Precision Medicine in Inflammatory Bowel Disease

Educational Objectives

The goal of this program is to improve use of precision medicine in inflammatory bowel disease (IBD). After hearing and assimilating this program, the clinician will be better able to:

1. Optimize use of infliximab in ulcerative colitis.
2. Differentiate among drug classes in effectiveness for treatment of significant colonic disease in Crohn disease.

Summary

Introduction: most drugs for inflammatory bowel disease (IBD) only have response rates of 40% to 45%; most patients are likely go through a sequence of ineffective treatments before finding a drug that facilitates remission; this incurs significant direct and indirect costs; under the current treatment paradigm, several factors are considered when identifying a treatment, eg, symptoms, disease severity, prognostic factors, treatment efficacies from randomized control trials (RCTs), cost and coverage, adverse effects, and the route of administration; however, these factors do not predict an individual’s response to treatment

Predictors of response: response to anti-tumor necrosis factor (TNF) therapy decreases with increasing severity of the disease; early treatment, combination treatment, and optimized trough levels for biologics help patients respond better; Vande Casteele et al (2021) — a tool combining baseline infliximab clearance (defined using albumin level and patient sex), stool frequency, and rectal bleeding at the time of initiating treatment helped predict the week-8 endoscopic response to infliximab for ulcerative colitis (UC); eg, patient with albumin level of 4 g/dL, stool frequency subscore of 1, and rectal bleeding subscore of 1 has 86% probability of response to drug; patient with, eg, albumin level 2.5 g/dL, stool frequency subscore of 2, and rectal bleeding subscore of 3 had 11% probability of response; and individual patient data can inform the probability of response to the drug

Using treatment journey to assess efficacy: there may be a difference in drug efficacy between biologic-naive vs biologic-exposed patients; eg, ozanimod may have lower efficacy in patients who are biologic-exposed, whereas there may not be a significant difference with Janus kinase (JAK) inhibitors; however, there is a lack of mechanism-specific clinical predictors for individual biologics; if a patient has multiple predictors indicating that they may not respond to a particular drug, assess response early and optimize or change the drug if it is not effective

Clinical decision support tools: Meserve et al (2020) — used data from the GEMINI trial for vedolizumab and developed a model for predicting response to vedolizumab based on the duration of UC, prior biologic use, severity of endoscopic activity at treatment initiation, and baseline albumin; using the decision support tool for vedolizumab and then assessing the results of, eg, the VARSITY trial (Sands et al [2019]) that compared vedolizumab with adalimumab, may help clinicians compare the 2 drugs; Narula et al (2022) — compared the efficacy of adalimumab, infliximab, ustekinumab, and vedolizumab for Crohn disease (CD); anti-TNF agents were associated with a superior response in patients with large ulcers and significant colonic disease

Drug safety: Cheng et al (2022) — in an individual with comorbidity, there was a significant safety benefit to using ustekinumab over anti-TNFs; no difference was observed in individuals without comorbidities

Biomarkers: UK study of oncostatin M (OSM) — authors showed cluster of genes in colon (primarily OSM) predicted response to anti-TNF therapy in patients with IBD; patients with high expression of OSM were refractory to anti-TNF therapy whereas those with low OSM expression responded well (West et al [2017]); triggering receptor expressed on myeloid cells 1 (TREM1) — Verstockt et al (2019) studied this serum biomarker that is also expressed in intestinal tissue; there was no difference in its expression with vedolizumab or ustekinumab use, but baseline TREM1 was downregulated in future anti-TNF responders; intestinal gene expression can help clinicians decide between different treatments

Microbiome: critically important in propagating inflammation in IBD and can be used to determine treatment choice; certain microbial features lend themselves to a better response to one treatment vs another; Lee et al (2021) — for individuals with the specific microbial phenotype Dirichlet multinomial mixture 1 (DMM-1), there was a substantial difference in response rates with anti-TNF therapy (more effective) compared with vedolizumab

Sazonovs et al (2020): in the PANTS study, the presence of specific genetic variants in patients with CD was associated with a higher likelihood of developing anti-drug antibodies to infliximab and adalimumab; thus, combination therapy should be preferentially used for patients with this genetic predisposition, and anti-TNF monotherapy can be used for patients without the variants

Predicting adverse events: certain genes predict, eg, thiopurine-induced pancreatitis (TIP) and thiopurine-induced myelosuppression (TIM); profiling for these genes can help guide decision-making

Personalized drug dosing: uses patient demographics, drug clearance, trough levels, and laboratory data to guide subsequent dosing; micromanaging at the level of an individual dose is expected in the future; Al-Talib et al (2023) showed that ≈50% of patients were able to deescalate their dose without losing clinical response using the precision medicine-guided approach (cost saving)

Tools: currently available — clinical prognostic tools and omic markers for adverse events (ie, TIP, TIM, immunogenicity to anti-TNF agents); near future — clinical tools that determine which treatment will be effective (models still need to be validated); precision drug dosing; longer-term future — omic markers to predict therapeutic response and to choose between drugs; some markers are modifiable (eg, microbiome); some patients can safely stop treatment, but there is no current way to determine who does not need long-term treatment; precision medicine may someday be able to determine which patients need medication vs surgery and which environmental factors are important for each patient

