1 NAB vs NAB + B_Cyfra21

    癤풦D NAB Gold B_Cyfra21_1  B_CEA B_SCC_Ag C_CYFRA  C_CEA   C_SCC Cyfra CEA
1       1   1    1        2.43   4.76     0.40  114.10   6.67   0.165     0   0
2       2   2    1        1.32   3.32     0.50   18.11   3.87   0.280     0   0
3       3   2    1        1.59   0.92     0.80   39.10   0.89   0.100     0   0
4       4   1    1        1.88   1.64     0.60   24.18   0.10   0.170     0   0
5       5   2    2        0.60   1.88     0.30    5.29   0.10   0.155     0   0
6       6   2    1        1.66   3.51     0.90   18.90   0.21   0.300     0   0
7       7   2    2        0.76   4.14     0.30    4.14   0.44   0.185     0   0
8       8   1    1        3.85   2.59     2.00  440.95  10.41  17.300     1   0
9       9   1    1        2.60   1.72     1.90   22.59   6.69 150.000     0   0
10     10   2    2        0.60   1.08     0.90    7.23   0.39   0.175     0   0
11     11   2    1        0.81   0.32     0.50   21.85   0.10   3.050     0   0
12     12   1    1        0.67   3.21     0.80    7.66   1.31   0.205     0   0
13     13   1    1        2.27   3.37     1.90    8.24   9.80  24.400     0   0
14     14   2    2        0.89   1.49     0.50   10.29   0.10   0.420     0   0
15     15   1    1        4.31   3.06     1.50  231.70   2.04   8.300     1   0
16     16   2    1        1.60   1.22     0.60   10.24   0.10   0.135     0   0
17     17   2    1        3.54   3.40     0.50   35.33   8.00   0.300     1   0
18     18   1    1       45.71 366.70     0.40  197.40 164.95   0.815     1   1
19     19   1    1        3.70   1.61     1.20   26.34   0.71   9.950     1   0
20     20   1    1        6.83   3.61     0.60  201.70   0.10  24.850     1   0
21     21   2    2        1.94   0.75     1.40    2.75   0.12   0.210     0   0
22     22   2    2        3.00   5.70     0.53    2.00   0.10   0.405     0   1
23     23   2    2        2.80   1.80     0.54    5.45   0.10   7.150     0   0
24     24   2    2        5.30   4.30     2.90    2.50   0.10   0.255     1   0
25     25   2    2        1.50   1.60     0.76    2.45   0.10   0.250     0   0
26     26   2    2        2.70   3.20     0.18    2.25   0.10   0.120     0   0
27     27   1    1        2.31   3.55     0.30  121.20  11.26  38.350     0   0
28     28   2    2        1.03   2.24     0.90    1.90   0.28   0.135     0   0
29     29   1    1       25.21   2.04     0.60   48.00   0.39   8.850     1   0
30     30   1    1        1.47   5.64     0.60  198.50  34.14   1.250     0   1
31     31   1    1        2.61   3.43     0.30   23.56   0.10   0.275     0   0
32     32   2    2        4.37   1.62     0.50    8.61   0.14   0.280     1   0
33     33   2    1        1.85  16.15     0.30   43.06  71.88   0.135     0   1
34     34   1    1        2.93  17.17     0.10   31.21   5.97   0.075     0   1
35     35   1    1        0.98  28.30     0.40    1.50   0.77   0.135     0   1
36     36   2    2        1.99   3.99     0.40    1.35   2.70   0.740     0   0
37     37   2    1        2.20   1.97     0.30    2.10   0.66   0.070     0   0
38     38   2    1        1.68   1.33     0.20   55.50   0.20  10.850     0   0
39     39   1    1        0.86   0.94     0.40   19.93   3.51  11.990     0   0
40     40   1    1        5.42  30.61     0.10   10.77   4.89   1.090     1   1
41     41   1    1        0.75   1.65     0.20   32.89   2.16   0.055     0   0
42     42   2    1       15.36  14.67     0.10   79.99   5.85 133.000     1   1
43     43   1    1        1.58   1.27     0.20    4.15   0.57   3.750     0   0
44     44   1    1        1.70   1.34     0.50    4.27   4.39   9.750     0   0
45     45   1    1        1.68   6.52     0.50   16.42  11.82   0.460     0   1
46     46   2    2        3.45   1.27     1.30    1.19   0.10   1.900     1   0
