NDLI: Combining spectral domain optical coherence tomography structural parameters for the diagnosis of glaucoma with early visual field loss.

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Combining spectral domain optical coherence tomography structural parameters for the diagnosis of glaucoma with early visual field loss.

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Combining spectral domain optical coherence tomography structural parameters for the diagnosis of glaucoma with early visual field loss.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Warren, Joshua L. Budenz, Donald L. Mwanza, Jean-Claude
Description	Author Affiliation: Mwanza JC ( Department of Ophthalmology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.)
Abstract	PURPOSE: To create a multivariable predictive model for glaucoma with early visual field loss using a combination of spectral-domain optical coherence tomography (SD-OCT) parameters, and to compare the results with single variable models. METHODS: Two hundred fifty-three subjects (149 healthy controls and 104 with early glaucoma) underwent optic disc and macular scanning using SD-OCT in one randomly selected eye per subject. Sixteen parameters (rim area, cup-to-disc area ratio, vertical cup-to-disc diameter ratio, average and quadrant RNFL thicknesses, average, minimum, and sectoral ganglion cell inner-plexiform layer [GCIPL] thicknesses) were collected and submitted to an exploratory factor analysis (EFA) followed by logistic regression with the backward elimination variable selection technique. Area under the curve (AUC) of the receiver operating characteristic (ROC), sensitivity, specificity, Akaike's information criterion (AIC), predicted probability, prediction interval length (PIL), and classification rates were used to determine the performances of the univariable and multivariable models. RESULTS: The multivariable model had an AUC of 0.995 with 98.6% sensitivity, 96.0% specificity, and an AIC value of 43.29. Single variable models yielded AUCs of 0.943 to 0.987, sensitivities of 82.6% to 95.7%, specificities of 88.0% to 94.0%, and AICs of 113.16 to 59.64 (smaller is preferred). The EFA logistic regression model correctly classified 91.67% of cases with a median PIL of 0.050 in the validation set. Univariable models correctly classified 80.62% to 90.48% of cases with median PILs 1.9 to 3.0 times larger. CONCLUSIONS: The multivariable model was successful in predicting glaucoma with early visual field loss and outperformed univariable models in terms of AUC, AIC, PILs, and classification rates.
ISSN	01460404
e-ISSN	15525783
DOI	10.1167/iovs.13-12749
Journal	Investigative Opthalmology & Visual Science
Issue Number	13
Volume Number	54
Language	English
Publisher	Association for Research in Vision and Ophthalmology
Publisher Date	2013-12-30
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Glaucoma Diagnosis Nerve Fibers Pathology Optic Disk Optic Nerve Diseases Retinal Ganglion Cells Vision Disorders Visual Fields Area Under Curve Imaging, Three-dimensional Intraocular Pressure Models, Statistical Ophthalmoscopy Roc Curve Scanning Laser Polarimetry Sensitivity And Specificity Tomography, Optical Coherence Visual Field Tests Comparative Study Research Support, Non-u.s. Gov't Discipline Ophthalmology
Content Type	Text
Resource Type	Article
Subject	Ophthalmology Sensory Systems Cellular and Molecular Neuroscience

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