Multivariate Normative Comparison, a Novel Method for Improved Use of Retinal Nerve Fiber Layer Thickness to Detect Early Glaucoma.
Jacqueline Chua, Florian Schwarzhans, Damon Wong, Chi Li, Rahat Husain, Jonathan G Crowston, Shamira A Perera, Chelvin C A Sng, Monisha E Nongpiur, Shivani Majithia, Yih Chung Tham, Sahil Thakur, Soh Zhi Da, Ching-Yu Cheng, Tin Aung, Georg Fischer, Clemens Vass, Leopold Schmetterer
Summary
The multivariate normative database of RNFL showed better glaucoma discrimination capability than conventional age-matched comparisons, suggesting that accounting for demographic and anatomic variance in RNFL thickness may have usefulness in improving glaucoma detection.
Abstract
PURPOSE
Detection of early glaucoma remains limited with the conventional analysis of the retinal nerve fiber layer (RNFL). This study assessed whether compensating the RNFL thickness for multiple demographic and anatomic factors improves the detection of glaucoma.
DESIGN
Cross-sectional study.
PARTICIPANTS
Three hundred eighty-seven patients with glaucoma and 2699 healthy participants.
METHODS
Two thousand six hundred ninety-nine healthy participants were enrolled to construct and test a multivariate compensation model, which then was applied in 387 healthy participants and 387 patients with glaucoma (early glaucoma, n = 219; moderate glaucoma, n = 97; and advanced glaucoma, n = 71). Participants underwent Cirrus spectral-domain OCT (Carl Zeiss Meditec) imaging of the optic disc and macular cubes. Compensated RNFL thickness was generated based on ethnicity, age, refractive error, optic disc (ratio, orientation, and area), fovea (distance and angle), and retinal vessel density. The RNFL thickness measurements and their corresponding areas under the receiver operating characteristic curve (AUCs) were obtained.
MAIN OUTCOME AND MEASURES
Measured and compensated RNFL thickness measurements.
RESULTS
After applying the Asian-specific compensation model, the standard deviation of RNFL thickness reduced, where the effect was greatest for Chinese participants (16.9%), followed by Malay participants (13.9%), and Indian participants (12.1%). Multivariate normative comparison outperformed measured RNFL for discrimination of early glaucoma (AUC, 0.90 vs. 0.85; P < 0.001), moderate glaucoma (AUC, 0.94 vs. 0.91; P < 0.001), and advanced glaucoma (AUC, 0.98 vs. 0.96; P < 0.001).
CONCLUSIONS
The multivariate normative database of RNFL showed better glaucoma discrimination capability than conventional age-matched comparisons, suggesting that accounting for demographic and anatomic variance in RNFL thickness may have usefulness in improving glaucoma detection.
Keywords
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Discussion
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