47     47   1    1        1.21   2.60     5.70   15.50   2.33   5.350     0   0
48     48   2    2        1.23   3.16     1.20    1.46   0.10   0.240     0   0
49     49   1    1        7.54   2.44     1.60   35.65   0.49   0.295     1   0
50     50   2    2        2.34   0.58     0.60    9.30   0.10   6.950     0   0
51     51   1    1       11.99 248.65     0.60  118.20  40.05  21.900     1   1
52     52   1    1        3.15   0.94     1.60   46.07   2.88   3.700     0   0
53     53   2    2        1.21   2.23     0.30    8.21   0.10   0.280     0   0
54     54   1    1        4.18   6.09     0.40   28.71   1.47   0.110     1   1
55     55   2    2        2.19   0.69     0.30    1.91   0.39   0.555     0   0
56     56   1    1        3.33   3.99     2.80  500.00  42.74 150.000     1   0
57     57   1    1       35.69  40.19     1.20   72.01  59.60   0.195     1   1
58     58   1    1        5.75   4.29     0.50  174.20   1.55   8.150     1   0
59     59   1    1       20.71 373.63     0.90  191.80 105.11   1.200     1   1
60     60   2    2        2.53   7.49     0.80   12.21   2.14  15.000     0   1
61     61   2    2        2.36   2.72     0.80    4.44   1.38   0.245     0   0
62     62   2    1        0.68   2.25     0.10   68.52  30.82   2.050     0   0
63     63   1    1        7.81  13.37     3.90    6.82   0.44  50.700     1   1
64     64   1    1        6.80 227.39     0.90    6.86  19.11   0.265     1   1
65     65   1    1       29.26   8.45     9.20   70.23   0.92   0.610     1   1
66     66   1    1        3.35   5.32     0.80   35.73  57.51  27.250     1   1
67     67   1    1        2.26  50.84     0.40   29.40   7.28   0.125     0   1
68     68   1    1        2.17   1.31     0.10   19.51   3.32   0.080     0   0
69     69   1    1        1.90   1.05     0.30   10.46   0.10   1.500     0   0
70     70   2    2        2.53   4.52     0.50    6.57   0.10   0.975     0   0
71     71   2    2        2.72   2.25     0.60    1.23   0.13   0.925     0   0
72     72   1    1        5.36   5.32     1.10  199.85   0.27   1.450     1   1
73     73   1    1        7.87  17.17     0.20   16.52   6.40   1.350     1   1
74     74   2    2        1.25   0.45     0.40    8.89   0.10  11.100     0   0
75     75   1    1        3.05   2.28     1.00  200.55  22.83   1.150     0   0
76     76   2    2        0.40   2.22     1.41    7.90   0.10   8.050     0   0
77     77   1    1        2.26   1.24     1.30   10.63   0.10   0.070     0   0
78     78   2    1        1.34   7.28     0.50    1.65   0.83   0.135     0   1
79     79   1    1        5.22  10.55     1.90  263.55  68.96   0.905     1   1
80     80   1    1        5.65   3.10     1.20    3.76   2.03  29.200     1   0
81     81   1    1        3.63   4.10     0.80    4.44   0.16   0.045     1   0
82     82   1    1        4.78   1.33     0.90   53.03  10.31   5.650     1   0
83     83   2    2        2.14   0.93     0.60    7.44   0.10   0.480     0   0
84     84   1    1        1.67   1.22     1.10    4.24   0.61   0.065     0   0
85     85   1    1        3.31   1.11     0.90   18.37   1.65   0.090     1   0
86     86   2    2        2.74   2.54     0.80    6.53   0.10   0.080     0   0
87     87   2    1        2.42   2.60     0.80   16.22   2.68   1.850     0   0
88     88   1    1        2.75   7.04     0.60  500.00   8.36   4.700     0   1
89     89   2    1        1.44   1.13     0.30    4.61   0.10   0.085     0   0
90     90   1    1        2.46   1.26     0.80    2.68   0.10   0.710     0   0
91     91   2    1        3.19   3.06     0.60   10.42   0.10   0.125     0   0
92     92   2    1        1.27   1.41     0.70    2.96   0.10   0.130     0   0
93     93   1    1        4.31   1.91     0.80   96.54   1.91   0.275     1   0
94     94   1    1        3.00   1.88     1.50  217.25   5.62   0.185     0   0
