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. 2025 Jan 1;22(1):53-58.
doi: 10.17392/1770-22-01. Online ahead of print.

The significance of individual patient characteristics in a cohort of patients with inflammatory bowel disease treated with vedolizumab

Affiliations

The significance of individual patient characteristics in a cohort of patients with inflammatory bowel disease treated with vedolizumab

Nadža Zubčević et al. Med Glas (Zenica). .

Abstract

Aim: Care for the inflammatory bowel disease (IBD) patients presents unique challenges as decisions regarding therapy must consider numerous distinct characteristics of each patient. The aim of the study was to recognize patients' characteristics as predictors of success in vedolizumab treatment.

Methods: In a retrospective observational study, data regarding age, gender, body mass index (BMI), length of disease, previous exposure to anti-tumour necrosis factor (TNF), drugs, and smoking status were extracted from the routine clinical practice. Patients were assessed for clinical remission and steroid-free remission after the 26-week treatment with vedolizumab.

Results: The study included 76 patients with UC and 63 with CD. A total of 63 (out of 76; 82.9%) (Cl: 72.5-90.6% ) of UC and 54 (out of 63; 85.7%) (Cl: 74.6-93.3%) CD patients achieved clinical remission in the 26-week vedolizumab treatment. Over five years, illness was noticed in 32 (53.1%) CD patients. Clinical remission was not achieved in six (out of 13; 46.1%) UC patients aged 40-49 years and six (out of nine; 66.6%) CD patients aged 30-49 years. Among CD patients, remission was achieved in 22 (85.7%) females and 23 (63.6%) males. Remission rates were generally higher in patients with a BMI of 18.6-25 and 25.1-30. Previous exposure to anti TNF drugs and smoking status did not influence treatment outcomes.

Conclusion: The efficacy of vedolizumab is a viable treatment option for both ulcerative colitis and Crohn's disease. The exploration of individual patient characteristics holds promise in predicting a treatment outcome.

Keywords: biologic treatment; individual disease control; predicting treatment success.

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