Table 2. nQi discrimination performance with different cut-off points in the combined dataset.

Misclassification cost (cost per FN/cost per FP)	Estimated cut-off point	Sensitivity	Specificity	Accuracy	TP	FN	TN	FP
1/1	0.078	0.71	0.84	0.78	30	12	36	7
2/1	0.075	0.74	0.79	0.76	31	11	34	9
1/2	0.105	0.55	0.95	0.75	23	19	41	2

TP: true positives, FN: false negatives, TN: true negatives, FP: false positives. The cut-off points have been automatically estimated by maximizing the generalized Youden Index³⁵ under three different misclassification costs assumptions: the cost for FN and FP is equal, the FN misclassification cost is twice the one for FP and that the FP misclassification cost is twice the one for FN.