Skip to main content
. Author manuscript; available in PMC: 2017 Jan 16.
Published in final edited form as: J Alzheimers Dis. 2016 Aug 10;54(1):325–335. doi: 10.3233/JAD-160259

Table 2.

Diagnostic parameters for GNP, WIV and the combination of the two metrics across AD, MCI, and HC

HC versus AD HC versus MCI MCI versus AD
GNP AUC (±95% CI) 0.99 (0.99–1.0) 0.94 (0.92–0.96) 0.81 (0.78–0.85)
Sensitivity/Specificity 0.98/0.96 0.85/0.88 0.71/0.76
Youden Index 0.94 0.73 0.47
Cutoff# 0.86 −0.52 1.85
Classification Accuracy 94% 85% 74%
WIV AUC (±95% CI) 0.96 (0.95–0.98) 0.89 (0.86–0.91) 0.72 (0.68–0.76)
Sensitivity/Specificity 0.88/0.93 0.79/0.83 0.64/0.73
Youden Index 0.81 0.62 0.37
Cutoff 1.26 1.09 1.64
Classification Accuracy 90% 80% 70%
GNP+WIV AUC (±95% CI) 0.99 (0.99–1.0) 0.95 (0.94–0.97)* 0.81 (0.78–0.85)
Sensitivity/Specificity 0.98/0.97 0.85/0.93 0.71/0.76
Youden Index 0.95 0.78 0.47
Classification Accuracy 98% 94% 83%

Bold text indicated the best model for predicting group.

*

Overall AUC is significantly improved with the addition of a measure of variability (WIV).

#

GNP Cutoff scores are reported as a Z-score.

AD, Alzheimer’s disease; AUC, area under the curve; CI, confidence interval; GNP, global neuropsychological performance; HC, healthy participants; MCI, mild cognitive impairment; WIV, within-individual variability.