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Kuo BI, Wang TA, Chu TCC, Chan DC, Cheng SY, Tsai CT, Tsai CL, Lee YC, Chen CJ, Chen WL, Lee JT, Tsai CY, Liu PYT, Chang CY, Chao CT, Kao JH, Hsieh YT, the Collaborators of AI Ophthalmology Research Group
Artificial Intelligence–Assisted Screening for Patients With Diabetic Retinopathy and Age-Related Macular Degeneration in Family Medicine and Geriatric and Gerontology Care: Protocol for a Pragmatic Randomized Clinical Trial
Artificial Intelligence-Assisted Screening for Patients with Diabetic Retinopathy and Age-related Macular Degeneration in Family Medicine and Geriatric and Gerontology Care: Protocol for a Pragmatic Randomized Clinical Trial
Bo-I Kuo;
Ting-Ann Wang;
Teresa Cheng-Chieh Chu;
Ding-Cheng Chan;
Shao-Yi Cheng;
Chia-Ti Tsai;
Chu-Lin Tsai;
Yi-Chia Lee;
Chiuan-Jung Chen;
Wei-Li Chen;
John Tayu Lee;
Chia-Ying Tsai;
Patrick Yan-Tyng Liu;
Chi-Yang Chang;
Chia-Ter Chao;
Jia-Horng Kao;
Yi-Ting Hsieh;
the Collaborators of AI Ophthalmology Research Group
ABSTRACT
Background:
Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are two of the leading causes of vision loss worldwide. As population aging and diabetes prevalence increase, timely detection of these conditions has become essential. However, limited professionalism and insufficient training of ophthalmic screening in general medicine physicians may lead to delayed diagnosis and treatment. Artificial intelligence (AI)-assisted diagnostic tools may help to improve the screening of DR and AMD in the routine clinical practice.
Objective:
To evaluate the clinical effectiveness and cost-effectiveness of AI-assisted fundus imaging for DR and AMD screening in adults with diabetes and older adults at risk of macular degeneration.
Methods:
This multicenter, two-arm, parallel-group, open-label, individual-level randomized controlled trial and patient recruitment is performed at the settings of Family Medicine and Geriatric and Gerontology Care over four medical centers in Taiwan. Eligibility includes (1) diabetic individuals aged 20 years or more for DR screening, and (2) individuals aged 50 years or more for AMD screening. The study protocol has been approved by the ethics committees of all participating hospitals, and all participants will provide written informed consent.
Results:
The study was funded in September 2024, began on October 2, 2025, and is expected to be completed in December 2027. After the pilot implementation phase without randomization, participants will be randomized 1:1 into two groups: (1) AI-assisted screening and (2) usual physician-only screening. The primary outcomes included the detection rates (defined as participants with confirmed DR or AMD among all screened participants) and the positive predictive values (defined as participants with confirmed DR or AMD among those who tested positive). Cost-effectiveness analyses will be performed using data derived from the trial results.
Conclusions:
This study will provide robust evidence on the effectiveness of AI-assisted ophthalmic screening in improving patient eye health outcomes through timely screening and accurate early detection. This strategy may be cost-effective. Clinical Trial: ClinicalTrials.gov: NCT07069647
Citation
Please cite as:
Kuo BI, Wang TA, Chu TCC, Chan DC, Cheng SY, Tsai CT, Tsai CL, Lee YC, Chen CJ, Chen WL, Lee JT, Tsai CY, Liu PYT, Chang CY, Chao CT, Kao JH, Hsieh YT, the Collaborators of AI Ophthalmology Research Group
Artificial Intelligence–Assisted Screening for Patients With Diabetic Retinopathy and Age-Related Macular Degeneration in Family Medicine and Geriatric and Gerontology Care: Protocol for a Pragmatic Randomized Clinical Trial