Online data supplement
Exhaled nitric oxide and asthma control: a longitudinal
study in unselected patients
____________________________________________
Alain Michils* PhD, Sandra Baldassarre* MD,
Alain Van Muylem* PhD
*
Chest Department – Erasme University Hospital – Brussels, Belgium
MATERIAL AND METHODS
Statistical methods
1. Intrinsic characteristics of an index
1.1. Sensitivity and specificity
If N events are rated as positive or negative (e.g. positive = well-controlled asthma; negative
= not-well controlled asthma) by a reference method (Gold Standard: GS), the ability of an
index to discriminate between these complementary states, for a given cut-off value, may be
assessed by using a contingency table. The index is considered as positive or negative
depending on its position relative to the cut-off value. The contingency table appears like
GS positive
GS negative
n+
n-
Index positive
TP
FP
Index negative
FN
TN
where n+ an n- are the amounts of positive and negative events (N = n+ + n-) according to the
Gold standard, respectively. TP and TN are the amounts of true positive and true negative
events, respectively; i.e. the amounts of events correctly rated by the index. FP and FN are the
amounts of false positive and false negative events, respectively, i.e. the amounts of events
incorrectly rated by the index.
From the contingency table, sensitivity (Se) and specificity (Sp) may be derived by
Se = TP/n+
(1)
Sp = TN/n-
(2)
Se and Sp are intrinsic characteristics of the index (for this given cut-off value). Se and Sp are
independent from the prevalence, the latter being defined as the positive events rate in a
considered context (the "prior" probability of a positive event). From the contingency table,
the prevalence is equal n+/N.
1.2. ROC curve
A contingency table may be constructed, and sensitivity and specificity computed, for a range
of cut-off values. The Receiving Operator Characteristics (ROC) curve is the true positive rate
(sensitivity) as a function of the false positive rate (1-specificity) for the considered range of
cut-off values. This curve allows visually assessing the relative "quality" of several indexes.
It also allows "choosing" an optimal cut-off value for a given index according to investigator's
criteria.
The area under the ROC curve (AUC) may be computed and its difference relative to 0.5 may
be statistically assessed. If AUC not different from 0.5 (which is the area under the first
bisector), it means that the considered index is as useful as tossing a coin.
1.3. The Youden's index
The Youden's index (J), is the difference between the true positive rate and the false positive
rate. Maximizing this index allows to find, from the ROC curve, an optimal cut-off point
independently from the prevalence. According to its definition, J is the vertical distance
between the ROC curve and the first bisector (or chance line). If F(x) is the function
describing the ROC curve, with x = 1-specificity, we may write
J(x)= F(x)-x
(3)
When J is maximal, J'(x) = 0, where J' is the derivative of J.
From Eq. 1:
J'(x)= F'(x) -1,
where F' is the derivative of F.
(4)
Hence, when J is maximal, F'(x) = 1, meaning that the tangent to the ROC curve is parallel to
the first bisector (slope = 1). It implies that, around this point, a gain (or a loss) in specificity
results in a loss (or a gain) of the same amplitude in sensitivity.
2. Predictive values
Positive (PPV) and negative (NPV) predictive values are the probability to rate correctly an
event using the index; i.e. the probability that the event is actually positive (negative) if the
index is positive (negative). They may be derived from the contingency table by
PPV = TP/(TP+FP)
(5)
NPV = TN/(TN+FN)
(6)
Contrary to Se and Sp, PPV and NPV are dependent on the context through the prevalence. It
implies that PPV and NPV, derived from the contingency table, may be used only if n+/N is
close to the actual prevalence of the considered event in the considered "real-life" context.
The accuracy (Acc) defined as (TP+TN)/N is also context dependent.
It is to be noted that PPV and NPV may be computed from Se and Sp (intrinsic
characteristics) and any given prevalence P (linked to a specific context) by the Baye's
formula:
(7)
(8)
.
