# Improving the Management of Rheumatoid Arthritis-Associated Lung Disease in Veterans Using Real-World Data

> **NIH VA IK2** · OMAHA VA  MEDICAL CENTER · 2024 · —

## Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting 1.3 million individuals in the U.S., causing
physical disability, reduced quality of life, premature mortality, and enormous health care costs. Veterans with
RA die from respiratory diseases at a rate three times higher than the general population. Much of this excess
respiratory mortality affecting Veterans with RA is attributable to interstitial lung disease (ILD), which has a
prognosis as poor as many cancers. Despite advances in RA treatment over the past two decades with the
adoption of novel therapies and more aggressive treatment strategies, the optimal management of RA-ILD is
unknown. Two critical limitations for effectively managing Veterans with RA-ILD are 1) the inability to identify
Veterans with progressive RA-ILD—those most likely to benefit from anti-fibrotic or aggressive
immunomodulatory therapies and 2) a lack of data on the comparative effectiveness and safety of disease-
modifying RA therapies in this population. Therefore, the overall objectives of this project are to leverage
unique prospective Veteran RA-ILD cohorts and data linkages within the Veterans Health Administration (VHA)
to 1) identify prognostic serum and genetic biomarkers for RA-ILD and 2) compare the effectiveness and safety
of RA therapies in Veterans with RA-ILD. Our central hypotheses are that serum and genetic biomarkers will
be independently associated with, and accurately predict, RA-ILD progression, and select RA therapies will
differentially slow ILD progression and improve related survival. In Aim 1, we will utilize prospective RA-ILD
cohorts to identify prognostic serum and genetic biomarkers and derive progressive RA-ILD predictive models.
We hypothesize that biomarkers from RA-ILD pathophysiologic domains—novel disease-related
autoantibodies, genetic markers, pro-inflammatory cytokines, and matrix metalloproteinases—will be
independently associated with ILD progression in Veterans with RA-ILD. In Aim 2, we will link national VHA
data sources and use advanced causal inference methodology to identify RA therapies that are associated
with less ILD progression and improved survival in Veterans with RA-ILD. We hypothesize that compared to
tumor necrosis factor inhibitors (TNFi), non-TNFi biologic therapies (rituximab, abatacept, and tocilizumab) will
be associated with less ILD progression and have a lower mortality risk in Veterans with RA-ILD. Impact: The
results from the proposed research will assist clinicians with personalized treatment selection in Veterans with
RA-ILD, a high-risk population with little data to currently guide treatment selection. The PI will complete this
research plan under the mentorship of a multidisciplinary team of experts in clinical and
pharmacoepidemiologic research within the VHA, building upon his early research productivity. The
accompanying mentored training program in pharmacoepidemiology and causal inference methodology
obtained through advanced, i...

## Key facts

- **NIH application ID:** 10909823
- **Project number:** 5IK2CX002203-04
- **Recipient organization:** OMAHA VA  MEDICAL CENTER
- **Principal Investigator:** Bryant R England
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2024
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2021-01-01 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10909823

## Citation

> US National Institutes of Health, RePORTER application 10909823, Improving the Management of Rheumatoid Arthritis-Associated Lung Disease in Veterans Using Real-World Data (5IK2CX002203-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10909823. Licensed CC0.

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