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

Abstract

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.