RESULTS
1. Transversal FENO-ACQ score relationship
Figure 1 shows individual FENO values at study onset as a function of the ACQ score. Panels
A (closed circles), B (open circles), C (open triangles), and D (closed triangles) present ICS
naïve patients, patients treated with low ICS dose, high-to-moderate ICS dose (excluding
severe asthmatics) and patients with severe asthma, respectively.
B
250
250
FENO (ppb)
FENO (ppb)
A
50
10
50
10
1
1
0
2
3
4
5
6
ACQ score
0
D
250
50
10
1
2
3
4
5
6
5
6
ACQ score
250
FENO (ppb)
FENO (ppb)
C
1
1
50
10
1
0
1
2
3
4
ACQ score
5
6
0
Figure 1
1
2
3
4
ACQ score
2. Additionnal cut-off values
Tables 1 to 12 present, for a range of cut-off value of FENO and FEV1 :
1. The statistical significance (p) of rejecting the null hypothesis AUC=0.
2. The amounts of true positive (TP), false negative (FN), true negative (TN) and false
positive (FP) events (contingency tables).
3. Sensitivity (Se) and specificity (Sp) (intrinsic characteristics)
4. Positive (PPV), negative (NPV) positive values and accuracy (Acc) (context
dependent characteristics).
Table 1: Cross-sectional assessment of asthma control in the whole population
FENO
P&
n+
n-
<0.001
Cut-off
(ppb)*
┌ TP
└ FN
┌ TN
└ FP
25
35
45
55
65
49
43
167
65
66
26
137
95
76
16
114
118
79
13
81
151
83
9
60
172
Se (%)
Sp (%)
53
72
72
59
83
49
86
35
90
26
PPV (%)
NPV (%)
Acc (%)
43
80
67
41
84
62
40
88
59
34
86
49
33
87
44
FEV1
p&
n+
n-
0.089
Cut-off
(%pred)*
┌ TP
└ FN
┌ TN
└ FP
75
80
85
90
95
80
12
51
181
75
17
74
158
68
24
97
135
48
44
121
111
34
58
153
79
Se (%)
Sp (%)
87
22
82
32
74
42
52
52
37
66
PPV (%)
NPV (%)
Acc (%)
31
81
40
32
81
46
33
80
51
30
73
52
30
73
58
Data are presented as &: statistical significance of rejecting AUC=0.5; *: boldface = cut-off value derived
from Youden's index maximization. TP, FN, TN and FP are the amounts of true positive, false negative,
true negative, and false positive cases, respectively. n+ and n- are the amounts of positive and negative
events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity, specificity, positive and negative predictive
values, and accuracy, respectively. A positive event is defined as a well-controlled asthma. A true positive
case is defined as FENO<cut-off or FEV1>cut-off associated with a well-controlled asthma.
Table 2: Cross-sectional assessment of asthma control, according to current ICS dose
ICS naïve
0.039
p&
Cut-off
(ppb)*
FENO
0<ICS dose 500#
0.036
ICS dose > 500#
0.84
25 35 45
55 65
25 35 45 55 65
25 35 45 55 65
6
11
108
17
9 10
8 7
93 84
32 41
10 12
7 5
64 49
61 76
28
18
36
20
16 23 27 27 29
13 6 2 2 0
24 16 11 7 4
27 35 40 44 47
35 53 59
86 74 67
59 71
51 39
61 76 87 91 91
64 50 34 21 16
55 79 93
47 31 22
PPV (%) 26 22 20
NPV (%) 91 92 92
Acc (%) 80 72 68
14 14
90 91
52 43
58 56 52 49 47
67 72 76 75 69
63 62 58 53 50
37 40 40 38 38
65 73 85 78 100
50 49 48 43 41
FEV1
0<ICS dose 500#
0.22
ICS dose > 500#
0.42
n+┌ TP
└ FN
┌ TN
n└ FP
Se (%)
Sp (%)
ICS naïve
0.37
p&
Cut-off
(%pred)*
35 40 42 42
11 6 4 4
28 19 12 9
28 37 44 47
93 100
14 8
75
80 85
90 95
75 80 85 90 95
75 80 85 90 95
16
1
23
