Dual-Level Pattern Tree for Visual Field Improves Glaucoma Progression and Polygenic Risk Prediction.

ABSTRACT:

Purpose

To develop a dual-level pattern tree to characterize visual field (VF) loss subtypes that can be used to better predict glaucoma progression and glaucoma polygenic risk scores (PRSs).

Methods

This study included 113,030 patients from three datasets, each used for a specific purpose: (1) model training, (2) progression forecasting, and (3) PRS correlations. We applied archetypal analysis to cluster 24-2 VFs into trunk patterns and their branch patterns. The Cox regression model was used to forecast VF progression using mean deviation (MD) slope, MD-fast slope, total deviation (TD) pointwise slope, and visual field index (VFI) slope. Multivariable regression analyses were used to link VF patterns with glaucoma PRSs. The Akaike information criterion (AIC) was used for m

SUBMITTER: Song L 

PROVIDER: S-EPMC12697711 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature