Table 3 shows the results of the ROC regression model investigating the effect of disease severity on the accuracy of the Cirrus parameter average thickness. The severity of disease, as measured by the VFI, had a significant influence on the diagnostic performance, as indicated by the statistically significant value attributed to the coefficient representing severity (β
1 = −0.038; 95% CI, −0.072 to −0.016). As expected, this parameter performed better in patients with more severe disease. There was a tendency for disease severity to exert a relatively greater effect on lower false-positive rates (i.e., higher specificities), as indicated by the negative coefficient for the term: Severity × Φ
−1(
q). However, this correlation was not statistically significant (β
2 = −0.006; 95% CI, −0.043 to 0.08).
Figure 2 shows ROC curves for arbitrary values of VFI. The areas under the ROC curves for arbitrary VFIs of 100%, 90%, 80%, and 70% were 0.822, 0.886, 0.932, and 0.962, respectively (
Table 4).
Figure 3 shows sensitivities at fixed specificities for detection of glaucoma according to levels of disease severity for the average thickness parameter. As expected, sensitivities were significantly higher for worse disease severities. A similar effect was observed when using MD as an indicator of disease severity in our ROC regression model. We obtained AUCs of 0.848, 0.917, and 0.959 for MD values of 0, −6, and −12, respectively. Using PSD as an indicator of severity, we found AUCs of 0.801, 0.932, and 0.983 for values of 0, 6, and 12 dB, respectively.