A validated risk calculator to assess risk and rate of visual field progression in treated glaucoma patients

Carlos Gustavo de Moraes, Mitra Sehi, David S. Greenfield, Yun S. Chung, Robert Ritch, Jeffrey M. Liebmann

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

PURPOSE. The purpose of our study is to develop and validate a model to predict visual field (VF) outcomes in patients with treated glaucoma. METHODS. Data from 587 eyes with treated glaucoma evaluated in a cohort were used to develop two equations to predict VF outcomes, one estimating the risk of progression (%) and another estimating the global rate of VF sensitivity change (decibels [dB]/year). These equations, which included variables associated with VF progression in a multivariable model, then were tested in another cohort (n = 62 eyes) followed for at least 4 years. Agreement, discrimination, and calibration of the model in the validation sample were assessed as main outcome measures. RESULTS. The mean difference between observed and predicted global rates of sensitivity change was 0.13 dB/year (95% confidence interval [CI] = 0.06 to 0.18 dB/year) and the mean difference between observed and predicted final VF mean deviation (MD) values was 0.37 dB (95% CI=0.00 to 0.75 dB). The predictive model had moderate discriminative ability to estimate VF progression in the independent sample (c-index of 0.78, 95% CI = 0.59 to 0.97). CONCLUSIONS. To our knowledge, this is the first attempt to generate and validate a risk model for patients with treated glaucoma. The prediction model showed moderate accuracy in estimating future VF outcomes in an independent glaucoma population, and may be useful for the objective assessment of risk of progressive VF loss.

Original languageEnglish (US)
Pages (from-to)2702-2707
Number of pages6
JournalInvestigative Ophthalmology and Visual Science
Volume53
Issue number6
DOIs
StatePublished - May 2012

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience

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