Cohort Study of Race/Ethnicity and Incident Primary Open-Angle Glaucoma Characterized by Autonomously Determined Visual Field Loss Patterns.

PURPOSE

We evaluated racial/ethnic differences in primary open-angle glaucoma (POAG) defined by machine-learning-derived regional visual field (VF) loss patterns.

METHODS

Participants (N = 209,036) from the Nurses' Health Study (NHS; 1980-2018), Nurses' Health Study II (NHS2; 1989-2019), and Health Professionals Follow-Up Study (HPFS; 1986-2018) who were ≥40 years of age and free of glaucoma were followed biennially. Incident POAG cases (n = 1946) with reproducible VF loss were confirmed with medical records. Total deviation information from the earliest reliable glaucomatous VF for each POAG eye (n = 2564) was extracted, and machine learning analyses were used to identify optimal solutions ("archetypes") for regional VF loss patterns. Each POAG eye was assigned a VF archetype based on the highest weighting coefficient. Multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using per-eye Cox proportional hazards models.

RESULTS

We identified 14 archetypes: four representing advanced loss patterns, nine of early loss, and one of no VF loss. Compared to non-Hispanic whites, black participants had higher risk of early VF loss archetypes (HR = 1.98; 95% CI, 1.48-2.66) and even higher risk for advanced loss archetypes (HR = 6.17; 95% CI, 3.69-10.32; P-contrast = 0.0002); no differences were observed for Asians or Hispanic whites. Hispanic white participants had significantly higher risks of POAG with paracentral defects and advanced superior loss; black participants had significantly higher risks of all advanced loss archetypes and three early loss patterns, including paracentral defects.

CONCLUSIONS

Blacks, compared to non-Hispanic whites, had higher risks of POAG with early central and advanced VF loss.

TRANSLATIONAL RELEVANCE

In POAG, risks of VF loss regional patterns derived from machine learning algorithms showed racial differences.