Purpose: The objectives of this study were the creation and validation of a screening tool for age-related macular degeneration (AMD) for routine assessment by primary care physicians, ophthalmologists, other healthcare professionals, and the general population.
Methods: A simple, self-administered questionnaire (Simplified Théa AMD Risk-Assessment Scale [STARS] version 4.0) which included well-established risk factors for AMD, such as family history, smoking, and dietary factors, was administered to patients during ophthalmology visits. A fundus examination was performed to determine presence of large soft drusen, pigmentary abnormalities, or late AMD. Based on data from the questionnaire and the clinical examination, predictive models were developed to estimate probability of the Age-Related Eye Disease Study (AREDS) score (categorized as low risk/high risk). The models were evaluated by area under the receiving operating characteristic curve analysis.
Results: A total of 3854 subjects completed the questionnaire and underwent a fundus examination. Early/intermediate and late AMD were detected in 15.9% and 23.8% of the patients, respectively. A predictive model was developed with training, validation, and test datasets. The model in the test set had an area under the curve of 0.745 (95% confidence interval [CI] = 0.705-0.784), a positive predictive value of 0.500 (95% CI = 0.449-0.557), and a negative predictive value of 0.810 (95% CI = 0.770-0.844).
Conclusions: The STARS questionnaire version 4.0 and the model identify patients at high risk of developing late AMD.
Translational Relevance: The screening instrument described could be useful to evaluate the risk of late AMD in patients >55 years without having an eye examination, which could lead to more timely referrals and encourage lifestyle changes.
- age-related macular degeneration
- dietary factors
- machine learning
- primary care
- risk model
- self-administered questionnaire