102
15 12
2 5
34 48
91 77
8 7
9 10
64 78
61 47
44 41 37 28
2 5 9 18
11 17 25 26
45 39 31 30
20
9
17
34
94 88 71
18 27 38
47 41
51 62
96 89 80 61 39
20 30 45 46 63
PPV (%) 14 14 13 12 13
NPV (%) 96 94 91 88 89
Acc (%) 27 35 42 51 60
49 51 54 48 46
85 77 74 59 56
54 57 61 53 52
n+ ┌TP
└FN
┌TN
n└FP
Se (%)
Sp (%)
18
28
35
21
19
10
22
29
19
10
27
24
12 9
17 20
33 40
18 11
69 66 64
33 43 52
41 31
65 78
37 40 44 40 45
65 69 73 66 67
46 51 58 56 61
Data are presented as ; #: g equ BDP.day-1; &: statistical significance of rejecting AUC=0.5; *: boldface
= cut-off value derived from Youden's index maximization in the whole population. TP, FN, TN and FP
are the amounts of true positive, false negative, true negative, and false positive cases, respectively. n+ and
n- are the amounts of positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity,
specificity, positive and negative predictive values, and accuracy, respectively. A positive event is defined
as a well-controlled asthma. A true positive case is defined as FENO<cut-off or FEV1>cut-off associated
with a well-controlled asthma.
Table 3: Assessment of asthma control optimization in non-severe asthma
p&
Cut-off
(%)*
n+┌ TP
└ FN
┌ TN
n└ FP
Whole population
<0.001
FENO
ICS dose 500#
<0.001
ICS dose > 500#
<0.001
-20 -30 -40 -50 -60
-20 -30 -40 -50 -60
-20 -30 -40 -50 -60
71
21
99
60
47
9
35
15
24
12
64
45
63
29
110
49
59
33
124
35
30
62
145
14
41 39 30 18
15 17 26 38
40 42 44 48
10 8 6 2
23
13
71
38
19
17
82
27
13
23
90
19
12
24
96
13
47 33
84 91
84 73 70 54 32
70 80 84 88 96
67 63 53
59 65 75
PPV (%) 54 56 63 63 68
NPV (%) 83 79 79 73 70
Acc (%) 68 69 73 71 70
76 80 83 83 90
80 73 71 63 56
77 76 76 70 62
35 38 41 41 48
84 85 83 80 80
61 65 70 71 74
Whole population
<0.001
FEV1
ICS dose 500#
0.21
ICS dose > 500#
<0.001
+5 +10 +15 +20 +25
+5 +10 +15 +20 +25
+5 +10 +15 +20 +25
41
51
110
49
11
81
149
10
19 13 5 5 3
37 43 51 51 53
35 41 46 49 49
15 9 4 1 1
22
14
75
34
14 12
93 94
34 23 9 9 5
70 82 92 98 98
61 53 50
69 78 86
PPV (%) 46 49 52 54 52
NPV (%) 68 68 67 65 65
Acc (%) 60 63 64 64 64
56 59 56 83 75
49 49 47 49 48
51 51 48 51 49
39 44 55 42 50
84 83 84 78 78
67 72 77 73 75
Se (%)
Sp (%)
p&
Cut-off
(%)*
n+ ┌TP
└FN
┌TN
n└FP
Se (%)
Sp (%)
77 69 64
62 69 78
43
49
134
25
32
60
126
33
23
69
138
21
45 35 25
69 79 87
13
79
148
11
19
17
85
24
36 33
83 88
18 8 8
18 28 28
94 98 101
15 11 8
22 22
90 93
Data are presented as ; #: g equ BDP.day-1; &: statistical significance of rejecting AUC=0.5; *: boldface
= cut-off value derived from Youden's index maximization in the whole population. TP, FN, TN and FP
are the amounts of true positive, false negative, true negative, and false positive cases, respectively. n+ and
n- are the amounts of positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity,
specificity, positive and negative predictive values, and accuracy, respectively. A positive event is defined
as an optimization of asthma control. A true positive case is defined as FENO changecut-off or FEV1
change cut-off associated with an optimization of asthma control between consecutive visits.
