November 6, 2014

Study May Lead to More Accurate Long-Term Prediction of Wet AMD


Study May Lead to More Accurate Long-Term Prediction of Wet AMD

Stanford University School of Medicine scientists have found a new way to forecast which patients with age-related macular degeneration (AMD) are likely to progress to the advanced wet form of the disease. Until now, there has been no effective way to to do this.
The new method predicts whether a patient’s vision would, if untreated, probably deteriorate more rapidly, due to retinal blood vessel growth and leakage, and approximately when that would occur. Armed with such information, ophthalmologists could make smarter decisions about when to schedule office visits for high-risk patients.
The study, published in the November issue of Investigative Ophthalmology & Visual Science, describes how researchers have derived a formula that accurately distinguishes likely from unlikely progressors by analyzing patient data from retinal scans using spectral domain optical coherence tomography (SD-OCT). The new method, according to Daniel Rubin, MD (assistant professor of radiology and of biomedical informatics) adds to the traditional data a computerized image-processing step that combines and analyzes the patient’s previous scans to generate a prediction.
Doctors will then be able to generate a number (“risk score”) that predicts a patient’s likelihood of progressing to wet AMD within one, three, or five years.
After analyzing data from 2,146 scans of 330 eyes in 244 patients over a five-year period, the researchers found that a risk score could be determined by weighing the area and height of drusen, the amount of reflectivity at the macular surface, and the degree of change in these features over time. Comparing this data with actual instances of progression to wet AMD, they were able to accurately predict every occurrence of progression to the wet stage within a year.
Rubin and his associates are now entering into a larger study with patients from other institutions to try duplicating the results.
SOURCE: Stanford press release

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