Lead Investigator: Neeraj Narula, Hamilton Health Sciences
Title of Proposal Research: Predictors of Mucosal Healing in Ulcerative Colitis: A Post-hoc Analysis of VARSITY
Vivli Data Request: 5945
Funding Source: None
Potential Conflicts of Interest: Neeraj Narula holds a McMaster University Department of Medicine Internal Career Award. Neeraj Narula has received honoraria from Janssen, AbbVie, Takeda, Pfizer, Merck, Lupin and Ferring.
Summary of the Proposed Research:
There is a need for predictor(s) of mucosal healing in patients with Inflammatory Bowel Disease (IBD), in particular with ulcerative colitis, to improve long-term patient outcomes. This study aims to identify possible early predictor(s) for mucosal healing in ulcerative colitis from the VARSITY trial, data accessed through VIVLI.
The participants include those subjects who participated in the VARSITY TRIAL. This study enrolled 771 people, of whom 769 received at least one dose of treatment, either vedolizumab (383 participants) or adalimumab (386 participants).
The proposed research is a post-hoc review of the VARSITY trial data to identify predictor(s) at baseline and week 14 for achieving mucosal healing at week 52 in the study.
The VARSITY trial was a randomized, double-blind, active-controlled trial with two medication treatment groups (vedolizumab or adalimumab) from July 2015 to January 2019 at 245 sites in 34 countries. Inclusion criteria included patients ages 18 to 85 with moderate to severe active ulcerative colitis. This post-hoc analysis aims to evaluate predictors of mucosal healing at week 52 utilizing data including clinical laboratory test results (i.e. fecal calprotectin, a biomarker measurement of inflammation), and a disease activity index for ulcerative colitis referred to as the Mayo scale that includes endoscopic scores evaluated by physicians utilizing imaging of endoscopic procedures read at a central location and patient reported outcomes (i.e stool frequency and rectal bleeding) from baseline and week 14.
Statistical Analysis Plan
The frequencies of the comparison groups will be analyzed with chi-square tests and the continuous variables will be compared with independent t-tests. The continuous variables will be analyzed accordingly to the type of data, for non-normally distributed data by Mann-Whitney U test where the variances are similar and by bootstrapped method where the assumption of equal variances is not statistically met. In addition, multivariate logistic regression analysis will be utilized to evaluate the association between baseline and week 14 endoscopic disease activity (measured by Mayo subscores), fecal calprotectin levels, histologic activity and patient reported symptoms including rectal bleeding and stool frequency at baseline, and achievement of mucosal healing at week 52. These associations will be adjusted with variables found to be significant on univariate analysis. Data will be accessed in a secure research environment protecting participant privacy.
A Randomized, Double-Blind, Double-Dummy, Multicenter, Active-Controlled Study to Evaluate the Efficacy and Safety of Vedolizumab IV Compared to Adalimumab SC in Subjects With Ulcerative Colitis
Study ID: NCT02497469
Sponsor ID: MLN0002-3026
- Narula, N., Wong, E., Colombel, J. F., Riddell, R., Marshall, J., Reinisch, W., & Dulai, P. (2021). DOP03 Early change in epithelial neutrophilic infiltrate predicts long-term response to biologics in Ulcerative Colitis. Journal of Crohn’s and Colitis, 15(Supplement_1), S042–S043. doi: 10.1093/ecco-jcc/jjab073.042
- Narula, N., Wong, E. C., Colombel, J. F., Riddell, R., Marshall, J. K., Reinisch, W., & Dulai, P. S. (2021). Early Change in Epithelial Neutrophilic Infiltrate Predicts Long-Term Response to Biologics in Ulcerative Colitis. Clinical Gastroenterology and Hepatology. Published. doi.org/10.1016/j.cgh.2021.07.005
- Wong ECL, Dulai PS, Narula N. Correspondence on “PICaSSO Histologic Remission Index (PHRI) in ulcerative colitis: development of a novel simplified histological score for monitoring mucosal healing and predicting clinical outcomes and its applicability in an artificial intelligence system” by Gui et al. Gut. 2022 Jun 7. gutjnl-2022-327661. doi: 10.1136/gutjnl-2022-327661