Table 4: Assessment of asthma control improvement in severe asthma.
FENO
p&
n+
n-
<0.001
Cut-off
(%)*
┌ TP
└ FN
┌ TN
└ FP
-5
-10
-15
-20
-25
23
9
24
17
23
9
26
15
23
9
29
12
22
10
30
11
20
12
31
10
Se (%)
Sp (%)
72
58
72
64
72
70
69
73
63
76
PPV (%)
NPV (%)
Acc (%)
58
73
64
61
74
67
66
76
71
67
75
71
67
72
70
FEV1
p&
n+
n-
Cut-off
(%)*
┌ TP
└ FN
┌ TN
└ FP
<0.001
+5
+10
+15
+20
+25
23
9
25
16
20
12
29
12
17
15
33
8
14
18
36
5
12
20
36
5
Se (%)
Sp (%)
72
62
63
71
53
81
44
89
38
89
PPV (%)
NPV (%)
Acc (%)
59
74
66
63
71
67
68
69
68
74
67
68
71
64
66
Data are presented as &: statistical significance of rejecting AUC=0.5; *: boldface = cut-off value
derived from Youden's index maximization. TP, FN, TN and FP are the amounts of true positive, false
negative, true negative, and false positive cases, respectively. n+ and n- are the amounts of positive and
negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity, specificity, positive and negative
predictive values, and accuracy, respectively. A positive event is defined as an improvement of asthma
control. A true positive case is defined as FENO changecut-off or FEV1 change cut-off associated
with an improvement of asthma control between consecutive visits.
Table 5: Assessment of loss of optimal asthma control in non-severe asthma
Whole population
0.021
FENO
ICS dose 500#
0.002
ICS dose > 500#
0.39
+10 +20 +30 +40 +50
+10 +20 +30 +40 +50
+10 +20 +30 +40 +50
24
15
69
56
16
23
90
35
15 14 14 11 10
4 5 5 8 9
44 49 54 57 58
41 36 31 28 27
9 9 7 6 6
11 11 13 14 14
26 27 28 31 33
14 13 12 9 7
44 41
70 72
79 74 74 58 53
52 58 64 67 68
45 45 35
65 68 70
PPV (%) 30 32 33 31 31
NPV (%) 82 83 82 80 80
Acc (%) 57 59 63 64 65
27 28 31 28 27
92 91 92 88 87
57 61 65 65 65
39 41 37 40 46
70 71 68 69 70
58 60 58 62 65
Whole population
0.075
FEV1
ICS dose 500#
0.51
ICS dose > 500#
0.062
-5 -10 -15 -20 -25
-5 -10 -15 -20 -25
-5 -10 -15 -20 -25
18
21
94
31
7 4 3 2 1
12 15 16 17 18
63 77 79 83 83
22 8 6 2 2
11 9 8 4 3
9 11 12 16 17
31 35 36 38 40
9 5 4 2 0
13 8
97 99
37 21 16 11 5
74 91 93 98 98
55 45 40
78 88 90
PPV (%) 37 48 50 56 75
NPV (%) 82 81 80 78 78
Acc (%) 68 76 76 77 77
24 33 33 50 33
84 84 83 83 82
67 78 79 82 81
55 64 67 67 100
78 76 75 70 70
70 73 73 70 72
p&
Cut-off
(%)*
n+┌ TP
└ FN
┌ TN
n└ FP
Se (%)
Sp (%)
p&
Cut-off
(%)*
n+ ┌TP
└FN
┌TN
n└FP
Se (%)
Sp (%)
24
15
73
52
21
18
83
42
62 62 54
55 58 66
14
25
110
15
17
22
88
37
10 5 3
29 34 36
115 121 124
10 4 1
46 36 26
75 88 92
30 30
78 83
20 15
95 100
Data are presented as #: g equ BDP.day-1; &: statistical significance of rejecting AUC=0.5; *: boldface =
cut-off value derived from Youden's index maximization in the whole population. TP, FN, TN and FP are
the amounts of true positive, false negative, true negative, and false positive cases, respectively. n + and nare the amounts of positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity,
specificity, positive and negative predictive values, and accuracy, respectively. A positive event is defined
as a loss of optimal asthma control. A true positive case is defined as FENO changecut-off or FEV1
change cut-off associated with a loss of optimal asthma control between consecutive visits.
