Race and Glaucoma Progression
JAMA Ophthalmology, April 2018
In a multicenter longitudinal study of visual field changes in Europeans and Africans with glaucoma, Gracitelli et al. found that African descent is linked to larger variability in standard automated perimetry results and greater time to detect disease progression.
Participants were enrolled from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study; 173 patients (236 eyes) were of European descent and 171 (235 eyes) were of African descent. Mean baseline age was similar for the study groups, as was gender distribution. Differences in test-retest variability were investigated, and the simulated time to detect glaucoma progression was estimated. For each eye, standard automated perimetry mean deviation values were regressed over time, and the standard deviation (SD) of residuals was used as a measure of variability. Distributions of residuals were used in computer simulations to reconstruct real-world standard automated perimetry mean deviation trajectories under different assumptions for change rates and testing schedules. The mean follow-up period was 7.5 years.
The mean (SD) of residuals was found to be larger for eyes in the African group: 1.45 (0.83) dB versus 1.12 (0.48) dB in the European group (mean difference, 0.33 dB). As glaucoma progressed, those of African descent were more likely to have a greater increase in visual field variability. Disease progression was detected earlier in the European group, as demonstrated by simulation analyses. For a scenario with baseline mean deviation of –10 dB and a change rate of –0.5 dB/year, progression detection was delayed by 3.1 years in the African group (assuming 80% power and annual testing).
This research adds to previous studies of the high prevalence of glaucoma-related visual impairment among people of African descent. The high variability in visual field test-retest results can prolong detection of progression. To avert this, the authors suggested increasing the frequency of testing, which may yield better estimates of change indices over time; using complementary methods to assess progression; and combining structural and functional testing. (Also see related commentary by Eve J. Higginbotham, SM, MD, in the same issue.)
The original article can be found here.