# Identifying Protective and Risk Factors for Non-infectious Uveitis

> **NIH NIH R21** · MASSACHUSETTS EYE AND EAR INFIRMARY · 2020 · $205,802

## Abstract

Project Summary/Abstract
Background Information and Relevance: Uveitis is an important cause of permanent vision loss that affects
younger patients. Despite the human and economic impact of this disease, the risk factors for non-infectious
uveitis are poorly understood. This is in part because epidemiologic studies of uveitis have been limited by
insufficient numbers of participants. Newly available large health care claims databases provide an opportunity
to increase the ability to detect uveitis risk factors. Hypotheses: Metformin, statin, angiotensin converting
enzyme inhibitors are associated with a lower incidence of non-infectious uveitis, while female hormonal
therapies are associated with a higher incidence of non-infectious uveitis. Specific Objectives: 1. To determine
if non-infectious uveitis incidence varies in relation to putative protective medications, including metformin,
statins and angiotensin converting enzyme inhibitors. 2. To determine if non-infectious uveitis incidence varies
in relation the modifiable risk factor of female hormonal therapy, including hormonal replacement therapy and
hormonal contraceptive therapy. Methods: The Clinformatics™ Data Mart Database contains medical claims
on over 60 million beneficiaries from a large insurer in the United States. We will define non-infectious uveitis
based on validated diagnosis codes recorded by an eye care provider twice within a 120-day period and
exclusion of infectious or surgical causes of uveitis with diagnosis and procedural codes. Potential
confounders including demographic (age, gender, race/ethnicity, education level, financial net worth) and
clinical (smoking exposure) covariate information will be extracted from the database. Medication exposure
will be rigorously captured based on the filling of outpatient prescriptions or coding of clinic-administered
therapies. The cohort not exposed to the medication will be matched on age (±3 years), race/ethnicity, sex and
date of plan entry and exit (±3 months) to the medication-exposed cohort. Propensity scores for each
medication exposure will be estimated using multivariable logistic regression and the rich information on
comorbid conditions and treatments available in the database. With multivariable Cox proportional hazards
regression, we will calculate the hazard ratios for incident non-infectious uveitis based on exposure to each of
the medications listed above. To account for the possibility of systematic differences between individuals with
and without the exposures of interest, the Cox proportional hazards models will be weighted by the inverse of
the predicted probability of their observed exposures using the propensity scores. We will interpret the results
taking into the account the multiple comparisons being tested. Implications: The well-powered, rigorous
analyses proposed here offer a unique opportunity to identify novel modifiable protective and risk factors for
non-infectious uveitis, guide practice pattern...

## Key facts

- **NIH application ID:** 9850573
- **Project number:** 5R21EY029851-02
- **Recipient organization:** MASSACHUSETTS EYE AND EAR INFIRMARY
- **Principal Investigator:** Lucia Sobrin
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $205,802
- **Award type:** 5
- **Project period:** 2019-02-01 → 2021-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9850573

## Citation

> US National Institutes of Health, RePORTER application 9850573, Identifying Protective and Risk Factors for Non-infectious Uveitis (5R21EY029851-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9850573. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*