Readings

Al-Talib I, Iqbal M, Shaheen S, et al. P60 De-escalation of biological therapy in Inflammatory bowel disease (IBD) and outcomes at week 52: A single centre experience. Gut. 2023;72(Suppl 2):A78-A78. doi:https://doi.org/10.1136/gutjnl-2023-BSG.132; Cheng D, Kochar B, Cai T, et al. Comorbidity influences the comparative safety of biologic therapy in older adults with inflammatory bowel diseases. Am J Gastroenterol. 2022;117(11):1845-1850. doi:10.14309/ajg.0000000000001907; Lee JWJ, Plichta D, Hogstrom L, et al. Multi-omics reveal microbial determinants impacting responses to biologic therapies in inflammatory bowel disease. Cell Host Microbe. 2021;29(8):1294-1304.e4. doi:10.1016/j.chom.2021.06.019; Macaluso FS, Maida M, Grova M, et al. Head-to-head comparison of biological drugs for inflammatory bowel disease: From randomized controlled trials to real-world experience. Therap Adv Gastroenterol. 2021;14:17562848211010668. Published 2021 May 3. doi:10.1177/17562848211010668; Meserve J, Dulai P. Predicting response to vedolizumab in inflammatory bowel disease. Front Med (Lausanne). 2020;7:76. Published 2020 Apr 2. doi:10.3389/fmed.2020.00076; Narula N, Wong ECL, Dulai PS, et al. Comparative effectiveness of biologics for endoscopic healing of the ileum and colon in Crohn's disease. Am J Gastroenterol. 2022;117(7):1106-1117. doi:10.14309/ajg.0000000000001795; Sands BE, Peyrin-Biroulet L, Loftus EV Jr, et al. Vedolizumab versus adalimumab for moderate-to-severe ulcerative colitis. N Engl J Med. 2019;381(13):1215-1226. doi:10.1056/NEJMoa1905725; Sazonovs A, Kennedy NA, Moutsianas L, et al. HLA-DQA1*05 carriage associated with development of anti-drug antibodies to infliximab and adalimumab in patients With Crohn's disease. Gastroenterology. 2020;158(1):189-199. doi:10.1053/j.gastro.2019.09.041; Vande Casteele N, Jairath V, Jeyarajah J, et al. Development and validation of a clinical decision support tool that incorporates pharmacokinetic data to predict endoscopic healing in patients treated with infliximab. Clin Gastroenterol Hepatol. 2021;19(6):1209-1217.e2. doi:10.1016/j.cgh.2020.04.078; Verstockt B, Verstockt S, Dehairs J, et al. Low TREM1 expression in whole blood predicts anti-TNF response in inflammatory bowel disease. EBioMedicine. 2019;40:733-742. doi:10.1016/j.ebiom.2019.01.027; Weizman AV, Nguyen GC, Seow CH, et al. Appropriateness of biologics in the management of Crohn's disease using RAND/UCLA appropriateness methodology. Inflamm Bowel Dis. 2019;25(2):328-335. doi:10.1093/ibd/izy333; West NR, Hegazy AN, Owens BMJ, et al. Oncostatin M drives intestinal inflammation and predicts response to tumor necrosis factor-neutralizing therapy in patients with inflammatory bowel disease [published correction appears in Nat Med. 2017 Jun 6;23 (6):788]. Nat Med. 2017;23(5):579-589. doi:10.1038/nm.4307.

Disclosures

For this program, members of the faculty and planning committee reported nothing relevant to disclose.

Acknowledgements

Dr. Ananthakrishnan was recorded at the 16th Annual Inflammatory Bowel Disease: The Art and Science in the Diagnosis and Treatment 2023, held on September 8, 2023, in Boston, MA, and presented by the Boston University Chobanian and Avedisian School of Medicine. For information on upcoming CME activities from this presenter, please visit Cme.bu.edu. Audio Digest thanks the speakers and presenters for their cooperation in the production of this program.

CME/CE INFO

Accreditation:

The Audio- Digest Foundation is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The Audio- Digest Foundation designates this enduring material for a maximum of 0.75 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Audio Digest Foundation is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's (ANCC's) Commission on Accreditation. Audio Digest Foundation designates this activity for 0.75 CE contact hours.

Lecture ID:

GE381202

Expiration:

This CME course qualifies for AMA PRA Category 1 Credits™ for 3 years from the date of publication.

Instructions:

To earn CME/CE credit for this course, you must complete all the following components in the order recommended: (1) Review introductory course content, including Educational Objectives and Faculty/Planner Disclosures; (2) Listen to the audio program and review accompanying learning materials; (3) Complete posttest (only after completing Step 2) and earn a passing score of at least 80%. Taking the course Pretest and completing the Evaluation Survey are strongly recommended (but not mandatory) components of completing this CME/CE course.

Estimated time to complete this CME/CE course:

Approximately 2x the length of the recorded lecture to account for time spent studying accompanying learning materials and completing tests.