A proof-of-concept study recently published in the American Journal of Ophthalmology outlined the development and evaluation of Atrophy Advisor, a clinical decision tool integrating geographic atrophy (GA) progression and personalized lifespan estimates to help clinicians considering complement factor inhibitor injections for GA patients.
Give me some background.
GA is an advanced form of age-related macular degeneration (AMD) characterized by atrophic lesions that start in the outer retina and progress across the macula and fovea, resulting in permanent vision loss over time.
- In recent years, GA treatment has undergone rapid changes with the FDA approvals for avacincaptad pegol (IZERVAY, Astellas Pharma) and pegcetacoplan (SYFOVRE, Apellis Pharmaceuticals)—two intravitreal injections that target the complement cascade.
And while these therapies slow GA progression by inhibiting lesion growth, they have a limited effect on visual acuity and carry the usual risks of intravitreal injections.
- Consequently: Having a tool that can help guide clinicians weigh the benefits and risks of complement factor inhibitor injections for GA patients may aid in optimizing patient selection.
So tell me about this Atrophy Advisor calculator.
Written in JavaScript code, the tool utilizes inputs from a clinician's estimates of distance of the closest GA point to the fovea—as well as a patient's age and sex.
The result: An output that shows the estimated time until the GA touches the fovea as well as the patient’s expected lifespan.
- See here for details on how the calculator works.
Alrighty, now talk about the study.
In this retrospective cohort study, investigators analyzed fundus imaging and electronic health record (EHR) data from 50 consecutive patients (median age: 78 years, 64% female) with GA secondary to nonexudative AMD who were seen at Wake Forest University-affiliated retina clinics from May 2013 to June 2025.
Fundus photographs at two or more time points were assessed using ImageJ to measure the distance from the fovea to the nearest GA edge.
- Then: Pixel-to-micron conversion was made using an assumed vertical disk diameter of 1,800 μm.
Anything else?
Demographics, comorbidities, and corrected visual acuities (VAs) were extracted from records, and lifespan estimates were calculated using University of Connecticut (UC) and Social Security Administration algorithms—and were then subsequently compared to these observed outcomes.
The study’s main outcome measures included:
- GA edge-to-fovea distance
- GA progression rate
- Corrected VA
- Predicted vs. observed lifespan
Findings?
The baseline median GA-to-fovea distance was 792 μm (interquartile range [IQR]: 508-1,213 μm) and declined to 395 μm (IQR: 194-702 μm) at the last follow-up.
Median GA progression was 122 μm/year (range: 2-626 μm/year), with a direct relationship between initial distance and progression rate (P = 0.006).
How did the lifespan calculators perform?
The UC calculator yielded a median lifespan estimate of 11.9 years, while Atrophy Advisor reported 11.0 years and these programs influenced treatment guidance in 4% of cases.
Expert opinion?
The study authors explained the need for “more precise ophthalmology-specific lifespan models that incorporate systemic risk factors (e.g., hypertension, body mass index [BMI], smoking) and genetic profiles.”
Moreover: They recommended developing quality-adjusted life expectancy to better evaluate the burden of injections compared to the benefit of vision preservation at various life stages.
Any limitations to note?
Measurement variability and the study’s retrospective design were the main limitations of this analysis.
Take home.
These findings suggest that clinicians could feasibly use Atrophy Advisor for combining GA progression kinetics and lifespan estimates to inform treatment decisions.
However: Variability in progression rates and lifespan predictions highlights the need for personalized approaches.
What’s next?
“Possible next steps might involve validating GA proximity metrics in larger, prospective cohorts with standardized imaging protocols, incorporating machine-learning approaches to integrate hyperreflective foci, genetic risk and focality data, and comparing nearest GA edge-based progression model against area-based methods in clinical trials,” the study authors explained.