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Describing Candidate Geographic Atrophy Phenotypes and Their Different Growth Parameters
Talisa E de Carlo Forest1, Marc T Mathias1, Nathan Grove1
1From the Sue Anschutz-Rodgers Eye Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Purpose:
Describe distinct candidate geographic atrophy (GA) phenotypes in age-related macular degeneration and their different growth parameters.
Design:
Prospective cohort study.
Method:
Patients with GA enrolled in the University of Colorado age-related macular degeneration Registry from 9/2014 to 9/2022, with follow-up through 4/2023, with ≥five fundus autofluorescence (FAF) time points were included. Longitudinal FAFs for each patient's eye were reviewed by two graders for candidate GA phenotype: (1) unifocal foveal-involving (UF), (2) large coalescing multifocal (LCM), (3) small numerous multifocal (SNM), and presence of a concomitant peripapillary component. Each FAF image was processed using an artificial intelligence (AI) based segmentation model to automatically delineate GA lesions and calculate lesion area, with manual review/adjustment. Square root transformed (SQRT) growth rate was calculated per eye. Gompertz modelling of GA growth was performed to estimate maximum GA growth rate and projected GA size. Linear regression using generalized estimating equations estimated associations between phenotypes and measures of GA growth rate.
Results:
81 eyes with GA from 48 patients were included. Average subject age was 80 years (SD:8). Average baseline GA size was 6.4mm2 (SD:7.5). Eyes with a peripapillary component had higher modeled maximum GA growth rates (beta 0.37; 95% confidence interval [CI]:0.16,0.59; P<0.001) and maximum GA size (beta 0.24; 95%CI:0.10,0.38; P<0.001) in univariate analysis. After adjusting for a peripapillary component, the LCM and SNM phenotypes had larger predicted maximum GA sizes than the UF phenotype (beta 0.10; 95%CI:0.03,0.18; P=0.009 and beta 0.10; 95%CI:-0.00,0.21; P=0.059, respectively). The SNM phenotype had faster SQRT and modeled maximum GA growth rates compared to the UF phenotype (beta 0.09; 95%CI:0.03,0.16; P=0.005 and beta 0.29; 95%CI:0.13,0.44; P<0.001, respectively), and the LCM phenotype had borderline faster SQRT growth rates than the UF phenotype (P=0.05). Further, the SNM phenotype had marginally higher modeled maximum GA growth rates than the LCM phenotype (estimated marginal mean difference 0.200mm/y; 95%CI:-0.00,0.40; P=0.054).
Conclusions:
We describe three candidate GA phenotypes and their different growth parameters. The large coalescing multifocal and small numerous multifocal phenotypes had more severe growth trajectories, and presence of a peripapillary component portended more severe outcomes. This may have implications for clinical trial interpretation and clinical prognostication.
