Clinical performance of predicting late age‐related macular degeneration development using multimodal imaging.

Background: To examine whether the clinical performance of predicting late age‐related macular degeneration (AMD) development is improved through using multimodal imaging (MMI) compared to using colour fundus photography (CFP) alone, and how this compares with a basic prediction model using well‐established AMD risk factors. Methods: Individuals with AMD in this study underwent MMI, including optical coherence tomography (OCT), fundus autofluorescence, near‐infrared reflectance and CFP at baseline, and then at 6‐monthly intervals for 3‐years to determine MMI‐defined late AMD development. Four retinal specialists independently assessed the likelihood that each eye at baseline would progress to MMI‐defined late AMD over 3‐years with CFP, and then with MMI. Predictive performance with CFP and MMI were compared to each other, and to a basic prediction model using age, presence of pigmentary abnormalities, and OCT‐based drusen volume. Results: The predictive performance of the clinicians using CFP [AUC = 0.75; 95% confidence interval (CI) = 0.68–0.82] improved when using MMI (AUC = 0.79; 95% CI = 0.72–0.85; p = 0.034). However, a basic prediction model outperformed clinicians using either CFP or MMI (AUC = 0.85; 95% CI = 0.78–91; p ≤ 0.002). Conclusions: Clinical performance for predicting late AMD development was improved by using MMI compared to CFP. However, a basic prediction model using well‐established AMD risk factors outperformed retinal specialists, suggesting that such a model could further improve personalised counselling and monitoring of individuals with the early stages of AMD in clinical practice. [ABSTRACT FROM AUTHOR]