Journal of Ocular Biology
Research Article
Custom-Designed Approach to Treatment with Algorithms (C-DATA) for Diabetic Macular Edema
Yaghy A and Jabbour NM
1Department of Ophthalmology and Visual Sciences, University of
Massachusetts Chan Medical School, Worcester, MA, USA
2West Virginia University Eye Institute
3Mid-Atlantic Retina Consultations
4ForSight Foundation
2West Virginia University Eye Institute
3Mid-Atlantic Retina Consultations
4ForSight Foundation
*Address for Correspondence:Nabil M. Jabbour, Department of Ophthalmology, West Virginia University Eye Institute, USA. Email Id: nnjabbour@gmail.com
Submission: 26-April-2025
Accepted: 09-May-2025
Published: 12-May-2025
Copyright: © 2025 Yaghy A, et al. This is an open access article
distributed under the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Keywords:Diabetic Macular Edema; Custom-Designed Treatment Algorithm
(C-DATA); Anti-VEGF Therapy; Intravitreal Injections; Personalized
Medicine
Abstract
Objective: To evaluate the efficacy of a custom-designed
approach to treatment with algorithms (C-DATA) for diabetic macular
edema (DME) compared to established published protocols.
Design: Prospective, comparative clinical study.
Subjects: 33 patients with DME, contributing to 49 distinct eyes treated.
Methods: Patients were treated according to the C-DATA algorithm, which guided the selection and timing of intravitreal injections, subtenon injections, and focal grid laser therapy based on individual patient characteristics and treatment responses. Comprehensive ophthalmic examinations, including Optical Coherence Tomography (OCT), were performed at each visit. Main Outcome Measures: Best-corrected visual acuity, treatment frequency, and patient dropout rate.
Results: Eyes treated with C-DATA showed a mean improvement of 14.7 letters over an average follow-up period of 37.2 months, compared to 8.2 letters for eyes treated with standard protocols. 71.4% of C-DATA-treated eyes improved, gaining an average of 22.14 letters. C-DATA required an average of 2.6 treatments per year, compared to 10.6 treatments per year for regimented protocols. The dropout rate for C-DATA was 1.9%, versus 11.4% for standard protocols.
Conclusions: The C-DATA approach for DME management demonstrated superior visual acuity outcomes, significantly reduced treatment burden, and enhanced patient compliance compared to traditional regimented protocols. These findings suggest that personalized, algorithm-based treatment strategies may optimize DME management and improve long-term patient outcomes.
Subjects: 33 patients with DME, contributing to 49 distinct eyes treated.
Methods: Patients were treated according to the C-DATA algorithm, which guided the selection and timing of intravitreal injections, subtenon injections, and focal grid laser therapy based on individual patient characteristics and treatment responses. Comprehensive ophthalmic examinations, including Optical Coherence Tomography (OCT), were performed at each visit. Main Outcome Measures: Best-corrected visual acuity, treatment frequency, and patient dropout rate.
Results: Eyes treated with C-DATA showed a mean improvement of 14.7 letters over an average follow-up period of 37.2 months, compared to 8.2 letters for eyes treated with standard protocols. 71.4% of C-DATA-treated eyes improved, gaining an average of 22.14 letters. C-DATA required an average of 2.6 treatments per year, compared to 10.6 treatments per year for regimented protocols. The dropout rate for C-DATA was 1.9%, versus 11.4% for standard protocols.
Conclusions: The C-DATA approach for DME management demonstrated superior visual acuity outcomes, significantly reduced treatment burden, and enhanced patient compliance compared to traditional regimented protocols. These findings suggest that personalized, algorithm-based treatment strategies may optimize DME management and improve long-term patient outcomes.