Predicting Progression of Age-Related Macular Degeneration Using Optical Coherence Tomography and Fundus Photography.

PURPOSE: To compare the performance of automatically quantified optical coherence tomography (OCT) imaging biomarkers and conventional risk factors manually graded on color fundus photographs (CFP) for predicting progression to late age-related macular degeneration (AMD). DESIGN: Longitudinal observational study. PARTICIPANTS: 280 eyes from 140 participants with bilateral large drusen. METHODS: All participants underwent OCT and CFP imaging at baseline and were then reviewed at six-monthly intervals to determine progression to late AMD. CFPs were manually graded and OCT scans underwent automated image analyses to quantify risk factors and imaging biomarkers respectively based on drusen and AMD pigmentary abnormalities. Four predictive models for progression to late AMD or atrophic AMD only were developed (each including age), based on: (1) CFP only (two parameters); (2) OCT biomarkers, minimal (three parameters); (3) OCT biomarkers, extended (seven parameters); (4) CFP and OCT combined (eight parameters). MAIN OUTCOME MEASURES: Predictive performance for progression to late AMD, examined based on the area under the receiver operating characteristic curve (AUC) for correctly predicting progression. RESULTS: The AUC for predicting late AMD development was similar for the models based on CFP alone (model 1; 0.80), OCT alone (models 2 and 3; 0.82 for both) and when using both modalities together (model 4; 0.85). In addition, these models also performed similarly for predicting the endpoint of atrophic AMD only (AUC = 0.83, 0.84, 0.85 and 0.88 for models 1, 2, 3 and 4 respectively). CONCLUSIONS: OCT imaging biomarkers could provide an automatic method of risk stratification for progression to vision-threatening late AMD as well as manually grading of CFP.