5PSQ-090 Impact of vedolizumab levels on clinical response in Crohn’s disease: a retrospective study

<h3>Background and Importance</h3> Therapeutic drug monitoring (TDM) is crucial for optimising vedolizumab treatment in inflammatory bowel disease patients. <h3>Aim and Objectives</h3> We aimed to evaluate how VDZ levels correlate with clinical response in patients with Crohn’s Disease (CD) and explore additional variables influencing treatment outcomes. <h3>Material and Methods</h3> We conducted a retrospective observational study of all CD patients at our hospital on VDZ maintenance treatment (≥14 weeks). Serum trough VDZ concentrations were analysed (ELISA method) along with demographic (age, sex) and clinical variables (age at diagnosis, location, disease pattern, biomarkers). Clinical response was assessed with the HBI index (remission &lt;5), and patients were classified as responders/non-responders. Samples were grouped using clustering (K-means), with time on treatment as the primary variable. Differences in VDZ levels between responders and non-responders were evaluated with Mann-Whitney, and predictive ability was assessed with ROC curves (without AUC, due to responder/non-responder imbalance). Logistic regression was used to identify other response-influencing variables. <h3>Results</h3> We included 70 measurements of trough serum concentrations of VDZ from 39 CD patients in the maintenance phase. Samples were grouped into 2 clusters. Cluster-1, with older patients (66.5±10.3 years) and longer on treatment (44.8±28.4 months), had a response rate of 78.1%. Responders had VDZ levels of 16.2 mcg/mL (IQR:12.1–20.7) versus 10.9 mcg/mL in non-responders (p=0.045). In Cluster-2, younger patients (45.7±12.4 years) with less time on treatment (18.8±16.6 months) had a response rate of 73.7%. Responders had 21.5 mcg/mL(IQR:15.6–30.55), while non-responders had 20.6 mcg/mL (IQR:10.8–27.35), with no significant differences (p=0.155). No ROC curve was performed in Cluster-2 due to lack of association between VDZ levels and response. In Cluster-1, sensitivity was 0.712 and precision 0.737, obtained from the ROC curve. Logistic regression identified age, VDZ levels, and time on treatment as key factors affecting treatment response. <h3>Conclusion and Relevance</h3> In Cluster-1, VDZ levels were significantly higher in responders, highlighting the importance of TDM in patients with longer treatment duration. The ROC curve showed moderate predictive ability (sensitivity=0.712, accuracy=0.737), though 30% of responders were not predicted by VDZ levels alone, suggesting other factors like pharmacodynamic variability or subclinical inflammation could influence response. Logistic regression identified age, VDZ levels, and time on treatment as key factors for clinical response. <h3>References and/or Acknowledgements</h3> <h3>Conflict of Interest</h3> No conflict of interest