Faculty Bibliography

PURPOSE: To compare prospectively detection of progressive retinal nerve fiber layer thickness (RNFL) atrophy identified using time-domain optical coherence tomography with visual field progression using standard automated perimetry in glaucoma suspect and preperimetric glaucoma patients or perimetric glaucoma patients. DESIGN: Prospective, longitudinal clinical trial. METHODS: Eligible eyes with 2 years or more of follow-up underwent time-domain optical coherence tomography and standard automated perimetry every 6 months. The occurrence of visual field progression was defined as the first follow-up visit reaching a significant (P < .05) negative visual field index slope over time. RNFL progression or improvement was defined as a significant negative or positive slope over time, respectively. Specificity was defined as the number of eyes with neither progression nor improvement, divided by the number of eyes without progression. Cox proportional hazard ratios were calculated using univariate and multivariate models with RNFL loss as a time-dependent covariate. RESULTS: Three hundred ten glaucoma suspect and preperimetric glaucoma eyes and 177 perimetric glaucoma eyes were included. Eighty-nine eyes showed visual field progression and 101 eyes showed RNFL progression. The average time to detect visual field progression in those 89 eyes was 35 +/- 13 months, and the average time to detect RNFL progression in those 101 eyes was 36 +/- 13 months. In multivariate Cox models, average and superior RNFL losses were associated with subsequent visual field index loss in the entire cohort (every 10-mum loss; hazard ratio, 1.38; P = .03; hazard ratio, 1.20; P = .01; respectively). Among the entire cohort of 487 eyes, 42 had significant visual field index improvement and 55 had significant RNFL improvement (specificity, 91.4% and 88.7%, respectively). CONCLUSIONS: Structural progression is associated with functional progression in glaucoma suspect and glaucomatous eyes. Average and superior RNFL thickness may predict subsequent standard automated perimetry loss.