The Glaucoma and Retinopathy Screening Study

NCT06882356 | Recruiting

• 1 other identifier: 2024p003709
• Study Type: interventional
• Target: 2,000
• Locations: 1 country
• Sites: 5

Brief Summary

The goal of this clinical trial is to learn if a new screening approach including an artificial intelligence algorithm that analyzes fundus photographs, measurement of eye pressure and visual field testing works to screen for glaucoma. Participants will: Have an image of their fundus (back of the eye) taken as part of their diabetic eye screening Have a measurement of their eye pressure If needed, have a test of their side vision using a headset

Conditions

Glaucoma

Outcome Measures

Primary Outcomes (1)

• Glaucoma detection

  This primary outcome measure will assesses the proportion of participants who receive a glaucoma diagnosis in the combined DED and glaucoma screening group compared to the DED-only screening group. Glaucoma diagnosis in the intervention group is based on AI-assisted analysis of fundus photography, intraocular pressure, and virtual reality perimetry testing for confirmation.

  1 year from initial screening

Secondary Outcomes (3)

• Cost-Effectiveness of Combined Screening vs. DED-Only Screening

  1 year from initial screening

• Participant Satisfaction with Screening Process

  Day of screening

• Participant knowledge about glaucoma

  Day of screening

Study Arms (2)

Combined DED and Glaucoma Screening

EXPERIMENTAL

Participants in this arm will have fundus photographs that are taken as a part of standard clinical care analyzed by AI for signs of glaucoma in addition to for diabetic retinopathy. They will also have intraocular pressure measured. If the AI detects possible glaucoma, participants will undergo virtual perimetry testing for further assessment.

Device: AI-based glaucoma screening; Device: IOP measurement; Device: Virtual Reality Visual Field Testing

DED Screening Only (Control Arm)

NO INTERVENTION

Participants in this arm will undergo diabetic eye disease (DED) screening only for routine clinical care. This includes fundus photography for AI assessment of signs of diabetic retinopathy.

Interventions

AI-based glaucoma screening DEVICE

AI analysis of fundus photographs to detect signs of glaucoma, added to AI-based diabetic eye disease screening performed for routine clinical care

Combined DED and Glaucoma Screening

IOP measurement DEVICE

Intraocular pressure measurement by Icare tonometer

Combined DED and Glaucoma Screening

Virtual Reality Visual Field Testing DEVICE

Virtual Reality Visual Field Testing by the Olleyes device for participants suspected of having glaucoma

Combined DED and Glaucoma Screening

Eligibility Criteria

• Age: 40 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

* Individuals with diabetes undergoing AI-based screening for diabetic retinopathy using the LumineticsCore (Digital Diagnostics) system for clinical care at primary care centers. * Individuals who are able and willing to provide informed consent for participation in the study.

Contact the study team to discuss eligibility requirements. They can help determine if this study is right for you.

Sponsors & Collaborators

• Massachusetts Eye and Ear Infirmary: lead
• Centers for Disease Control and Prevention: collaborator

Study Sites (5)

Brigham and Women's Primary Care Associates of Longwood

Boston, Massachusetts, 02115, United States

RECRUITING

MGH Chelsea HealthCare Center

Chelsea, Massachusetts, 02150, United States

RECRUITING

NSPG Lynn

Lynn, Massachusetts, 01904, United States

RECRUITING

NSPG Salem

Salem, Massachusetts, 01970, United States

NOT YET RECRUITING

NSPG Saugus

Saugus, Massachusetts, 01906, United States

RECRUITING

MeSH Terms

Conditions

Glaucoma

Condition Hierarchy (Ancestors)

Ocular Hypertension; Eye Diseases

Study Officials

• David S Friedman, MD, PhD, MPH

  Massachusetts Eye and Ear

  PRINCIPAL INVESTIGATOR

Central Study Contacts

David S Friedman, MD, PhD, MPH

CONTACT

617-573-3094; grass@mgb.org

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: SCREENING
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Ophthalmology

Model Details: This study uses a prospective interventional model to evaluate the effectiveness of integrating AI-based glaucoma screening with existing diabetic eye disease (DED) screening among diabetic patients. Participants will have fundus images assessed by AI for glaucoma in addition to DED, and have intraocular pressure measurement measured. Suspected glaucoma cases will receive virtual perimetry testing for confirmation, and those diagnosed with glaucoma will be referred for follow-up care. This study aims to compare glaucoma detection rates between combined DED and glaucoma screening versus DED-only screening, ultimately supporting early glaucoma detection and enhancing care access in underserved communities.

Study Record Dates

• First Submitted: March 10, 2025
• First Posted: March 18, 2025
• Study Start: July 16, 2025
• Primary Completion (Estimated): September 1, 2030
• Study Completion (Estimated): September 1, 2030
• Last Updated: August 28, 2025

Record last verified: 2025-06

Data Sharing

• IPD Sharing: Will share
• Time Frame: After study completion
• Access Criteria: Data sharing will require adherence to Mass General Brigham institutional and IRB policies. External researchers will need to contact the Principal Investigator to request data and complete a Data Use Agreement. Only deidentified data will be shared.

Locations

US (5)