Multivariable normative comparison, a novel method for improved use of the retinal nerve fiber layer thickness to detect early glaucoma.

Purpose Detection of early glaucoma remains limited with the conventional analysis of the retinal nerve fiber layer (RNFL). To assess whether compensating the RNFL thickness for multiple demographic and anatomical factors improves the detection of glaucoma. Design Cross-sectional study METHODS: 2699 healthy participants were enrolled to construct and test a multivariable compensation model, which was then applied in 387 healthy and 387 glaucoma participants (early, n=219; moderate, n=97; and, advanced, n=71). Participants underwent Cirrus spectral-domain optical coherence tomography (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. RNFL thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were obtained. Main outcome and measures Measured and compensated RNFL thickness measurements RESULTS: After applying the Asian-specific compensation model, the standard deviation (SD) of RNFL thickness reduced, where the effect was greatest for Chinese (16.9%), followed by Malays (13.9%) and then Indians (12.1%). Multivariable normative comparison outperformed measured RNFL for discrimination of early glaucoma (AUC=0.90 vs 0.85; P Conclusions The multivariable normative database of RNFL showed better glaucoma discrimination capability than conventional age-matched comparisons, suggesting there may be utility in accounting for demographic and anatomical variance in RNFL thickness to improve glaucoma detection.