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  string(1662) "Background

Inflammatory bowel disease (IBD) is a condition of chronic intestinal inflammation that contributes to significant morbidity and affects up to 3 million adults in the United States, with a growing global disease burden.1,2  However, to our knowledge, no studies to date have specifically evaluated treatment response in clinical trials based on race/ethnicity.

Objective

The purpose of this study is to determine if there is evidence of a differential response to biologic treatment in IBD based on race/ethnicity.

Study Design

We will conduct a pooled analysis of individual participant data from randomized controlled clinical trials of infliximab, golilumab and ustekinumab in IBD. We will compare outcomes between white patients and non-white IBD patients enrolled in these trials.

Participants

Biologic-treated IBD patients

Main Outcome Measure(s)

Primary outcome is clinical remission (defined by CDAI < 150 for Crohns disease or Mayo Clinical Score < 3 for UC).

Secondary outcomes are clinical response (CDAI decrease of 70 or 100 points for Crohns and decrease from baseline in the Mayo score by ? 30% and ? 3 points for UC) and mucosal healing (absence of ulcerations in Crohn?s and Mayo endoscopic sub-score of 0 or 1).

Statistical Analysis

Baseline characteristics will be summarized by frequency and mean/median. Statistical significance of baseline variables will be assessed using chi-square tests for categorical variables and ANOVA, t-tests for continuous variables. Outcome measures by ethnicity will be analyzed by multivariable logistic regression."
  ["project_brief_bg"]=>
  string(2806) "The inflammatory bowel diseases (IBD), ulcerative colitis (UC) and Crohns disease (CD), are conditions of chronic intestinal inflammation with increasing global incidence.1,2 Although the exact trigger of disease onset is yet unclear, the pathogenesis of IBD is thought to occur as a result of both environmental and genetic influences. For instance, factors such as breastfeeding, antibiotic use, and food additives have been implicated in exerting influence on the intestinal microbiome in a genetically predisposed individual thus triggering manifestations of IBD.2,3

Previous studies have described distinct IBD genotypic and phenotypic characteristics among different ethnic groups.4-6 For example, among individuals of European ancestry, NOD2 and IL23R are some of the more than 200 established loci of single nucleotide polymorphisms (SNPs) for Crohn?s disease. SNPs at ZNF649 and LSAMP have more recently been described to associate with UC among those of African ancestry, and other variant genetic mutations and susceptibility genes have been identified in Asian subpopulations.5,6 There is evidence of IBD phenotypic variation by ethnicity, for instance, with evidence of increased peri-anal involvement among individuals of African and Asian ancestry.7 There have also been disparities in clinical outcomes noted in IBD, with for example, higher rates of hospitalizations and complications among African American patients, although it is unclear if this difference is due to care patterns or underlying disease phenotype.8-11

Whether or not genotypic and phenotypic variations in IBD among different ethnic groups contribute to a differential response to IBD therapies is also unclear. Most studies of anti TNF biologics, for example, have included relatively few individuals of non-white/European ancestry and those studies that do look at ethnic differences tend to focus on the comparative use of various IBD medications or use of surgery. Whether or not differences in outcome pertain to different underlying disease processes rather than to external system or practice-based factors is an area of uncertainty. No study to our knowledge has specifically evaluated the efficacy of IBD therapies by ethnicity.

Knowledge of differential response to IBD medications based on racial/ethnic background may serve as an important component of personalizing the approach to treatment in an increasingly diverse population of IBD patients. In the absence of significant differences in response/remission rates in the controlled research setting of randomized control trials, differences in patient outcomes by ethnicity may point to other processes, such as health care systems, as opposed intrinsic differences in disease and drug response biology related to genetic background."
  ["project_specific_aims"]=>
  string(460) "Aim 1: Compare rates of induction and maintenance of clinical response and remission in CD/UC/IBD patients treated with biologic drugs (anti-TNF, infliximab, golimumab; anti-IL 12/23, ustekinumab) stratified by race/ethnicity.  

Aim 2: Compare rates of induction and maintenance of endoscopic remission in patients CD/UC/IBD patients treated with biologic drugs (anti-TNF, infliximab, golimumab; anti-IL 12/23, ustekinumab) stratified by race/ethnicity."
  ["project_study_design"]=>
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    ["label"]=>
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  string(250) "Inclusion: CD and UC patients in induction and maintenance RCTs  for biologic therapy. Adults (age 18 or older)

Exclusion: Insufficient data available to determine outcomes and/or primary variable of interest (race/ethnicity).  Age < 18 years."
  ["project_main_outcome_measure"]=>
  string(528) "Primary outcome will be clinical remission defined as Crohn?s disease activity index (CDAI) < 150 for CD or Mayo Clinical Score (MCS) < 3 for UC at end of induction and end of maintenance. This will be a dichotomous outcome. 

Secondary outcomes will include:

Clinical response (CDAI decrease of 70 or 100 points for CD or decrease from baseline in the MCS by ? 3 points and at least 30% from baseline for UC). 

