Title: Investigating the Relationship Between Glaucoma Progression and Intraocular Pressure Reduction

Author: Fred Deyu Sun

Area of Concentration: Clinical and Translational Research / Informatics & Data Science

Specialty: Ophthalmology

Keywords: Glaucoma, Intraocular Pressure

Background: Glaucoma is a leading cause of irreversible blindness worldwide. Lowering intraocular pressure (IOP) is the primary therapeutic strategy to slow disease progression. However, significant heterogeneity in patients’ disease trajectories suggests that uniform IOP targets may be suboptimal. While past randomized controlled trials have shown an overall linear benefit of IOP reduction, real-world clinical variability raises the possibility that patients may benefit from personalized IOP targets. Current tools, such as the Save Sight Years Engine, apply fixed reduction ratios without accounting for dynamic individual response. This project aims to address that gap by modeling the relationship between longitudinal IOP changes and visual field progression.

Objective: To elucidate the individualized relationship between glaucoma progression rate and IOP reduction.

Methods: Using a longitudinal dataset from an institutional glaucoma registry, we are analyzing visual field index (VFI) changes and associated IOP measurements across multiple visits. The primary outcome is the rate of progression (RoP), measured via changes in VFI. We are fitting simple linear models and advanced models such as linear mixed-effects models to quantify patient-level associations between IOP and RoP.

Results: Preliminary data processing and mixed-effects model construction are underway. Due to ongoing data extraction and validation, final statistical results and model performance metrics will be updated in the final report (expected May 2025). Early exploratory analysis suggests a non-uniform relationship between baseline IOP and subsequent RoP, supporting the hypothesis that different patients may benefit from tailored IOP targets.

Conclusions: This study is expected to demonstrate that personalized IOP targets, dynamically informed by prior disease trajectories, may improve clinical outcomes compared to fixed reduction thresholds. The resulting clinical decision support tool could enhance individualized care in glaucoma management. [Final conclusions will be updated after full analysis completion.]