Analysis of DR Progression to Identify Risks and Need for Treatment

Overview

The goal of this observational study is to understand whether vascular and structural changes in the eyes caused by diabetes can help predict which people are more likely to experience worsening diabetic retinopathy (a diabetes-related eye disease) and how these eye changes are related to cardiovascular complications. The study will include about 1,000 people with type 2 diabetes, aged 35 to 90 years, and will take place over twelve months. It may also include a retrospective component, where existing medical and imaging data collected from previous visits (within the last 1 to 5 years) will be analyzed. The main questions it aims to answer are: * Can eye vessel and tissue changes, observed through modern imaging techniques and clinical data, help better describe and predict which cases of diabetic retinopathy will become more severe? * Can these same eye changes help predict the presence and risk of cardiovascular problems-such as heart disease or stroke-in people living with type 2 diabetes?

Detailed description

Diabetic Retinopathy (DR) is a leading cause of vision loss in adults with type 2 diabetes (T2D) and is associated with systemic complications, including cardiovascular disease. Early identification of patients at high risk of DR progression and cardiovascular events is critical to optimizing clinical management. Retinal imaging biomarkers, combined with clinical and demographic data, provide an opportunity to better understand disease mechanisms, predict progression of DR and associated cardiovascular complications, and guide personalized interventions.

The aim of this study is to investigate the influence of central versus peripheral retinal lesions on DR progression and staging, characterize associations between retinal biomarkers and cardiovascular risk factors and major adverse cardiovascular events (MACE), and contribute to the understanding of pathophysiological mechanisms underlying DR in T2D patients. The study will also generate a high-quality, harmonized database to support the development of artificial intelligence (AI) models.

This study aims to determine the extent to which central and peripheral retinal lesions, together with quantitative imaging biomarkers, contribute to the progression and staging of DR and the occurrence of cardiovascular complications in patients with T2D. Additionally, in the scope of the ALERT project (supported by Fundação para Ciência e Tecnologia (FCT); COMPETE2030-FEDER-00921900), the data of this clinical study will be used to create a harmonized, high-quality database for the development of exploratory interpretable artificial intelligence models for predicting DR progression and stage as well as predict the values of cardiovascular risk factors, and the risk of developing cardiovascular complications.

Primary outcome measures

• Change in Diabetic Retinopathy Staging [Time frame: Baseline to 12 months]
• Diabetic Retinopathy (DR) Progression, measured on the OPTOS Ultra-widefield Fundus Photography (UWF-FP) [Time frame: Baseline to 12 months]
• Proportion of participants with ≥15-letter loss in ETDRS Best-Corrected Visual Acuity (BCVA) [Time frame: Baseline to 12 months]
• Incidence of Major Adverse Cardiovascular Events (MACE) [Time frame: Baseline to 12 months]

Secondary outcome measures (12)

• Number of microaneurysms in the central ETDRS area (90°) [Time frame: Baseline to 12 months]
• Number of microaneurysms in the peripheral retina (90-200°) [Time frame: Baseline to 12 months]
• Presence of hemorrhages in the central ETDRS area [Time frame: Baseline to 12 months]
• Presence of peripheral retinal hemorrhages (90-200°) [Time frame: Baseline to 12 months]
• Presence of exudates in the retina [Time frame: Baseline to 12 months]
• Presence of cotton wool spots in the retina [Time frame: Baseline to 12 months]
• Correlation between retinal microaneurysm count and glycated hemoglobin (HbA1c) [Time frame: Baseline to 12 months]
• Retinal vessel density [Time frame: Baseline to 12 months]
• Correlation between retinal vessel density and systolic blood pressure [Time frame: Baseline to 12 months]
• Abnormal intercapillary spaces (AIS) in the retina [Time frame: Baseline to 12 months]
• Correlation between abnormal intercapillary spaces (AIS) and major adverse cardiovascular events (MACE) [Time frame: Baseline to 12 months]
• Retinal venous calibre [Time frame: Baseline to 12 months]

Eligibility criteria

Inclusion criteria

• Diagnosed with type 2 diabetes according to the 1985 WHO criteria.
• Age between 35 and 90 years.
• Retrospective visit or referenced patients. For the retrospective visit, a documented follow-up of 1-5 years is required, with at least one clinical visit. For the referenced patients, it is required that they have either diabetic retinopathy at the baseline visit, the presence of at least one cardiovascular risk factor at the baseline visit, or cardiovascular complications at the baseline visit.
• Signed informed consent.

Exclusion criteria

• Previous laser photocoagulation or intravitreal injections (consider if corticosteroids were administered).
• Presence of clinically significant macular edema (CSME) with vision loss or requiring immediate treatment.
• Proliferative diabetic retinopathy.
• Any ocular surgery within the previous 3 months.
• Renal Replacement Therapy (Hemodialysis, Peritoneal Dialysis).
• Severe systemic illness, subject to investigator's judgment.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model

Cohort

Study locations

Portugal · 1 center

• AIBILI-Clinical Trial Centre — Portugal

Publications

• Cunha-Vaz J, Mendes L. Characterization of Risk Profiles for Diabetic Retinopathy Progression. J Pers Med. 2021 Aug 23;11(8):826. doi: 10.3390/jpm11080826. PMID 34442470
• Marques IP, Madeira MH, Messias AL, Santos T, Martinho AC, Figueira J, Cunha-Vaz J. Retinopathy Phenotypes in Type 2 Diabetes with Different Risks for Macular Edema and Proliferative Retinopathy. J Clin Med. 2020 May 12;9(5):1433. doi: 10.3390/jcm9051433. PMID 32408522
• Santos AR, Almeida AC, Rocha AC, Reste-Ferreira D, Marques IP, Cunha-Vaz Martinho A, Mendes L, Santos T, Lewis W, Cunha-Vaz J. CENTRAL AND PERIPHERAL INVOLVEMENT OF THE RETINA IN THE INITIAL STAGES OF DIABETIC RETINOPATHY. Retina. 2024 Apr 1;44(4):700-706. doi: 10.1097/IAE.0000000000004021. PMID 38109709
• Sato Y, Lee Z, Hayashi Y. Subclassification of preproliferative diabetic retinopathy and glycemic control: relationship between mean hemoglobin A1C value and development of proliferative diabetic retinopathy. Jpn J Ophthalmol. 2001 Sep-Oct;45(5):523-7. doi: 10.1016/s0021-5155(01)00380-x. PMID 11583677
• Silva PS, Cavallerano JD, Haddad NM, Kwak H, Dyer KH, Omar AF, Shikari H, Aiello LM, Sun JK, Aiello LP. Peripheral Lesions Identified on Ultrawide Field Imaging Predict Increased Risk of Diabetic Retinopathy Progression over 4 Years. Ophthalmology. 2015 May;122(5):949-56. doi: 10.1016/j.ophtha.2015.01.008. Epub 2015 Feb 19. PMID 25704318
• IDF Diabetes Atlas 9th edition. (2019). IDF Diabetes Atlas 9th edition 2019. In International Diabetes Federation Diabetes Atlas, Ninth Edition.
• Marques, I., Mendes, L., & Cunha-Vaz, J. (2018). Noninvasive Multimodal Imaging of Diabetic Retinopathy (pp. 88-101). https://doi.org/10.1159/000487414

Identifiers

NCT: NCT07417410 · 4C-2025-16

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