P1047The Vedolizumab Clinical Decision Support Tool does not predict treatment response in Primary Sclerosing Cholangitis associated Inflammatory Bowel Disease (PSC-IBD)

Abstract Background PSC-IBD is a distinct entity differing from non-PSC IBD in its aetiology, distribution, symptom burden and response to treatment.1 Evidence regarding the effectiveness of advanced therapy in PSC-IBD is limited.2 The Vedolizumab Clinical Decision Support Tool (VDZ-CDST) is a validated prognostic scoring system predicting treatment response to vedolizumab, with iterations for Crohn’s disease (CD) and Ulcerative Colitis (UC).3,4 The accuracy of the VDZ-CDST in PSC-IBD is unknown. Methods We conducted a retrospective observational study of PSC-IBD patients receiving vedolizumab in a high-volume tertiary hospital. Clinical and mucosal (endoscopy or calprotectin if no endoscopy undertaken) responses were assessed against set criteria 12 months post-initiation. Clinical parameters underpinning VDZ-CDST scores were applied in multivariate logistic regression models to calculate prognostic capacity for mucosal response. Further modelling was used to identify predictors specific to PSC-IBD. Results Data was collected from 106 patients with PSC-IBD treated with vedolizumab. Of these, 87% were biologic naïve, and 57% commenced vedolizumab following liver transplantation. Pancolonic distribution predominated (64%). Excluding the 9 (8%) patients with an ileoanal pouch, rectal sparing was observed in 53% and small bowel involvement in 14%. Median treatment duration was 649 days (IQR 298 – 1276). In all, 57% achieved clinical remission at 12 months. However, only 16% attained remission by objective (biochemical and/or endoscopic) assessment and more than half (53%) of those in clinical remission had ongoing active inflammation. Given this disparity, mucosal response was determined as the outcome of interest. Excluding those with ileoanal pouches or incomplete outcome data, 78 patients contributed to the modelling. Clinical parameters underpinning the VDZ-CDST for UC and CD poorly identified those with mucosal non-response. A new model was constructed for PSC-IBD (Table 1). The top 5 baseline predictors of non-response in PSC were: previous liver transplant, moderate-severe histological activity, prior advanced therapy exposure, colonic disease only and lower haemoglobin levels. A multivariate logistic regression based on these 5 factors better predicted treatment failure (lack of mucosal response) than the UC (4 factors) or CD (5 factors) VDZ-CDST (Figure 1). Conclusion Existing tools perform poorly and cannot be applied to predict mucosal response to vedolizumab in PSC-IBD. Our data suggests that PSC-colitis patients who have moderate-severe histological activity post liver transplant, are unlikely to respond vedolizumab treatment . Future multicentre analysis may provide data on optimal biologic sequencing. References: 1. Horst LJ, Kempski J, Walmsley M, Huber S, Schramm C. PSC and colitis: A complex relationship. Hepatology. 2025;82(4):960-984. doi:10.1097/HEP.0000000000001236 2. Shah A, Jones MP, Callaghan G, et al. Efficacy and safety of biologics in primary sclerosing cholangitis with inflammatory bowel disease: A systematic review and meta-analysis. Hepatol Commun. 2024;8(1):e0347. Published 2024 Jan 11. doi:10.1097/HC9.0000000000000347 3. Dulai PS, Boland BS, Singh S, et al. Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn’s Disease. Gastroenterology. 2018;155(3):687-695.e10. doi:10.1053/j.gastro.2018.05.039 4. Dulai PS, Singh S, Vande Casteele N, et al. Development and Validation of Clinical Scoring Tool to Predict Outcomes of Treatment With Vedolizumab in Patients With Ulcerative Colitis. Clin Gastroenterol Hepatol. 2020;18(13):2952-2961.e8. doi:10.1016/j.cgh.2020.02.010 Conflict of interest: Morris, Sean: Nil Chandra-Segaran, Nimeshan: No conflicts Cooney, Rachel: I have received speaker fees from Abbvie, J&J, Takeda, Falk. I have received advisory fees from Abbvie, Celltrion, Lilly, and BMS. I have received support to attend meetings from Alfa-sigma, Lilly, J&J Iqbal, Tariq: Speaker fees from Pharmacosmos Trivedi, Palak: Nil Dr. Rimmer, Peter: I have received research funding from F. Hoffman La Roche. I have received educational grants from Abbvie and Johnson & Johnson. I have received speaker fees from Abbvie, Ferring, Johnson & Johnson and Takeda.