Discrimination of Glaucoma Patients From Healthy Individuals Using Combined Parameters From Spectral-domain Optical Coherence Tomography in an African American Population. Issue 3 (March 2016) - Blumberg, Dana M.; Dale, Elizabeth; Pensec, Noelle; Cioffi, George A; Radcliffe, Nathan; Pham, Michelle; Al-Aswad, Lama; Reynolds, Margaret; Ciarleglio, Adam
Abstract : Purpose: To create a multivariable predictive model for glaucoma in an exclusively African American population and to compare the performance of the model with individual structural parameters derived from SD-OCT. Patients and Methods: A total of 103 healthy eyes and 118 glaucomatous eyes of African American patients underwent SD-OCT optic disc and macular scanning. Twenty-seven optic nerve head, retinal nerve fiber layer (RNFL), and ganglion cell parameters were collected. A multivariable model was derived using a backward elimination variable selection procedure. Areas under the curve were used to measure the diagnostic performance of the individual parameters and the multivariable model. Results: The best performing parameters for glaucoma patients included inferior quadrant thickness (AUC=0.9239), average RNFL thickness (AUC=0.9209), sup2 RNFL thickness (AUC=0.9157), superior quadrant thickness (AUC=0.8906), and vertical CDR (AUC=0.8640). The best performing parameters for early glaucoma patients were sup2 RNFL thickness (AUC=0.8680), inferior quadrant thickness (AUC=0.8571), average RNFL thickness (AUC=0.8550), superior quadrant thickness (AUC=0.8420), and inf2 RNFL thickness (AUC=0.8420). The AUC of the multivariable model was 0.8918 for early glaucoma and 0.9744 for moderate/advanced glaucoma. There was some variability in the performance of the model based on disc size. Conclusions: These findings confirm that several individual RNFL, ONH, and GCA parameters have excellent diagnostic performance in differentiating glaucomatous patients from healthy patients in African American population. A multivariable model was developed and validated with high diagnostic accuracy.