95     95   1    1        2.45   0.82     4.60    3.63   0.81   0.085     0   0
96     96   1    1        2.59   4.98     7.80   60.87   1.22  13.000     0   0
97     97   2    2        3.82   4.43     2.70    9.53   0.36   0.080     1   0
98     98   1    1      288.00   3.09     0.90  500.00   0.45   0.120     1   0
99     99   2    2        2.73   1.73     0.20   17.59   1.30  54.150     0   0
100   100   1    1        1.21   3.29     5.70    3.04   0.69   0.405     0   0
101   101   1    1        1.62  26.20     1.90   24.79   1.30   0.070     0   1
102   102   2    1        6.51   6.89     1.80   24.60   3.59  14.850     1   1
103   103   1    1        3.94   8.46     1.40  155.65  18.39   0.870     1   1
104   104   1    1        3.14   3.93     1.30   15.55   1.18   1.600     0   0
105   105   1    1        1.55   2.58     1.10    9.53   2.09   0.180     0   0
106   106   1    1        6.41   2.84     3.70   26.14   7.11 211.920     1   0
107   107   2    1        1.45   1.86     0.60    3.41   0.45   0.125     0   0
108   108   1    1        1.54   3.45     0.70  500.00  11.21  96.150     0   0
109   109   1    1        1.45   2.13     0.80    7.91   0.56   0.130     0   0
110   110   2    2        1.29   5.46     0.70    5.07   0.23   0.065     0   1
111   111   2    2        1.45   1.73     0.80    1.94   0.35   6.250     0   0
112   112   1    1        1.59   1.88     1.30    7.39   1.49   0.100     0   0
113   113   1    1        6.18  27.50     1.50   24.40   3.09  14.500     1   1
114   114   1    1        3.08   3.90     1.20   18.00   1.81   0.800     0   0
115   115   1    1        0.69   2.11     1.10    1.11   0.55   0.105     0   0
116   116   1    1        3.28   1.21     0.28  108.35   1.91   4.500     0   0
117   117   1    1        1.77   2.92     0.45  237.55   1.30   0.880     0   0
118   118   2    2        2.22   1.89     1.80    2.16   0.21   0.195     0   0
119   119   2    2        2.43   2.42     0.24    3.68   0.33   0.175     0   0
120   120   2    2        1.47   1.21     0.33   11.96   0.40   0.105     0   0
121   121   2    2        2.00   2.21     0.46    1.39   0.31   0.110     0   0
122   122   1    1       13.66   3.98     2.80  500.00 142.47  70.050     1   0
123   123   1    1        2.55 495.71     0.54    3.56  10.12   1.400     0   1
124   124   1    1        6.15   6.50     4.80   15.99   3.03  17.850     1   1
125   125   2    2        3.19   2.92     0.71    2.31   0.39   1.600     0   0
126   126   1    1        1.96   6.20     0.32   22.76   2.59   0.235     0   1
127   127   1    1        4.05   1.75     0.63    6.64   0.82   1.150     1   0
128   128   1    1       55.24  32.31     2.10  500.00 879.54  44.800     1   1
129   129   1    1       20.43  10.61     0.25  138.20   1.83   1.700     1   1
130   130   1    1        1.51   1.77     0.35    2.92   0.38   0.110     0   0
131   131   1    1       13.92   4.26     1.40   42.79   1.67   4.550     1   0
132   132   2    2        4.51   0.52     1.00    6.57   0.35   5.750     1   0
133   133   1    1        3.71   2.15     1.90  500.00   0.68   0.975     1   0
134   134   1    1        7.26 200.16     0.32   66.54 171.40   0.205     1   1
135   135   2    2        2.20   2.53     0.49    4.59   0.25   0.130     0   0
136   136   1    1        4.39  10.23     0.96   56.60  62.40  33.700     1   1
137   137   1    1        2.48  17.19     0.28   50.77   2.27   7.800     0   1
138   138   2    2        3.75   3.91     0.90    3.26   0.18   0.200     1   0
139   139   2    2        5.15   4.23     0.60    8.91   0.21  11.150     1   0
140   140   1    1        2.24  11.51     1.50   12.82   0.20   9.650     0   1
141   141   1    1       14.67 526.78     0.32  500.00  38.80   0.390     1   1