Table 6: Assessment of asthma control worsening in severe asthma.
FENO
p&
Cut-off
(%)*
0.008
+5
+10
+15
+20
+25
15
10
37
25
14
11
38
24
13
12
42
20
13
12
51
25
12
13
43
19
Se (%)
Sp (%)
58
60
56
62
52
67
51
68
48
69
PPV (%)
NPV (%)
Acc (%)
38
79
62
37
78
60
39
78
63
34
81
63
39
77
63
n+ ┌ TP
└ FN
┌ TN
n└ FP
FEV1
p&
Cut-off
(%)*
<0.001
-5
-10
-15
-20
-25
14
11
48
14
11
14
53
9
7
18
55
7
3
22
59
3
2
23
59
3
Se (%)
Sp (%)
57
78
44
86
26
88
13
95
7
95
PPV (%)
NPV (%)
Acc (%)
50
81
71
55
79
74
50
75
71
50
73
71
40
72
70
n+ ┌ TP
└ FN
┌ TN
n└ FP
Data are presented as &: statistical significance of rejecting AUC=0.5; *: boldface = cut-off value
derived from Youden's index maximization. TP, FN, TN and FP are the amounts of true positive, false
negative, true negative, and false positive cases, respectively. n+ and n- are the amounts of positive and
negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity, specificity, positive and negative
predictive values, and accuracy, respectively. A positive event is defined as worsening of asthma control. A
true positive case is defined as FENO changecut-off or FEV1 change cut-off associated with an asthma
control worsening between consecutive visits.
Table 7: Prediction of asthma control optimization in non-severe asthma
p&
Cut-off
(ppb)*
Whole population
0.018
FENO
ICS dose 500#
0.047
ICS dose > 500#
0.038
15 25 35
45 55
15 25 35 45 55
15 25 35 45 55
62 57 50
3 8 15
6 18 40
77 65 43
42
23
46
37
38 35 32 28
3 6 9 13
3 5 10 12
22 20 15 13
23 22 20 14 8
1 2 4 10 16
3 14 30 35 44
55 44 28 23 14
95 88 77
7 22 48
65 47
55 70
93 85 79 68 54
12 20 39 48 56
96 92 83
5 24 52
PPV (%) 45 47 54 53 55
NPV (%) 67 69 73 67 63
Acc (%) 46 51 61 59 60
63 64 68 68 67
50 45 53 48 42
62 61 64 61 55
29 33 42 38 36
75 88 88 78 73
32 44 61 60 63
FEV1
ICS dose 500#
0.86
ICS dose > 500#
0.96
70 75
55 60 67 70 75
55 60 67 70 75
60 58 55
5 7 10
9 12 19
74 71 64
53
12
19
64
44
21
33
50
39 38 36 34 31
2 3 5 7 10
3 3 2 3 4
22 22 22 22 21
21 21 20 19
3 3 4 5
6 9 16 17
52 49 42 41
92 89 85
11 15 23
82 67
23 40
95 93 87 83 76
12 12 12 12 16
88 88 83
10 16 28
PPV (%) 45 45 46 45 47
NPV (%) 64 63 66 61 61
Acc (%) 47 47 50 49 52
64 63 62 61 60
60 50 38 30 29
64 62 59 56 53
29 30 32 32 31
67 75 80 77 73
33 37 44 44 51
n+┌ TP
└ FN
┌ TN
n└ FP
Se (%)
Sp (%)
p&
Whole population
0.49
Cut-off
55 60 67
(%pred)*
n+ ┌ TP
└ FN
┌ TN
n└ FP
Se (%)
Sp (%)
31
34
58
25
22
19
14
11
58 33
60 76
13
11
29
29
79 54
29 50
Data are presented as ; #: g equ BDP.day-1; population; &: statistical significance of rejecting AUC=0.5;
*
: boldface = cut-off value derived from Youden's index maximization in the whole. TP, FN, TN and FP
are the amounts of true positive, false negative, true negative, and false positive cases, respectively. n+ and
n- are the amounts of positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity,
specificity, positive and negative predictive values, and accuracy, respectively. A positive event is defined
as an optimisation of asthma control. A true positive case is defined as FENO valuecut-off or a FEV1
value cut-off at initial visit associated with asthma control optimization at the subsequent visit.
