Topographic Agreement of Retinal Nerve Fiber and Ganglion Cell Loss Improves Incipient Glaucoma Detection

To evaluate combinations of geographically corresponding retinal nerve fiber layer (RNFL) parameters and ganglion cell-inner plexiform layer (GCIPL) parameters for detection of incipient glaucoma (IG).

A cross-sectional study.

The early glaucoma (EG) exploratory cohort consisted of 156 diseased subjects and 199 age-matched controls. The IG validation cohort consisted of 75 diseased subjects and 247 age-matched controls. Only 1 eye from each subject was used.

Retinal nerve fiber layer and GCIPL scans were obtained with Cirrus HD-OCT. Linear regression was used to determine the degree of correlation between corresponding RNFL and GCIPL sector thinning in EG. Logistic regression models of parameter combinations were fit on the EG cohort, then used to generate receiver operating characteristic (ROC) curves. Fitted models were validated on the IG dataset. Diagnostic power was assessed by calculating area under the ROC curve (AUC).

Area under the ROC curve (AUC) RESULTS: In EG patients, inferotemporal GCIPL loss is moderately correlated to inferior RNFL loss (R² = 0.38), and supertemporal GCIPL loss is moderately correlated to superior RNFL loss (R² = 0.32). A logistic regression model of all these parameters combined improved significantly when these correlations were accounted for with interaction terms (ΔAIC = -17.4, ΔBIC = -9.7). The combined model performed strongly in diagnosing both EG (AUC = 0.969) and IG (AUC = 0.903) and outperformed all of the individual parameters in both EG and IG (unpaired bootstrapped AUC comparisons, P < 0.0001 for all).

Combining corresponding sectors of the GCIPL and RNFL, and factoring in their correlation, produces a model with strong diagnostic accuracy both in EG and IG. Attention to corresponding GCIPL and RNFL thickness loss in these sectors can help clinicians detect IG.

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