Predicting Development of Glaucomatous Visual Field Conversion Using Baseline Fourier-Domain Optical Coherence Tomography  

Oleh:

Xinbo Zhang ; Loewen, Nils ; Tan, Ou ; Greenfield, David S. ; Schuman, Joel S. ; Varma, Rohit ; Huang, David

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: American Journal of Ophthalmology (keterangan: ada di ClinicalKey) vol. 163 (Mar. 2016), page 29-37.
Topik: Glaucomatous Visual; Fourier-Domain Optical Coherence Tomography
Fulltext: A12 v163 p29 kelik2016.pdf (412.67KB)

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Perpustakaan FK Nomor Panggil: A12.K Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Purpose: To predict the development of glaucomatous visual field (VF) defects using Fourier-domain optical coherence tomography (FD OCT) measurements at baseline visit. Design: Multicenter longitudinal observational study. Glaucoma suspects and preperimetric glaucoma participants in the Advanced Imaging for Glaucoma Study. Methods: The optic disc, peripapillary retinal nerve fiber layer (NFL), and macular ganglion cell complex (GCC) were imaged with FD OCT. VF was assessed every 6 months. Conversion to perimetric glaucoma was defined by VF pattern standard deviation (PSD) or glaucoma hemifield test (GHT) outside normal limits on 3 consecutive tests. Hazard ratios were calculated with the Cox proportional hazard model. Predictive accuracy was measured by the area under the receiver operating characteristic curve (AUC). Results: Of 513 eyes (309 participants), 55 eyes (46 participants) experienced VF conversion during 41 ± 23 months of follow-up. Significant (P < .05, Cox regression) FD OCT risk factors included all GCC, NFL, and disc variables, except for horizontal cup-to-disc ratio. GCC focal loss volume (FLV) was the best single predictor of conversion (AUC = 0.753, P < .001 for test against AUC = 0.5). Those with borderline or abnormal GCC-FLV had a 4-fold increase in conversion risk after 6 years (Kaplan-Meier). Optimal prediction of conversion was obtained using the glaucoma composite conversion index (GCCI) based on a multivariate Cox regression model that included GCC-FLV, inferior NFL quadrant thickness, age, and VF PSD. GCCI significantly improved predictive accuracy (AUC = 0.783) over any single variable (P = .04). Conclusions: Reductions in NFL and GCC thickness can predict the development of glaucomatous VF loss in glaucoma suspects and preperimetric glaucoma patients.

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