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P413 A simple scoring tool predicts exposure–response relationship, onset of action, response to interval shortening, and surgical risk with vedolizumab therapy for Crohn’s disease

P. S. Dulai*1, A. Amiot2, L. Peyrin-Biroulet3, S. Singh1, M. Serrero4, V. Jairath5, J. Filippi6, B. Pariente7, E. V. Loftus Jr8, X. Roblin9, S. Kane8, A. Buisson10, C. A. Siegel11, Y. Bouhnik12, W. J. Sandborn1, K. Lasch13, M. Rosario13, B. G. Feagan5, D. Bojic14, C. Trang-Poisson15, B. Shen16, R. Altwegg17, B. E. Sands18, J-F. Colombel18, F. Carbonnel19, M. Bohm20, D. Hudesman21, A. Bourrier22, D. Lukin23, GETAID OBSERV-IBD and VICTORY Cohorts Collaboration1

1University of California San Diego, La Jolla, CA, USA, 2Henri Mondor University Hospital, Creteil, France, 3University of Lorraine, Nancy, France, 4Aix-Marseille University, Marseille, France, 5University of Western Ontario, London, ON, Canada, 6Nice University Hospital, Nice, France, 7Claude Huriez Hospital, Lille, France, 8Mayo Clinic, Rochester, MN, USA, 9University Hospital of Saint-Etienne, Saint-Etienne, France, 10Estaing University Hospital, Clermont-Ferrand, France, 11Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA, 12Beaujon Hospital, Clichy, France, 13Takeda Pharmaceuticals U.S.A., Inc., Deerfield, IL, USA, 14Takeda Pharmaceuticals International AG, Zurich, Switzerland, 15University Hospital of Nantes, Nantes, France, 16Cleveland Clinic Foundation, Cleveland, OH, USA, 17University Hospital of Montpellier Saint-Eloi, Montpellier, France, 18Icahn School of Medicine at Mount Sinai, New York, NY, USA, 19Bicetre University Hospital, Paris, France, 20Indiana University, Indianapolis, IN, USA, 21New York University (NYU), New York, NY, USA, 22Saint-Antoine University Hospital, Paris, France, 23Montefiore Medical Center, New York, NY, USA

Background

We previously created and validated a clinical decision support tool (CDST) for predicting response to vedolizumab (VDZ) in Crohn’s disease (CD). We now aim to further validate this tool in an additional CD cohort and assess its performance for predicting other health outcomes.

Methods

Using GEMINI II data, we explored correlations between VDZ exposure and onset of action across CDST-predicted probability of response groups (low, intermediate, high). The operating properties of the CDST for prediction of clinical remission and onset of action in the GETAID VDZ cohort were evaluated. In the GETAID and VICTORY cohorts, response to dose optimisation was assessed, and in the VICTORY cohort, we assessed the ability of the CDST to predict risk of surgery while on active therapy.

Results

A linear relationship was observed between CDST-predicted probability of response groups, VDZ exposure, onset of action, and efficacy in the GEMINI cohort for Week 2 through Week 52 (p < 0.001). In the GETAID cohort, the CDST predicted clinical remission at Week 14 (AUC 0.68), and a significant difference in speed of onset of action was observed between low- and intermediate–high-probability groups (p = 0.04). In both the GETAID and VICTORY cohorts, only patients in the low-probability group significantly benefited from shortening of VDZ intervals to Q4 weeks for non-response. In the GETAID cohort, a single infusion at Week 10 for patients in the low-probability group overcame differences in speed of onset of action seen between this group and the intermediate–high-probability group. In the VICTORY cohort, the CDST predicted a 2-fold increase in risk for surgery over 12 months of VDZ therapy among low–intermediate-probability patients compared with high-probability patients (HR 2.06, 95% CI 1.33–3.21).

Conclusion

The CD VDZ CDST demonstrated good performance during external validation in the GETAID cohort. This tool was able to prognosticate VDZ exposure-efficacy relationships and speed of onset of action, identify patients who would most benefit from interval shortening for lack of response, and stratify patients at greatest risk for surgery while on active therapy.