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Felipe A. Medeiros, Linda M. Zangwill, Luciana M. Alencar, Christopher Bowd, Pamela A. Sample, Remo Susanna, Robert N. Weinreb; Detection of Glaucoma Progression with Stratus OCT Retinal Nerve Fiber Layer, Optic Nerve Head, and Macular Thickness Measurements. Invest. Ophthalmol. Vis. Sci. 2009;50(12):5741-5748. doi: https://doi.org/10.1167/iovs.09-3715.
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To evaluate and compare the ability of optical coherence tomography (OCT) retinal nerve fiber layer (RNFL), optic nerve head, and macular thickness parameters to detect progressive structural damage in glaucoma.
This observational cohort study included 253 eyes of 253 patients. Images were obtained annually with the Stratus OCT (Carl Zeiss Meditec, Inc., Dublin, CA) along with optic disc stereophotographs and standard automated perimetry (SAP) visual fields. The median follow-up time was 4.01 years. Progression was determined by the Guided Progression Analysis software for SAP (Carl Zeiss Meditec, Inc.) and by masked assessment of optic disc stereophotographs performed by expert graders. Random coefficient models and receiver operating characteristic (ROC) curves were used to evaluate the relationship between change in Stratus OCT parameters over time and progression as determined by SAP and/or stereophotographs.
From the 253 eyes, 31 (13%) showed progression over time by stereophotographs and/or SAP. Mean rates of change in average RNFL thickness were significantly higher for progressors compared with nonprogressors (−0.72 μm/y vs. 0.14 μm/y; P = 0.004), with sensitivity of 77% for specificity of 80%. RNFL parameters performed significantly better than ONH and macular thickness measurements in discriminating progressors from nonprogressors. The parameters with the largest ROC curve areas for each scanning area were inferior RNFL thickness (0.84), cup area (0.66), and inferior inner macula thickness (0.64).
Stratus OCT RNFL parameters discriminated between eyes progressing by visual fields or optic disc photographs and eyes that remained stable by these methods and performed significantly better than ONH and macular thickness parameters in detecting change over time.
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