The goal of this study was to evaluate the association between glaucoma and optic disc structural parameters and to determine whether these associations differ between African Americans and whites. Structural parameters describing the cup were vertical cup-to-disc ratio, cup volume and area, cup shape, and the mean and maximum depth of the cup. Structural parameters describing the neuroretinal rim were rim volume, global rim-to-disc ratio, and rim area. Disc margin parameters included in the model were RNFL thickness, contour line modulation (CLM) ratios for the inferior-to-temporal and superior-to-temporal sectors, and the maximum elevation and depression of the contour line.
Logistic regression was used to calculate the association between glaucoma and cup, rim, and disc margin parameters using odds ratios and 95% confidence intervals. Before including structural parameters in the logistic regression models, the distributions of each of these normally continuous variables were evaluated for the total study population, and the median value was used to categorize each variable. To determine the set of structural parameters that demonstrated significant, independent associations with glaucoma, several logistic regression models were evaluated. First, the association between glaucoma and each structural parameter was estimated separately. Then, a multivariate model was estimated that included all cup structural parameters in a single model that were independently significant; similar models were evaluated for rim and disc margin parameters. From these three separate full models, only those variables that demonstrated significant, independent associations in each model were retained in reduced models. Finally, the cup, rim, and disc margin parameters identified as being independently associated with glaucoma in these reduced models were then included in a single multivariate model. In the context of this model, only those variables that retained statistical significance were maintained in the final model. To account for the effect of differences in optic disc area, this parameter was included in the multivariate model at each level of interaction in constructing the final model. Thus, the final model is composed of the parameters with the best independent associations with glaucoma, independent of the effect of disc area. This approach was used for the total study sample, and then separately for African Americans and whites. Finally, to account for the intercorrelation of eyes within persons, generalized estimating equations were used for these calculations.
The use of median cut points that ignore disease and race-specific distributions has both advantages and disadvantages. With respect to the former, this approach provides a set of variables that can be readily compared across groups. If different cut points had been chosen for specific groups, between-group comparisons (e.g., blacks versus whites) would be impaired. With respect to disadvantages, the use of a median cut point may hide or exaggerate the true association. Unfortunately, when the sample size is small, as in this study, the creation of tertiles or higher order cut points is difficult. Thus, evaluating the actual nature of the association beyond binary variables is problematic. Ultimately, when the true nature of the relationships is not known and sample size is limited, the use of arbitrary cut points, as in this study, reflects a conservative approach.