Predicting progression in glaucoma suspects with longitudinal estimates of retinal ganglion cell counts.

Published online

Journal Article

PURPOSE: We evaluated the ability of baseline and longitudinal estimates of retinal ganglion cell (RGC) counts in predicting progression in eyes suspected of having glaucoma. METHODS: The study included 288 glaucoma suspect eyes of 288 patients followed for an average of 3.8 ± 1.0 years. Participants had normal standard automated perimetry (SAP) at baseline. Retinal nerve fiber layer thickness assessment was performed with optical coherence tomography (OCT). Progression was defined as development of repeatable abnormal SAP or glaucomatous progressive optic disc changes. Estimates of RGC counts were obtained by combining data from SAP and OCT according to a previously described method. Joint longitudinal survival models were used to evaluate the ability of baseline and rates of change in estimated RGC counts for predicting progression over time, adjusting for confounding variables. RESULTS: A total of 48 eyes (17%) showed progression during follow-up. The mean rate of change in estimated RGC counts was -18,987 cells/y in progressors versus -8,808 cells/y for nonprogressors (P < 0.001). Baseline RGC counts and slopes of RGC loss were significantly predictive of progression, with HRs of 1.56 per 100,000 cells lower (95% confidence interval [CI], 1.18-2.08; P = 0.002) and 2.68 per 10,000 cells/y faster loss (95% CI, 1.22-5.90; P = 0.014), respectively. The longitudinal model including estimates of RGC counts performed significantly better than models including only structural or functional indexes separately. CONCLUSIONS: Baseline and longitudinal estimates of RGC counts may be helpful in predicting progression and performed significantly better than conventional approaches for risk stratification of glaucoma suspects.

Full Text

Duke Authors

Cited Authors

  • Meira-Freitas, D; Lisboa, R; Tatham, A; Zangwill, LM; Weinreb, RN; Girkin, CA; Liebmann, JM; Medeiros, FA

Published Date

  • June 19, 2013

Published In

Volume / Issue

  • 54 / 6

Start / End Page

  • 4174 - 4183

PubMed ID

  • 23661375

Pubmed Central ID

  • 23661375

Electronic International Standard Serial Number (EISSN)

  • 1552-5783

Digital Object Identifier (DOI)

  • 10.1167/iovs.12-11301


  • eng

Conference Location

  • United States