July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Validated Prediction Models for Macular Degeneration Progression and Predictors of Visual Acuity Loss Identify High Risk Individuals
Author Affiliations & Notes
  • Johanna M Seddon
    Ophthalmology and Visual Sciences, Macular Degeneration Center of Excellence, University of Massachusetts Medical School, Worcester, Massachusetts, United States
  • Bernard Rosner
    Channing Division of Network Medicine, Harvard Medical School, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Johanna Seddon, Gemini Therapeutics, Inc (E); Bernard Rosner, None
  • Footnotes
    Support  NIH Grant R01 EY011309, R01 EY022445, Mass. Lions Research Fund, American Macular Degeneration Foundation
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 2211. doi:https://doi.org/
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      Johanna M Seddon, Bernard Rosner; Validated Prediction Models for Macular Degeneration Progression and Predictors of Visual Acuity Loss Identify High Risk Individuals. Invest. Ophthalmol. Vis. Sci. 2019;60(9):2211. doi: https://doi.org/.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To determine predictive factors and risk scores for conversion from non-advanced to advanced age-related macular degeneration (AMD), geographic atrophy (GA), neovascular disease (NV), and loss of vision, and to derive and validate a model for AMD progression in an external cohort.

Methods : Progression to advanced AMD over 12 years was evaluated using stepwise survival analysis in the derivation cohort (AREDS) with the eye as the unit of analysis (n=5355 eys). Risk scores including genetic, demographic, behavioral, and ocular factors were derived for three advanced AMD endpoints and were validated and calibrated in our large independent cohort (n=3955 eyes). Vision loss of 15 or more letters was evaluated as a new endpoint in genetic analyses.

Results : Eight 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. (Table 1) 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 non-progressors had a lower risk category when genetic factors were considered. Eyes 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 (Table 2). 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, BMI, smoking, and several common and rare genetic variants.

Conclusions : A model with both genetic and non-genetic variables yields meaningful risk stratification among eyes with a similar baseline macular phenotype. 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.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Table1. Stepwise Selection of Genetic Factors Predictive of Progression to Advanced AMD in Derivation Cohort, adjusting for age, sex, race, education, BMI, smoking, baseline AMD.

Table1. Stepwise Selection of Genetic Factors Predictive of Progression to Advanced AMD in Derivation Cohort, adjusting for age, sex, race, education, BMI, smoking, baseline AMD.

 

Table 2. Incidence of Progression to Advanced AMD Based on the Composite Risk Score, Adjusting for Mortality, in Eyes with Baseline Intermediate Stage.

Table 2. Incidence of Progression to Advanced AMD Based on the Composite Risk Score, Adjusting for Mortality, in Eyes with Baseline Intermediate Stage.

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