vedolizumab therapy. Method: this retrospective study analyzed clinical data from patients with UC between January 2021 and December 2023. Healthy individuals were recruited as controls. Disease activity was evaluated using the modified Mayo score, while clinical response was assessed using patient-reported outcomes (PRO2). Mayo Endoscopic Score (MES) was used for the grading of mucosal lesions. Receiver operating characteristic (ROC) curves were used to assess the ability of various indices to differentiate between patients with UC and healthy controls. Results: patients with UC (n = 82) had significantly higher CVAIs compared to healthy controls (n = 72) (36.34 ± 19.82 vs. 55.93 ± 25.14, p < 0.001). ROC analysis indicated that CVAI was the most effective predictive factor in distinguishing between patients with UC and healthy controls, with the highest area under the curve (AUC = 0.720). The CVAI was significantly correlated with clinical activity and endoscopic scores in patients with UC, while patients who responded to vedolizumab had lower pre-treatment CVAIs compared to non-responders (54.14 ± 15.45 vs. 72.84 ± 21.44, p = 0.002). A low pre-treatment CVAI score was also effective in predicting the response to vedolizumab (AUC = 0.789). Conclusion: The CVAI may be a valuable marker for assessing disease activity in UC and has the potential to predict the response to vedolizumab therapy.
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