Identifying Predictors of Anti-VEGF Treatment Response in Patients with Neovascular Age-Related Macular Degeneration through Discriminant and Principal Component Analysis
Аннотация:<b><i>Objective:</i></b> AURA was an observational study that monitored visual acuity outcomes following ranibizumab use in neovascular age-related macular degeneration patients over 2 years. The aim of this analysis was to identify factors that were predictive of visual acuity outcomes in AURA. <b><i>Methods:</i></b> The correlation between the baseline characteristics, the use of resources and the visual acuity outcomes in AURA was explored using principal component analysis (PCA) and partial least-squares-discriminant analysis (PLS-DA). The response variables analysed were mean change in visual acuity over 2 years (analysed via PCA) and no decline in visual acuity at 2 years compared with baseline (analysed via PLS-DA). <b><i>Results:</i></b> The AURA dataset comprised 2,227 patients and 132 variables. Using PCA and PLS-DA, we found that the number of ranibizumab injections, clinic and monitoring visits, number of optical coherence tomography scans and ophthalmoscopies correlated with a change in visual acuity at Years 1 and 2, and are therefore key drivers of treatment success. <b><i>Conclusion:</i></b> This is a novel approach to graphically explore relationships between multiple correlated covariates and outcomes in real-life ophthalmology studies. It identified a number of variables that are positively linked with treatment outcomes.
