ArticleAmerican journal of ophthalmology2019
Validated Prediction Models for Macular Degeneration Progression and Predictors of Visual Acuity Loss Identify High-Risk Individuals.
Article in American journal of ophthalmology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Dietary Nutrient Intake and Progression to Late Age-Related Macular Degeneration in the Age-Related Eye Disease Studies 1 and 2.Ophthalmology · 2021Trial
- Characterization of Drusen and Hyperreflective Foci as Biomarkers for Disease Progression in Age-Related Macular Degeneration Using Artificial Intelligence in Optical Coherence Tomography.JAMA ophthalmology · 2020Trial
- OCT predictors of retinal atrophy in neovascular age-related macular degeneration treated with aflibercept.International journal of ophthalmology · 2025Article
- The role of nutritional factors in transitioning between early, mid, and late stages of age-related macular degeneration: prospective longitudinal analysis.The American journal of clinical nutrition · 2024Observational
- Personalizing Nutrition Strategies: Bridging Research and Public Health.Journal of personalized medicine · 2024Review
- Personalized Care in Eye Health: Exploring Opportunities, Challenges, and the Road Ahead for Chatbots.Journal of personalized medicine · 2023Review
- Family History of Age-Related Macular Degeneration and Genetics Predict Progression to Advanced Age-Related Macular Degeneration Adjusting for Macular Status, Demographic, and Lifestyle Factors.American journal of ophthalmology · 2023Article
- Symmetry of Macular Fundus Features in Age-Related Macular Degeneration.Ophthalmology. Retina · 2023Article
- Evaluation of Risk Prediction with Hierarchical Data: Dependency Adjusted Confidence Intervals for the AUC.Stats · 2023Article
- Rare DysfunctionalOphthalmology science · 2023Article
- Identifying Novel Genes and Variants in Immune and Coagulation Pathways Associated with Macular Degeneration.Ophthalmology science · 2023Article
- Deep ensemble learning for automated non-advanced AMD classification using optimized retinal layer segmentation and SD-OCT scans.Computers in biology and medicine · 2023Article
- Risk and protection of different rare protein-coding variants of complement component C4A in age-related macular degeneration.Frontiers in genetics · 2023Article
- Polygenic Risk Score Impact on Susceptibility to Age-Related Macular Degeneration in Polish Patients.Journal of clinical medicine · 2022Article
- The negative impact of COVID-19 pandemic on age-related macular degeneration patients treated with intravitreal bevacizumab injections.International ophthalmology · 2022Article
- Genetic Aspects of Age-Related Macular Degeneration and Their Therapeutic Potential.International journal of molecular sciences · 2022Review
- Functional analysis of rare genetic variants in complement factor I in advanced age-related macular degeneration.Human molecular genetics · 2022Article
- Role of Adiponectin Peptide I (APNp1) in Age-Related Macular Degeneration.Biomolecules · 2022Article
- A Screening Tool for Self-Evaluation of Risk for Age-Related Macular Degeneration: Validation in a Spanish Population.Translational vision science & technology · 2022Article
- Sex and Age-Related Differences in Complement Factors Among Patients With Intermediate Age-Related Macular Degeneration.Translational vision science & technology · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
purposeTo determine predictive factors and risk scores for conversion to overall advanced age-related macular degeneration (AMD), geographic atrophy (GA), neovascular disease (NV), and loss of vision, and to validate the model for AMD in an external cohort.
methodsProgression to advanced AMD was evaluated using stepwise survival analysis. Risk scores including genetic, demographic, behavioral, and ocular factors were derived for 3 AMD endpoints and were validated and calibrated in a large independent cohort. Vision loss of 15 or more letters was evaluated as a new endpoint in genetic analyses.
resultsEight common and rare variants in genes CFH, C3, ARMS2, COL8A1, and HSPH1/B3GALTL conferred a significantly higher risk of transition to advanced AMD. Three loci (C2, CFB, RAD51B) were associated with lower rate of progression. A protective effect was suggested for CTRB1 and PELI3. The age-adjusted area under the curve (AUC) for the composite model including 13 loci model was 0.900 over 12 years (0.896 in the validation cohort). Generally, progressors had a higher risk category and nonprogressors had a lower risk category when genetic factors were considered. Furthermore, there was heterogeneity between models for GA and NV. The model was calibrated in the validation cohort. Determinants of visual loss included age, education, body mass index, smoking, and several common and rare genetic variants.
conclusionEyes with the same baseline macular grade had a wide range of estimated probability of subsequent progression and visual loss based on the validated risk score. Identifying high-risk individuals at an earlier stage using predictive modeling could lead to improved preventive and therapeutic strategies in the era of precision medicine.
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