S2012 Advanced Therapies in IBD and Risk of Active Tuberculosis

Introduction: Advanced therapies (ATs), including tumor necrosis factor (TNF) inhibitors and non-TNF ATs—such as Janus kinase (JAK) inhibitors, integrin receptor antagonists, interleukin (IL) inhibitors, and sphingosine-1-phosphate (S1P) receptor modulators—are widely used in the treatment of inflammatory bowel disease (IBD). In the U.S., baseline and annual tuberculosis (TB) screening is universally required for insurance coverage of biologic and small molecule therapies, regardless of the actual risk. We aimed to evaluate the risk of active TB in IBD patients, stratified by AT type. Methods: We conducted a retrospective cohort study using TriNetX, a federated global research network comprising de-identified electronic health records from U.S. healthcare organizations. IBD patients were identified between January 2000 and January 2024. Patients were categorized into 3 cohorts: (1) those treated with TNF inhibitors, (2) those receiving non-TNF AT (JAK inhibitors, integrin receptor antagonists, IL inhibitors, or S1P receptor modulators), and (3) those naïve to AT. The primary outcome was active TB diagnosis (International Classification of Diseases-10 codes A15-19). Propensity score matching (1:1) was applied to adjust for demographics (age, sex, race) and clinical confounders (HIV infection, chronic kidney disease, nicotine dependence, corticosteroid use, chemotherapy, and autoimmune diseases). Adjusted odd’s ratios (aORs) with 95% confidence intervals (CIs) were calculated. Results: Among 102,019 IBD patients treated with AT and followed for a total of 357,066.5 patient-years, 280 were diagnosed with active TB compared to 90 cases in patients naïve to AT (aOR = 2.3; 95% CI: 1.8–2.9). Patients receiving TNF inhibitors (n = 63,560) had a significantly increased risk of active TB compared to AT–naïve patients (126 vs 65 cases; aOR = 1.9; 95% CI: 1.4–2.6). In contrast, patients on non-TNF AT (n = 31,369) did not demonstrate an increased active TB risk relative to their AT–naïve counterparts (24 vs 35 cases; aOR = 0.69; 95% CI: 0.4–1.1). In a direct comparison between TNF and non-TNF AT treated patients (n = 20,104 each), TNF inhibitor use was associated with a threefold higher risk of active TB (aOR = 3.0; 95% CI: 1.6–5.4). Conclusion: In this large, real-world cohort of IBD patients, TNF inhibitors were associated with a significantly increased risk of active TB, whereas non-TNF advanced therapies were not. These findings support a risk-stratified approach to TB screening based on the specific class of advanced therapy.

Publication Details

Journal
The American Journal of Gastroenterology
Published
2025-10-01
DOI
https://doi.org/10.14309/01.ajg.0001135508.06102.22
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

S2012 Advanced Therapies in IBD and Risk of Active Tuberculosis

The American Journal of Gastroenterology
Tuberculosis Research and Epidemiology
article

S2012 Advanced Therapies in IBD and Risk of Active Tuberculosis

article en

Abstract

Introduction: Advanced therapies (ATs), including tumor necrosis factor (TNF) inhibitors and non-TNF ATs—such as Janus kinase (JAK) inhibitors, integrin receptor antagonists, interleukin (IL) inhibitors, and sphingosine-1-phosphate (S1P) receptor modulators—are widely used in the treatment of inflammatory bowel disease (IBD). In the U.S., baseline and annual tuberculosis (TB) screening is universally required for insurance coverage of biologic and small molecule therapies, regardless of the actual risk. We aimed to evaluate the risk of active TB in IBD patients, stratified by AT type. Methods: We conducted a retrospective cohort study using TriNetX, a federated global research network comprising de-identified electronic health records from U.S. healthcare organizations. IBD patients were identified between January 2000 and January 2024. Patients were categorized into 3 cohorts: (1) those treated with TNF inhibitors, (2) those receiving non-TNF AT (JAK inhibitors, integrin receptor antagonists, IL inhibitors, or S1P receptor modulators), and (3) those naïve to AT. The primary outcome was active TB diagnosis (International Classification of Diseases-10 codes A15-19). Propensity score matching (1:1) was applied to adjust for demographics (age, sex, race) and clinical confounders (HIV infection, chronic kidney disease, nicotine dependence, corticosteroid use, chemotherapy, and autoimmune diseases). Adjusted odd’s ratios (aORs) with 95% confidence intervals (CIs) were calculated. Results: Among 102,019 IBD patients treated with AT and followed for a total of 357,066.5 patient-years, 280 were diagnosed with active TB compared to 90 cases in patients naïve to AT (aOR = 2.3; 95% CI: 1.8–2.9). Patients receiving TNF inhibitors (n = 63,560) had a significantly increased risk of active TB compared to AT–naïve patients (126 vs 65 cases; aOR = 1.9; 95% CI: 1.4–2.6). In contrast, patients on non-TNF AT (n = 31,369) did not demonstrate an increased active TB risk relative to their AT–naïve counterparts (24 vs 35 cases; aOR = 0.69; 95% CI: 0.4–1.1). In a direct comparison between TNF and non-TNF AT treated patients (n = 20,104 each), TNF inhibitor use was associated with a threefold higher risk of active TB (aOR = 3.0; 95% CI: 1.6–5.4). Conclusion: In this large, real-world cohort of IBD patients, TNF inhibitors were associated with a significantly increased risk of active TB, whereas non-TNF advanced therapies were not. These findings support a risk-stratified approach to TB screening based on the specific class of advanced therapy.

The American Journal of GastroenterologyVol. 120(10S2)
Openalex Percentile: Top 33%
Tuberculosis Research and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.