142   142   2    2        1.57   1.75     0.48    3.54   0.13   0.245     0   0
143   143   1    1       10.58 148.63     2.00    9.30   4.92   0.135     1   1
144   144   2    2        1.94   0.75     1.40    2.75   0.12   0.210     0   0
145   145   1    1        1.90   2.10     1.10   19.05  15.25   0.210     0   0
146   146   2    2        3.00   5.70     0.53    2.00   0.10   0.405     0   1
147   147   2    1        2.10   1.70     0.37   60.85   0.10  13.200     0   0
148   148   1    1      114.80   2.70     0.72   92.15   0.80   0.160     1   0
149   149   1    1        2.80   6.70     1.00  247.10   1.00   0.315     0   1
150   150   2    1        3.10   1.20     0.25   46.35   1.40   0.885     0   0
151   151   1    1        9.80  13.20     7.80  270.25  63.90 150.000     1   1
152   152   1    1        3.10   2.10     1.20  500.00  12.20   0.255     0   0
153   153   1    1        3.20   0.70     0.56   73.35   0.10 138.000     0   0
154   154   1    1        2.70   6.40     1.00   37.55  12.15   0.105     0   1
155   155   1    1        1.50   2.80     1.50  236.05   9.65  13.750     0   0
156   156   1    1        5.70  23.50     0.28    7.45   0.90   0.160     1   1
157   157   1    1        1.50   1.10     1.40   72.30   0.10  10.100     0   0
158   158   1    1        8.40 513.30     0.89   75.15  46.75   1.750     1   1
159   159   1    1        2.50 149.90     0.19  500.00  53.25   3.750     0   1
160   160   2    1        1.60   3.50     1.00   50.75   8.30  37.500     0   0
161   161   1    1        5.10   2.50     1.10    4.65   0.10   1.350     1   0
162   162   1    1        2.70 243.70     0.47   22.35  13.00   0.140     0   1
163   163   1    1        2.30   3.10     0.70   11.25   0.20   7.805     0   0
164   164   1    1        7.20 100.30     1.10   53.30  23.70   0.345     1   1
165   165   2    2        2.80   1.80     0.54    5.45   0.10   7.150     0   0
166   166   1    1       24.40   8.00     5.30  440.95   0.30  43.900     1   1
167   167   1    1        1.20   1.40     0.39  244.25   1.20   2.100     0   0
168   168   2    2        5.30   4.30     2.90    2.50   0.10   0.255     1   0
169   169   1    1        6.70  22.90     0.95  500.00  39.25   0.505     1   1
170   170   2    2        1.50   1.60     0.76    2.45   0.10   0.250     0   0
171   171   1    1        2.80   3.60     1.00  235.25   0.10   7.900     0   0
172   172   1    1        1.80   5.80     1.10  313.75  21.15   0.190     0   1
173   173   2    1        2.20   1.60     0.94  500.00   0.10   1.550     0   0
174   174   1    1        1.90   2.00     0.10  100.35  44.00   0.195     0   0
175   175   1    1        7.60  40.70     1.60  188.70  40.95   0.850     1   1
176   176   1    1        1.60   1.90     0.83    5.55   7.10   1.100     0   0
177   177   1    1        4.10   1.10     0.36  241.85   0.10   0.710     1   0
178   178   1    1       33.00  15.70     1.90  500.00  31.20   8.900     1   1
179   179   1    1        2.90   1.10     0.74    7.30   0.10   1.150     0   0
180   180   1    1        5.10   2.20     0.66  226.35   0.10   0.175     1   0
181   181   2    2        2.70   3.20     0.18    2.25   0.10   0.120     0   0
182   182   1    1        2.40   2.50     1.00  141.25 149.30  36.800     0   0
183   183   2    1        2.30   0.50     0.69   47.15   0.10   1.750     0   0
184   184   1    1        8.60  32.20     2.30   10.50   5.25   1.200     1   1
185   185   1    1        3.00   6.20     0.91   21.70   0.10   1.560     0   1
186   186   2    2        0.76   4.14     0.30    4.14   0.44   0.185     0   0
187   187   2    2        0.60   1.88     0.30    5.29   0.10   0.155     0   0
188   188   2    2        1.03   2.24     0.90    1.90   0.28   0.135     0   0
189   189   2    2        4.37   1.62     0.50    8.61   0.14   0.280     1   0
