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March 1, 2026Ophthalmology ScienceOpen Access

Retinomics as a tool for glaucoma prediction

Mayinuer Yusufu Selena Wei Zhang Robert N. Weinreb Chen Zhou Mengtian Kang Xianwen Shang Mingguang He Danli Shi

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Key Points

Investigate how retinomic changes can predict glaucoma onset and their predictive accuracy.
Analyzed data from 40,949 adults using color fundus photography (CFP) and optical coherence tomography (OCT).
Employed LASSO feature selection and Cox regression to examine associations with glaucoma incidence.
Utilized Gradient Boosting Machine for evaluating predictive performance of retinomic features.
653 participants developed glaucoma over a median follow-up of 12.49 years.
18 significant retinal parameters identified increased glaucoma risk by 8.2% to 26.4% per standard deviation change.
The model achieved a concordance index of 0.767 for incident glaucoma prediction.

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Implication

Cohort study demonstrates retinomic changes predict glaucoma onset, suggesting novel screening approaches.

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Cite This Study

Yusufu et al. (2026) studied this question.

synapsesocial.com/papers/69bf8692f665edcd009e8e35 https://doi.org/10.1016/j.xops.2026.101163

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