Table 8: Prediction of a loss of optimal asthma control within 3 months in non-severe
asthma.
FENO
p&
Cut-off
(ppb)*
0.047
10
20
30
40
50
11
0
5
45
9
2
17
33
9
2
27
23
8
3
35
15
3
8
41
9
Se (%)
Sp (%)
10
9
86
34
86
53
70
69
29
81
PPV (%)
NPV (%)
Acc (%)
10
100
26
21
89
43
28
93
59
35
92
70
25
84
72
n+ ┌ TP
└ FN
┌ TN
n└ FP
FEV1
p&
Cut-off
(%pred)*
0.51
70
75
78
85
90
2
9
45
5
2
9
40
10
5
6
38
12
5
6
31
19
5
6
26
24
Se (%)
Sp (%)
18
90
18
80
46
76
46
62
46
52
PPV (%)
NPV (%)
Acc (%)
29
83
77
17
82
69
29
86
70
21
84
59
17
81
51
n+ ┌ TP
└ FN
┌ TN
n└ FP
Data are presented as &: statistical significance of rejecting AUC=0.5; *: boldface = cut-off value derived
from Youden's index maximization in the whole population. TP, FN, TN and FP are the amounts of true
positive, false negative, true negative, and false positive cases, respectively. n + and n- are the amounts of
positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity, specificity, positive
and negative predictive values, and accuracy, respectively. A posiive event is defined as a loss of optimal
control. A valuetrue positive case is defined as FENO cut-off value or FEV1 cut-off value at initial
visit associated with a loss of optimal asthma control at the subsequent visit (within 3 months).
2. Assessment of asthma control change by absolute FENO change
Table 9: assessment of asthma control optimization by FENO in non-severe asthma
p&
Cut-off
(ppb)*
┌ TP
n+
└ FN
┌ TN
n└ FP
Whole population
<0.001
ICS dose 500#
<0.001
ICS dose > 500#
0.002
-5 -10 -15 -20 -25
-5 -10 -15 -20 -25
-5 -10 -15 -20 -25
74
18
91
68
48
8
34
16
25
11
58
51
65
27
110
49
55
37
126
33
42
50
142
17
42
14
38
12
38 33 30
18 23 26
40 41 44
10 9 6
23
13
73
36
17
19
85
24
15
21
94
15
12
24
98
11
52 46
84 89
86 75 68 59 54
68 76 80 82 88
69 64 47
53 67 78
PPV (%) 52 57 63 66 71
NPV (%) 83 80 77 75 74
Acc (%) 66 70 72 73 73
75 78 79 79 83
81 73 69 64 63
77 75 74 70 70
33 39 41 50 52
84 85 82 82 80
57 66 70 75 76
Se (%)
Sp (%)
80 71 60
57 69 79
48
44
134
25
42 33
86 90
Data are presented as #: g equ BDP.day-1; &: statistical significance of rejecting AUC=0.5; *: boldface =
cut-off value derived from Youden's index maximization in the whole population. TP, FN, TN and FP are
the amounts of true positive, false negative, true negative, and false positive cases, respectively. n + and nare the amounts of positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity,
specificity, positive and negative predictive values, and accuracy, respectively. A positive event is defined
asn optimization of asthma control. A true positive case is defined as FENO changecut-off associated
with an optimization of asthma control between consecutive visits.