190   190   2    2        3.45   1.27     1.30    1.19   0.10   1.900     1   0
191   191   2    2        1.23   3.16     1.20    1.46   0.10   0.240     0   0
192   192   2    2        2.34  10.58     0.60    9.30   0.10   6.950     0   1
193   193   2    2        1.21   2.23     0.30    8.21   0.10   0.280     0   0
194   194   2    2        2.19   0.69     0.30    1.91   0.39   0.555     0   0
    Gold_A NAB_A
1        1     1
2        1     0
3        1     0
4        1     1
5        0     0
6        1     0
7        0     0
8        1     1
9        1     1
10       0     0
11       1     0
12       1     1
13       1     1
14       0     0
15       1     1
16       1     0
17       1     0
18       1     1
19       1     1
20       1     1
21       0     0
22       0     0
23       0     0
24       0     0
25       0     0
26       0     0
27       1     1
28       0     0
29       1     1
30       1     1
31       1     1
32       0     0
33       1     0
34       1     1
35       1     1
36       0     0
37       1     0
38       1     0
39       1     1
40       1     1
41       1     1
42       1     0
43       1     1
44       1     1
45       1     1
46       0     0
47       1     1
48       0     0
49       1     1
50       0     0
51       1     1
52       1     1
53       0     0
54       1     1
55       0     0
56       1     1
57       1     1
58       1     1
59       1     1
60       0     0
61       0     0
62       1     0
63       1     1
64       1     1
65       1     1
66       1     1
67       1     1
68       1     1
69       1     1
70       0     0
71       0     0
72       1     1
73       1     1
74       0     0
75       1     1
76       0     0
77       1     1
78       1     0
79       1     1
80       1     1
81       1     1
82       1     1
83       0     0
84       1     1
85       1     1
86       0     0
87       1     0
88       1     1
89       1     0
90       1     1
91       1     0
92       1     0
93       1     1
94       1     1
95       1     1
96       1     1
97       0     0
98       1     1
99       0     0
100      1     1
101      1     1
102      1     0
103      1     1
104      1     1
105      1     1
106      1     1
107      1     0
108      1     1
109      1     1
110      0     0
111      0     0
112      1     1
113      1     1
114      1     1
115      1     1
116      1     1
117      1     1
118      0     0
119      0     0
120      0     0
121      0     0
122      1     1
123      1     1
124      1     1
125      0     0
126      1     1
127      1     1
128      1     1
129      1     1
130      1     1
131      1     1
132      0     0
133      1     1
134      1     1
135      0     0
136      1     1
137      1     1
138      0     0
139      0     0
140      1     1
141      1     1
142      0     0
143      1     1
144      0     0
145      1     1
146      0     0
147      1     0
148      1     1
149      1     1
150      1     0
151      1     1
152      1     1
153      1     1
154      1     1
155      1     1
156      1     1
157      1     1
158      1     1
159      1     1
160      1     0
161      1     1
162      1     1
163      1     1
164      1     1
165      0     0
166      1     1
167      1     1
168      0     0
169      1     1
170      0     0
171      1     1
172      1     1
173      1     0
174      1     1
175      1     1
176      1     1
177      1     1
178      1     1
179      1     1
180      1     1
181      0     0
182      1     1
183      1     0
184      1     1
185      1     1
186      0     0
187      0     0
188      0     0
189      0     0
190      0     0
191      0     0
192      0     0
193      0     0
194      0     0
logistf(formula = Gold_A ~ NAB_A, data = data)

