Retinal Layer Thickness, Demographic Data Can Aid in Glaucoma Diagnosis

Glaucoma detection may be improved with the incorporation of retinal nerve fiber layer (RNFL) data into ethnicity-tailored models, according to a report published in Ophthalmology Glaucoma.

Optical coherence tomography (OCT) data from 2699 healthy Asian participants was used to develop an Asian-specific multivariate model. Compensated RNFL thickness was estimated on the basis of age, ethnicity, refractive error, fovea, optic disc, and retinal vessel density and compared with measured values. This model was assessed with OCT data from 387 age- and gender-matched cohorts of patients with and without glaucoma and performance was compared with a previous model formulated with data from White participants.

The model was constructed using eye data from 646 Chinese, 552 Indian, and 421 Malay participants and validated using data from 430 Chinese, 367 Indian, and 282 Malay individuals.

Stratified by ethnicity, Patients who were Indian had the lowest OCT signal strength, shortest fovea distance and axial length, smallest foveal-optic disc angle, most sparse retinal vessel density, and most hyperopic spherical equivalent (all P <.001) and Chinese had the most elliptical optic disc and smallest area (both P <.001).

The Asian-specific compensation model had better standard deviations (SD) of the RNFL thickness than White-specific measures (14.34% vs 11.62%). Stratified by ethnicity, the difference in SD was greatest among Chinese (12.50%-16.94%) followed by Malays (10.42%-13.94%) and Indians (9.13%-12.08%).

The glaucoma cohort was aged mean 63.89±8.16 years and 219 had early glaucoma, 97 moderate glaucoma, and 71 advanced glaucoma. Eyes with glaucoma tended to have a less elliptical and tilted optic disc with larger area, sparser retinal vessel density, increased myopia, longer axial length, decreased OCT signal strength, and thinner RNFL thickness compared with the age- and gender-matched healthy controls (all P <.001).

Compared with the normative RNFL thickness model, those with advanced glaucoma had the greatest deviation (mean, −40.07±10.53 μm) followed by moderate glaucoma (mean, −32.31±11.36 μm), early glaucoma (mean, −26.92±11.17 μm), and controls (mean, −7.88±9.90 μm; P <.001).

Predicted RNFL thickness outperformed measured RNFL thickness among the early (area under the curve [AUC], 0.59-0.91 vs 0.53-0.88; P <.001), moderate (AUC, 0.62-0.96 vs 0.57-0.95; P <.001), and advanced (AUC, 0.78-0.99 vs 0-75-0.98; P =.004) glaucoma cohorts.

Overall, 71% of early glaucoma individuals had abnormal results compared with 59% using standard measurement; 83% compared with 76% for moderate glaucoma; and 97% compared with 91% for advanced glaucoma, respectively.

The best predictors for differentiating the glaucoma and control cohorts were ethnicity (AUC, 0.70-0.79) and spherical equivalent refractive error (AUC, 0.67-0.69).

This study was limited by not assessing the healthy controls for abnormal visual fields.

These data indicated that an Asian-specific RNFL thickness model improved detection of glaucoma, suggesting its clinical utility.

Reference

Chua J, Schwarzhans F, Wong D, et al. Multivariable normative comparison, a novel method for improved use of the retinal nerve fiber layer thickness to detect early glaucoma. Ophthalmol Glaucoma. 2021;S2589-4196(21)00248-9. doi:10.1016/j.ogla.2021.10.013