Discrimination of glaucoma patients from healthy individuals using combined parameters from spectral-domain optical coherence tomography in an African American Population

Dana M. Blumberg, Elizabeth Dale, Noelle Pensec, George A. Cioffi, Nathan Radcliffe, Michelle Pham, Lama Al-Aswad, Margaret Reynolds, Adam Ciarleglio

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

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.

Original languageEnglish
Pages (from-to)e196-e203
JournalJournal of Glaucoma
Volume25
Issue number3
DOIs
StatePublished - Mar 23 2016

Keywords

  • Diagnosis
  • Glaucoma
  • OCT

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