Age-Related Vision Loss Predicted by New Online Tool

A simple risk assessment tool incorporating baseline retinal characteristics can help predict a person's likelihood of developing age-related macular degeneration, researchers suggested.

A patient with a simple risk score of one, indicating the presence of a single retinal abnormality in one eye, had a hazard ratio of 6.38 (95% CI 3.48 to 11.69, P<0.001) for having advanced macular degeneration at ten years, according to Michael L. Klein, MD, of Oregon Health & Science University in Portland, and colleagues.

And with a risk score of just two out of four at baseline, the hazard ratio reached 14.12 (95% CI 8.06 to 24.75, P<0.001), the researchers reported online in the Archives of Ophthalmology.
A number of risk factors have been linked with age-related macular degeneration, such as smoking, dyslipidemia, and certain genetic polymorphisms.
While previous risk models have relied on these factors, Klein and colleagues sought to refine the accuracy by incorporating patient phenotypic characteristics.
Accordingly, they analyzed data from the longitudinal Age-Related Eye Disease Study, which followed almost 3,000 patients for the development of macular degeneration and cataracts.
All participants had detailed histories and ocular examinations done, and DNA samples were available for 2,846 of those who were white and therefore would not have race-related allele differences.
The two retinal abnormalities used to calculate the simple risk score were the presence of large yellow extracellular deposits known as drusen (125 μm in diameter or more), and any abnormality in retinal pigmentation.
A total of 24% of patients without severe abnormalities at baseline developed advanced macular degeneration during follow up.
In 46% of these, the degeneration involved geographic atrophy, or "dry" macular degeneration, while the remainder had the neovascular or "wet" form.
Univariate analysis identified numerous factors that might be associated with progression of macular degeneration, including age, family history, the simple risk score, smoking, and variants in several genes such as ARMS2 and CFH.
Then on multivariate analysis, the largest hazard ratios remained for the simple risk score -- much higher than any of the other significant variables:

• Risk score 4, HR 50.65 (95% CI 28.86 to 88.89, P<0.001)
• Very large drusen (≥250 μm), HR 1.79 (95% CI 1.50 to 2.14, P<0.001)
• Smoking, HR 1.78 (95% CI 1.37 to 2.31, P<0.001)
• TT allele of ARMS2, HR 2 (95% CI 1.59 to 2.50, P<0.001)
• CC allele of CFH, HR 1.44 (95% CI 1.14 to 1.83, P=0.003)
• Family history, HR 1.40 (95% CI 1.16 to 1.70, P<0.001)
• Advanced macular degeneration in one eye at baseline, HR 1.21 (95% CI 1.02 to 1.45, P=0.03)
• Age, HR 1.03 (95% CI 1.01 to 1.05, P<0.001)

When the researchers tested the performance of the model by calculating the area under the receiver operating characteristic curve, they found the C statistic to be excellent, at 0.872 (with 1.0 being perfect).
The findings of this analysis, according to the researchers, suggest that genetic testing alone or in addition to demographic and environmental factors -- as has been proposed by some -- is inadequate in screening for macular degeneration among older people.
"We believe that the first priority for individuals at potentially increased risk for developing [age-related macular degeneration] based on age, family history, and other factors should be to obtain an eye examination," asserted Klein and colleagues.
During this examination, which should include evaluation of the macula, information can also be obtained about the person's likelihood of other ocular disorders, along with relevant phenotypic, environmental, and demographic data.
Based on their analyses, Klein's group also developed a risk calculator (available online) that can be used to advise the patient immediately about prognosis.
They noted that greater advancements are likely to come in identifying environmental and genetic influences on macular degeneration. As information becomes available the authors plan to update the online model for use by clinicians.
Limitations of the model were its inclusion of only white participants and those ages 50 to 85, but the model could be adapted for use in other groups, they said.
The findings of this study "can be of potential value in clinical practice by helping determine the frequency of follow-up examinations, the use of home monitoring of central vision, and the advisability of initiating preventive measures including beneficial lifestyle changes such as dietary alterations and nutritional supplement use," Klein and colleagues concluded.