Table 3.

Classification success, estimated through leave-one-out cross validation, of the two tests sets: The primary, general test set comprising three different DFA models, A.1-A.3, to identify EGFRmut, KRASmut and EML4-ALK (cf. Figure 2), and the secondary, specific test set, comprising six further DFA models, B.1-B.6, that distinguish between specific genetic mutations (cf. Figure 3).

	Test	Test group	Control group	TP	TN	FP	FN	Sensitivity [%]a	Specificity [%]b	Accuracy [%]c
Primary (general) tests	A.1	EGFRmut	KRASmut; EML4-ALK; wt to all	7	27	0	3	70	100	92
	A.2	KRASmut	EGFRmut; EML4-ALK; wt to all	13	18	5	1	93	78	84
	A.3	EML4-ALK	EGFRmut; KRASmut; wt to all	5	29	0	3	63	100	92
Secondary (specific) tests	B.1	EGFRmut	KRASmut	10	13	1	0	100	93	96
	B.2	EGFRmut	EML4-ALK	10	6	2	0	100	75	89
	B.3	KRASmut	EML4-ALK	14	7	1	0	100	88	96
	B.4	EGFRmut	wt to all	9	4	1	1	90	80	87
	B.5	KRASmut	wt to all	12	4	1	2	86	80	84
	B.6	EML4-ALK	wt to all	7	5	0	1	88	100	92

The secondary test set is designed to deliver useful additional information in the case of an ambiguous sample classification through the primary tests.

^aSensitivity = TP/(TP + FN).

^bSpecificity = TN/(TN + FP).

^cAccuracy = (TP + TN)/(TP + TN + FP + FN).