Incorporating risk factors to improve the assessment of rates of glaucomatous progression.

Journal Article (Journal Article)

PURPOSE: To present and evaluate a new method of integrating risk factors into the analysis of rates of visual field progression in glaucoma. METHODS: The study included 352 eyes of 250 glaucoma patients followed up for an average of 8.1 ± 3.5 years. Slopes of change over time were evaluated by the mean deviation (MD) from standard automated perimetry. For each eye, the follow-up time was divided into two equal periods: the first half was used to obtain the slopes of change and the second period was used to test the predictions. Slopes of change were calculated with two methods: the conventional approach of ordinary least squares (OLS) linear regression and a Bayesian regression model incorporating information on risk factors and presence of progressive optic disc damage on stereophotographs. The mean square error (MSE) of the predictions was used to compare the predictive performance of the different methods. RESULTS: Higher mean IOP, thinner central corneal thickness (CCT), and presence of progressive optic disc damage were associated with faster rates of MD change. Incorporation of risk factor information into the calculation of individual slopes of MD change with the Bayesian method resulted in better prediction of future MD values than with the OLS method (MSE: 4.31 vs. 8.03, respectively; P < 0.001). CONCLUSIONS: A Bayesian regression model incorporating structural and risk factor information into the estimation of glaucomatous visual field progression resulted in more accurate and precise estimates of slopes of functional change than the conventional method of OLS regression. ( number, NCT00221897.).

Full Text

Duke Authors

Cited Authors

  • Medeiros, FA; Zangwill, LM; Mansouri, K; Lisboa, R; Tafreshi, A; Weinreb, RN

Published Date

  • April 24, 2012

Published In

Volume / Issue

  • 53 / 4

Start / End Page

  • 2199 - 2207

PubMed ID

  • 22410555

Pubmed Central ID

  • PMC3808189

Electronic International Standard Serial Number (EISSN)

  • 1552-5783

Digital Object Identifier (DOI)

  • 10.1167/iovs.11-8639


  • eng

Conference Location

  • United States