P0745Association of Early Vedolizumab Trough Levels with Clinical, Biochemical, Endoscopic Response and Drug Optimization During Maintenance Therapy in Patients with Inflammatory Bowel Diseases

Abstract Background Data on the association between vedolizumab (VDZ) trough levels (VTLs) and clinical, biochemical, and endoscopic outcomes in Asian patients with inflammatory bowel disease (IBD) are limited. Methods We assessed clinical outcomes, biochemical response using faecal calprotectin (BioRESFC) or C-reactive protein (BioRESCRP), and endoscopic healing (EH) at weeks 14 (W14) and W54 together with drug optimisation during maintenance therapy among 67 patients treated with VDZ (28 ulcerative colitis UC and 39 Crohn’s disease CD). Serum VTLs were checked before infusion at W2, W6, W14, and W54 among the patients who maintained VDZ therapy. Associations between early VTLs and outcomes were assessed, with VTL cut-offs proposed using the area under the receiver operating curve (AUC). Results 1) UC: VTL at W2 was significantly higher among W14 corticosteroid-free clinical response (CSF-CRES) achievers vs. non-achievers (43.1 vs. 34.4 μg/mL, P = 0.034) (Figure 1). Patients who achieved W14 BioRESFC had higher VTLs at W2, W6, and W14 compared to non-achievers. VTLs at W2 and W6 were significantly higher among patients who achieved W14 EH (42.4 vs. 31.2 μg/mL, P = 0.040 at W2, and 41.6 vs. 28.7 μg/mL, P = 0.035 at W6). The cut-off value of W2 VTL to predict W14 CSF-CREM was 41.0 μg/mL, with an AUC of 0.810 (95% CI, 0.604–1.000). The optimal VTL cut-offs at W2, W6 and W14 associated with W14 BioRESFC were 41.0 μg/mL with an AUC of 0.815 (95% CI, 0.636–0.994), 31.3 μg/mL with an AUC of 0.874 (95% CI, 0.733–1.000), and 9.8 μg/mL with an AUC of 0.849 (95% CI, 0.692–1.000), respectively. The predictive VTL cut-offs associated with W14 EH were 41.0 μg/mL with an AUC of 0.739 (95% CI, 0.527–0.951) at W2 and 38.1 μg/mL with an AUC of 0.744 (95% CI, 0.540–0.949) at W6. 2) CD: Higher VTLs at W6 and W14 were observed in those who achieved W14 BioRESCRP (Figure 2). Additionally, VTL at W14 was significantly higher among those who achieved W54 BioRESFC compared to non-responders (11.2 vs. 3.8 μg/mL, P = 0.036). VTLs at W14 were significantly lower in those who required drug optimisation compared to those who did not (2.2 vs. 5.8 μg/mL, P = 0.004). The optimal VTL cut-offs for predicting W14 BioRESCRP were 19.1 μg/mL at W6 and 4.4 μg/mL at W14, with corresponding AUC values of 0.733 (95% CI, 0.539–0.928) and 0.739 (95% CI, 0.539–0.948), respectively. The optimal VTL cut-off for predicting W54 BioRESFC was 5.3 μg/mL at W14, with an AUC of 0.859 (95% CI, 0.730–0.988). The optimal VTL cut-offs to predict drug optimisation was 4.6 μg/mL at W14, with an AUC of 0.765 (95% CI, 0.613–0.917). Conclusion This real-life study suggests higher early VTLs correlated with better outcomes, with W14 VTLs potentially predicting long-term outcomes in CD patients. Conflict of interest: Prof. Dr. Ye, Byong Duk: Byong Duk Ye reports consulting fees from AbbVie Korea, BMS Pharmaceutical Korea Ltd., Celltrion, Chong Kun Dang Pharm, CJ Red BIO, Curacle, Daewoong Pharm, Dong-A ST, Ferring Korea, Hanmi Pharmaceutical, Imscout, IQVIA, Johnson & Johnson, Johnson & Johnson Korea, Jeil Pharmaceutical Co., Kangstem Biotech, Korea Otsuka Pharm, Korea United Pharm, Lilly Korea, Medtronic Korea, NanoEntek, ORGANOIDSCIENCES Ltd., Pfizer Korea, Samsung Bioepis, Takeda, Takeda Korea and Yuhan speaker fees from AbbVie Korea, BMS Pharmaceutical Korea Ltd., Celltrion, Cornerstones Health, Curacle, Daewoong Pharm, Eisai Korea, Ferring Korea, IQVIA, Johnson & Johnson Korea, Pfizer Korea, Samsung Bioepis, and Takeda Korea and research support from Celltrion and Pfizer Korea. Kim, Kyuwon: No conflict of interest Yoon, Aran: No conflict of interest Hong, Seung Wook: No conflict of interest Hwang, Sung Wook: no conflicts Park, Sang Hyoung: No conflicts Yang, Dong-Hoon: No conflict of interest Byeon, Jeong-Sik: Clinical study grants from Olympus Co, GC genome, Pharmbio Korea Inc, and Taejoon Pharm. Clinical studies related to the grants include artificial intelligence endoscopy for colon polyp detection/diagnosis, cfDNA for colorectal cancer screening, and colonoscopy bowel preparation. I am a medical advisor of AINEX corporation, Korea, which is an AI endoscopy company. Myung, Seung-Jae: No conflict of interest