Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn's Disease

Parambir S. Dulai, Brigid S. Boland, Siddharth Singh, Khadija Chaudrey, Jenna L. Koliani-Pace, Gursimran Kochhar, Malav P. Parikh, Eugenia Shmidt, Justin Hartke, Prianka Chilukuri, Joseph Meserve, Diana Whitehead, Robert Hirten, Adam C. Winters, Leah G. Katta, Farhad Peerani, Neeraj Narula, Keith Sultan, Arun Swaminath, Matthew BohmDana Lukin, David Hudesman, John T. Chang, Jesus Rivera-Nieves, Vipul Jairath, G. Y. Zou, Brian G. Feagan, Bo Shen, Corey A. Siegel, Edward V. Loftus, Sunanda Kane, Bruce E. Sands, Jean Frederic Colombel, William J. Sandborn, Karen Lasch, Charlie Cao

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Background & Aims: As more treatment options for inflammatory bowel diseases become available, it is important to identify patients most likely to respond to different therapies. We created and validated a scoring system to identify patients with Crohn's disease (CD) who respond to vedolizumab. Methods: We collected data from the GEMINI 2 phase 3 trial of patients with active CD treated with vedolizumab for 26 weeks (n = 814) and performed logistic regression analysis to identify factors associated with clinical, steroid-free, and durable remission (derivation set). We used these data to develop a clinical decision support tool, which we validated using data from 366 participants in a separate clinical practice observational cohort of patients with active CD treated with vedolizumab for 26 weeks (the VICTORY cohort). We evaluated the ability of this tool to identify patients in clinical remission or corticosteroid-free remission, or those with mucosal healing (MH), clinical remission with MH, or corticosteroid-free remission with MH after vedolizumab therapy using receiver operating characteristic area under the curve (AUC) analyses. The primary outcome was to develop and validate a list of factors associated with achieving remission by vedolizumab in patients with active CD. Results: In the derivation analysis, we identified absence of previous treatment with a tumor necrosis factor antagonist (+3 points), absence of prior bowel surgery (+2 points), absence of prior fistulizing disease (+2 points), baseline level of albumin (+0.4 points per g/L), and baseline concentration of C-reactive protein (reduction of 0.5 points for values between 3.0 and 10.0 mg/L and 3.0 points for values >10.0 mg/L) as factors associated with remission. In the validation set, our model identified patients in clinical remission with an AUC of 0.67, patients in corticosteroid-free remission with an AUC of 0.66, patients with MH with an AUC of 0.72, patients in clinical remission with MH with an AUC of 0.73, and patients in corticosteroid-free clinical remission with MH with an AUC of 0.75. A cutoff value of 13 points identified patients in clinical remission after vedolizumab therapy with 92% sensitivity, patients in corticosteroid-free remission with 94% sensitivity, patients with MH with 98% sensitivity, patients with clinical remission and MH with 100% sensitivity, and patients with corticosteroid-free clinical remission with MH with 100% sensitivity. Conclusions: We developed and validated a scoring system to identify patients with CD most likely to respond to 26 weeks of vedolizumab therapy. Further studies are needed to optimize its accuracy in select populations and determine its cost-effectiveness.

Original languageEnglish (US)
Pages (from-to)687-695.e10
JournalGastroenterology
Volume155
Issue number3
DOIs
StatePublished - Sep 2018

Keywords

  • Biomarker
  • CD
  • IBD
  • Prediction Model

ASJC Scopus subject areas

  • Hepatology
  • Gastroenterology

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