Table 5.

AUC for Glaucoma Screening Parameters in High-Risk Subgroups of the LALES

Screening Parameter	History of Diabetes (n = 1040)	Family History of Glaucoma (n = 488)	Age >65 y (n = 1204)	Any High Risk Group (n = 2263)	Total Population (N = 6082)
Vertical C/D ratio	.918	.900	.885	.895	.900
MD	.826	.833	.799	.835	.861
IOP	.612	.624	.668	.668	.705
CCT	.586	.553	.572	.578	.549
FN	.674	.666	.588	.612	.646
PSD	.809	.860	.806	.835	.868

n, total number of participants with the risk factor. The ROC for each screening parameter plots sensitivity on the y-axis and 1 - specificity on the x-axis. The sensitivity and specificity of each potential cutoff for the screening parameter is plotted to give a curve extending from the lower left corner to the upper right corner of the graph. A perfectly diagonal line would indicate that any gain in sensitivity is exactly offset by a decrease in specificity. A better performing test would rise rapidly so that the curve approaches the upper left corner of the figure. In the case of a diagonal line, the AUC would be 0.5; the maximum AUC would be 1.0. There were modest differences in the AUCs for each of the risk groups, but regardless of risk group, vertical C/D ratio is consistently the best performing parameter. MD and PSD show relatively good AUCs, but were not independent predictors in our logistic regression model, whereas IOP and CCT show rather weak AUCs, but were independent predictors in the logistic regression model, indicating that MD and PSD, but not IOP and CCT, are closely associated with other independent predictors in the model.