Chung-Jung Chiu1, Paul Mitchell2, Ronald Klein3, Barbara E Klein3, Min-Lee Chang4, Gary Gensler5, Allen Taylor6. 1. Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts; Department of Ophthalmology, School of Medicine, Tufts University, Boston, Massachusetts. Electronic address: cj.chiu@tufts.edu. 2. Centre for Vision Research, Westmead Hospital, University of Sydney, Westmead, Australia. 3. Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. 4. Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts. 5. Age-Related Eye Disease Study Coordinating Center, The EMMES Corporation, Rockville, Maryland. 6. Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts; Department of Ophthalmology, School of Medicine, Tufts University, Boston, Massachusetts.
Abstract
PURPOSE: To develop a clinical eye-specific prediction model for advanced age-related macular degeneration (AMD). DESIGN: The Age-Related Eye Disease Study (AREDS) cohort followed up for 8 years served as the training dataset, and the Blue Mountains Eye Study (BMES) cohort followed up for 10 years served as the validation dataset. PARTICIPANTS: A total of 4507 AREDS participants (contributing 1185 affected vs. 6992 unaffected eyes) and 2169 BMES participants (contributing 69 affected vs. 3694 unaffected eyes). METHODS: Using Bayes' theorem in a logistic model, we used 8 baseline predictors-age, sex, education level, race, smoking status, and presence of pigment abnormality, soft drusen, and maximum drusen size-to devise and validate a macular risk scoring system (MRSS). We assessed the performance of the MRSS by calculating sensitivity, specificity, and the area under the receiver operating characteristic curve (i.e., c-index). MAIN OUTCOME MEASURES: Advanced AMD. RESULTS: The internally validated c-indexAREDS (0.88; 95% confidence interval, 0.87-0.89) and the externally validated c-indexBMES (0.91; 95% confidence interval, 0.88-0.95) suggested excellent performance of the MRSS. The sensitivity and specificity at the optimal macular risk score cutoff point of 0 were 87.6% and 73.6%, respectively. An application for the iPhone and iPad also was developed as a practical tool for the MRSS. CONCLUSIONS: The MRSS was developed and validated to provide satisfactory accuracy and generalizability. It may be used to screen patients at risk of developing advanced AMD.
PURPOSE: To develop a clinical eye-specific prediction model for advanced age-related macular degeneration (AMD). DESIGN: The Age-Related Eye Disease Study (AREDS) cohort followed up for 8 years served as the training dataset, and the Blue Mountains Eye Study (BMES) cohort followed up for 10 years served as the validation dataset. PARTICIPANTS: A total of 4507 AREDS participants (contributing 1185 affected vs. 6992 unaffected eyes) and 2169 BMES participants (contributing 69 affected vs. 3694 unaffected eyes). METHODS: Using Bayes' theorem in a logistic model, we used 8 baseline predictors-age, sex, education level, race, smoking status, and presence of pigment abnormality, soft drusen, and maximum drusen size-to devise and validate a macular risk scoring system (MRSS). We assessed the performance of the MRSS by calculating sensitivity, specificity, and the area under the receiver operating characteristic curve (i.e., c-index). MAIN OUTCOME MEASURES: Advanced AMD. RESULTS: The internally validated c-indexAREDS (0.88; 95% confidence interval, 0.87-0.89) and the externally validated c-indexBMES (0.91; 95% confidence interval, 0.88-0.95) suggested excellent performance of the MRSS. The sensitivity and specificity at the optimal macular risk score cutoff point of 0 were 87.6% and 73.6%, respectively. An application for the iPhone and iPad also was developed as a practical tool for the MRSS. CONCLUSIONS: The MRSS was developed and validated to provide satisfactory accuracy and generalizability. It may be used to screen patients at risk of developing advanced AMD.
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