Endoscopic healing (absence of ulcerations in CD and Mayo endoscopic sub-score of 0 or 1 in UC)."
  ["project_main_predictor_indep"]=>
  string(414) "Our primary predictor/independent variable will be race/ethnicity categorized as white versus non-white. Non-white patients will be defined as African, African-American, Black, Asian/Pacific Islander/SE Asian, Hispanic/Latino, or other non-white race. If sample size allows, we will look at specific non-white race/ethnicity groups including African/African American/Black, Asian, and Hispanic/Latino individually."
  ["project_other_variables_interest"]=>
  string(1144) "Other baseline variables of interest that will be included in our analysis include IBD type (UC or CD; categorical), peri-anal disease (categorical); disease duration (continuous), age (continuous), gender (categorical), disease location for CD and UC (categorical by Montreal classification), disease behavior for CD (categorical by Montreal classification), prior biologic use (categorical), smoking history (current versus former/never), baseline disease activity (continuous based on disease activity index, alternatively can categorize by pre-defined ranges for mild/moderate/severe disease), baseline albumin (continuous), baseline CRP (continuous), concomitant steroids at start of trial (categorical), concomitant immunomodulators at start of trial (categorical), extra-intestinal manifestations (categorical), dose of biologic (categorical), and trial design (induction vs. maintenance trial; categorical). We will also include individual study (categorical) as a variable to account for any differences between studies. Specific biologic studied will also be assessed (infliximab, golimumab, or ustekinumab as a categorical variable)."
  ["project_stat_analysis_plan"]=>
  string(1617) "Descriptive statistics will be performed using medians (interquartile range) and means (standard deviation) for continuous variables and proportions for categorical variables. Data distribution will be analyzed using Q-Q plots and the Shapiro-Wilk test. Continuous data between two groups will be analyzed using two-sample, non-paired t-tests for parametric data and the Wilcoxon rank-sum test for non-parametric data. To compare continuous data across more than two groups (for example, age across different non-white race/ethnicity subgroups), we will use ANOVA for parametric data and the Kruskal-Wallis test for non-parametric data. Categorical variables will be compared using chi-square or Fisher exact test where appropriate. 

We will first perform univariable analyses using logistic regression assessing the relationship between our covariables and the primary and secondary outcomes for all IBD patients. These outcomes will be stratified by induction versus maintenance studies (different regression models). We will also perform subgroup analyses based on disease type. We will first evaluate response to all biologics together and then by class (anti-TNF and anti-IL12/23). We will then construct multivariable models including those baseline characteristics with a p-value ?i 0.10 in the univariable analysis for the primary and secondary outcomes. We will a priori include baseline disease activity score, prior biologic exposure, and concomitant immunomodulator use in all multivariable models. All statistical tests will be two-sided with a p value < 0.05 considered statistically significant."
  ["project_timeline"]=>
  string(204) "Project Start Date: October 2018

Analysis Completion Date:  April 2019

Manuscript Submission:  May 2019

Publication Submission Date:  May 2019

Results Report to YODA: June 2019"
  ["project_dissemination_plan"]=>
  string(445) "We will disseminate results first in abstract form at national gastroenterology conferences, with target conference being Digestive Disease Week or Annual American College of Gastroenterology Meeting. We will then plan to submit a manuscript of the results to a peer-reviewed gastroenterology journal such as Gastroenterology, American Journal of Gastroenterology, Clinical Gastroenterology and Hepatology, or Inflammatory Bowel Disease Journal."
  ["project_bibliography"]=>
  string(2297) "
1. Nguyen GC, Chong CD, Chong RY. National estimates of the burden of inflammatory bowel disease among racial and ethnic groups in the United States. Journal of Crohn’s and Colitis 2014;8:288?295.

2. Kaplan GG, Ng SC. Understanding and Preventing the Global Increase of Inflammatory Bowel Disease. Gastro 2017; 152:313-321.

3. Ananthakrishnan AN. Environmental risk factors for inflammatory bowel diseases: a review. Dig Dis Sci. 2015;60(2):290-8

4. Liu JZ, van Sommeren S, Huang H, Ng SC, Alberts R, Takahashi A, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015;47(9):979-986.

5. Brant SR, Okou DT, Simpson CL, Cutler DJ, Haritunians T, Bradfield JP, et al. Genome-Wide Association Study Identifies African-Specific Susceptibility Loci in African Americans With Inflammatory Bowel Disease. Gastro 2017;152:206-217.

6. Ng SC, Tsoi KKF, Kamm MA, Xia B, Wu J, Chan FKL, et al. Genetics of Inflammatory Bowel Disease in Asia: Systematic Review and Meta-analysis. Inflamm Bowel Dis 2012; 18(6):1164-76.

7. Shi HY, Levy AN, Trivedi HD, Chan FKL, Ng SC, Ananthakrishnan AN. Ethnicity Influences Phenotype and Outcomes in Inflammatory Bowel Disease: A Systematic Review and Meta-analysis of Population-based Studies. Clinical Gastro Hep 2018; 16:190-197.

8. Sewell JL , Velayo FS. Systematic Review: The Role of Race and Socioeconomic Factors on IBD Healthcare Delivery and Effectiveness. Inflamm Bowel Dis 2013; (19)3: 627-643.

9. Dotson JL, Cho M, Bricker J, Kappelman MD, Chisolm DJ, Tomer G, et al. Race Differences in Initial Presentation, Early Treatment, and 1-year Outcomes of Pediatric Crohn’s Disease: Results from the ImproveCareNow Network. Inflamm Bowel Dis. 2017 May;23(5):767-774.

10. Barnes EL, Kochar B, Long MD, Pekow J, Ananthakrishnan A, Anyane-Yeboa A, et al. Lack of Difference in Treatment Patterns and Clinical Outcomes Between Black and White Patients With Inflammatory Bowel Disease. 2018 May 18. doi: 10.1093/ibd/izy179. [Epub ahead of print]

11. Ghazi et al. Racial Differences in Disease Activity and Quality of Life in Patients with Crohn?s Disease. Dig Dis Sci 2014; 59: 2508?2513.
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pi affil
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products
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