Model fitted by Penalized ML
Confidence intervals and p-values by Profile Likelihood Profile Likelihood 

                  coef  se(coef) lower 0.95 upper 0.95    Chisq            p
(Intercept) -0.8593826 0.2476848  -1.360021 -0.3903404 13.34203 0.0002595234
NAB_A        6.3104211 1.4447307   4.307835 11.1611300      Inf 0.0000000000

Likelihood ratio test=131.8933 on 1 df, p=0, n=194
Wald test = 19.07844 on 1 df, p = 1.254542e-05

Covariance-Matrix:
            [,1]        [,2]
[1,]  0.06134776 -0.06134776
[2,] -0.06134776  2.08724684
logistf(formula = Gold_A ~ NAB_A + B_Cyfra21_1, data = data)

Model fitted by Penalized ML
Confidence intervals and p-values by Profile Likelihood Profile Likelihood Profile Likelihood 

                   coef    se(coef)  lower 0.95  upper 0.95     Chisq
(Intercept) -0.82339619 0.248791761 -1.32532738 -0.35283591 12.131556
NAB_A        6.32998561 1.438483468  4.31551791 11.30334849       Inf
B_Cyfra21_1 -0.01497379 0.009746412 -0.03447302  0.01171638  2.343615
                       p
(Intercept) 0.0004957574
NAB_A       0.0000000000
B_Cyfra21_1 0.1257972913

Likelihood ratio test=130.813 on 2 df, p=0, n=194
Wald test = 20.31566 on 2 df, p = 3.877133e-05

Covariance-Matrix:
              [,1]         [,2]          [,3]
[1,]  0.0618973405 -0.043408941 -2.267612e-04
[2,] -0.0434089411  2.069234687 -7.518215e-03
[3,] -0.0002267612 -0.007518215  9.499254e-05
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Setting levels: control = 0, case = 1
Setting direction: controls < cases

Call:
roc.default(response = data$Gold_A, predictor = fit1$predict,     ci = T)

Data: fit1$predict in 55 controls (data$Gold_A 0) < 139 cases (data$Gold_A 1).
Area under the curve: 0.9173
95% CI: 0.8863-0.9483 (DeLong)

Call:
roc.default(response = data$Gold_A, predictor = fit2$predict,     ci = T)

Data: fit2$predict in 55 controls (data$Gold_A 0) < 139 cases (data$Gold_A 1).
Area under the curve: 0.9228
95% CI: 0.886-0.9596 (DeLong)