Table 10: Assessment of asthma control improvement by FENO in severe asthma.
p&
Cut-off
(ppb)*
0.002
-5
-10
-15
-20
-25
22
10
28
13
20
12
32
9
15
17
36
5
12
20
37
4
10
22
37
4
Se (%)
Sp (%)
69
69
63
78
47
87
38
91
31
91
PPV (%)
NPV (%)
Acc (%)
63
74
68
69
73
71
75
68
70
75
65
67
71
63
64
n+ ┌ TP
└ FN
┌ TN
n└ FP
Data are presented as &: statistical significance of rejecting AUC=0.5; *: boldface = cut-off value derived
from Youden's index maximization. TP, FN, TN and FP are the amounts of true positive, false negative,
true negative, and false positive cases, respectively. n+ and n- are the amounts of positive and negative
events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity, specificity, positive and negative predictive
values, and accuracy, respectively. A positive event is defined as an improvement of asthma control. A
true positive event is defined as FENO changecut-off associated with an improvement of asthma control
between consecutive visits.
Table 11: Assessment by FENO of a loss of optimal asthma control in non-severe asthma
p&
Cut-off
(ppb)*
n+┌ TP
└ FN
┌ TN
n└ FP
Whole population
0.046
ICS dose 500#
0.006
ICS dose > 500#
0.51
+5 +10 +15 +20 +25
+5 +10 +15 +20 +25
+5 +10 +15 +20 +25
20
19
83
42
8
31
113
12
14 12 10 5 4
5 7 9 14 15
54 61 66 73 74
31 24 19 12 11
6 6 6 5 4
14 14 14 15 16
29 33 37 38 40
11 7 3 2 0
18
21
93
32
16
23
103
22
10
29
110
15
Se (%)
51 46 41
26 21
74 63 53 26 21
30 30 30
25 20
Sp (%)
66 74 82
88 90
64 72 78 86 87
73 83 93
95 100
PPV (%) 32 36 42 40 40
NPV (%) 81 82 82 79 78
Acc (%) 63 68 73 73 74
31 33 34 29 27
92 90 88 84 83
65 70 73 75 75
35 46 67 71 100
67 70 73 72 71
58 65 72 72 73
Data are presented as #: g equ BDP.day-1; &: statistical significance of rejecting AUC=0.5; *: boldface
= cut-off value derived from Youden's index maximization in the whole population. TP, FN, TN and FP
are the amounts of true positive, false negative, true negative, and false positive cases, respectively. n + and
n- are the amounts of positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity,
specificity, positive and negative predictive values, and accuracy, respectively. A positive event is defined
as a loss of optimal asthma control. A true positive case is defined as FENO changecut-off associated
with an loss of optimal asthma control between consecutive visits.
Table 12: assessment of asthma control worsening by FENO in severe asthma.
p&
Cut-off
(ppb)*
0.003
+5
+10
+15
+20
+25
11
14
53
23
10
15
55
21
8
17
61
15
8
17
62
14
4
21
69
7
Se (%)
Sp (%)
43
70
39
73
30
80
30
82
17
91
PPV (%)
NPV (%)
Acc (%)
32
79
63
32
79
64
35
78
68
36
78
69
36
77
72
n+ ┌ TP
└ FN
┌ TN
n└ FP
Data are presented as &: statistical significance of rejecting AUC=0.5; *: boldface = cut-off value derived
from Youden's index maximization. Data are presented as *: boldface = cut-off value derived from
Youden's index maximization; &: statistical significance of rejecting AUC=0.5. TP, FN, TN and FP are
the amounts of true positive, false negative, true negative, and false positive cases, respectively. n+ and nare the amounts of positive and negative events, respectively. Se, Sp, PPV, NPV, and Acc are sensitivity,
specificity, positive and negative predictive values, and accuracy, respectively. A positive event is defined
as an improvement of asthma control. A true positive case is defined as FENO change cut-off
associated with an asthma control worsening between consecutive visits.