    DeLong's test for two correlated ROC curves

data:  roc1 and roc2
Z = -0.47753, p-value = 0.633
alternative hypothesis: true difference in AUC is not equal to 0
sample estimates:
AUC of roc1 AUC of roc2 
  0.9172662   0.9228254 

2 NAB vs NAB + B_Cyfra + B_CEA

logistf(formula = Gold_A ~ NAB_A, data = data)

Model fitted by Penalized ML
Confidence intervals and p-values by Profile Likelihood Profile Likelihood 

                  coef  se(coef) lower 0.95 upper 0.95    Chisq            p
(Intercept) -0.8593826 0.2476848  -1.360021 -0.3903404 13.34203 0.0002595234
NAB_A        6.3104211 1.4447307   4.307835 11.1611300      Inf 0.0000000000

Likelihood ratio test=131.8933 on 1 df, p=0, n=194
Wald test = 19.07844 on 1 df, p = 1.254542e-05

Covariance-Matrix:
            [,1]        [,2]
[1,]  0.06134776 -0.06134776
[2,] -0.06134776  2.08724684
logistf(formula = Gold_A ~ NAB_A + B_Cyfra21_1 + B_CEA, data = data)

Model fitted by Penalized ML
Confidence intervals and p-values by Profile Likelihood Profile Likelihood Profile Likelihood Profile Likelihood 

                    coef    se(coef)  lower 0.95  upper 0.95     Chisq
(Intercept) -0.806672254 0.249578170 -1.31005131 -0.33426441 11.524416
NAB_A        6.310920733 1.448074440  4.25082526 12.14135426       Inf
B_Cyfra21_1 -0.014861248 0.009754185 -0.03665319  0.08966310  2.249817
B_CEA       -0.005827097 0.004721622 -0.01851064  0.01136002  1.164203
                       p
(Intercept) 0.0006868804
NAB_A       0.0000000000
B_Cyfra21_1 0.1336302263
B_CEA       0.2805955077

Likelihood ratio test=128.6232 on 3 df, p=0, n=194
Wald test = 24.33854 on 3 df, p = 2.122735e-05

Covariance-Matrix:
              [,1]         [,2]          [,3]          [,4]
[1,]  6.228926e-02 -0.030563353 -2.685128e-04 -9.910281e-05
[2,] -3.056335e-02  2.096919585 -7.577893e-03 -4.400394e-03
[3,] -2.685128e-04 -0.007577893  9.514413e-05  1.447942e-05
[4,] -9.910281e-05 -0.004400394  1.447942e-05  2.229372e-05
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Setting levels: control = 0, case = 1
Setting direction: controls < cases

Call:
roc.default(response = data$Gold_A, predictor = fit3$predict,     ci = T)

Data: fit3$predict in 55 controls (data$Gold_A 0) < 139 cases (data$Gold_A 1).
Area under the curve: 0.9173
95% CI: 0.8863-0.9483 (DeLong)

Call:
roc.default(response = data$Gold_A, predictor = fit4$predict,     ci = T)

Data: fit4$predict in 55 controls (data$Gold_A 0) < 139 cases (data$Gold_A 1).
Area under the curve: 0.9211
95% CI: 0.8832-0.9591 (DeLong)

    DeLong's test for two correlated ROC curves

data:  roc3 and roc4
Z = -0.3166, p-value = 0.7515
alternative hypothesis: true difference in AUC is not equal to 0
sample estimates:
AUC of roc1 AUC of roc2 
  0.9172662   0.9211249 
logistf(formula = Gold_A ~ NAB_A, data = data)

Model fitted by Penalized ML
Confidence intervals and p-values by Profile Likelihood Profile Likelihood 

                  coef  se(coef) lower 0.95 upper 0.95    Chisq            p
(Intercept) -0.8593826 0.2476848  -1.360021 -0.3903404 13.34203 0.0002595234
NAB_A        6.3104211 1.4447307   4.307835 11.1611300      Inf 0.0000000000

Likelihood ratio test=131.8933 on 1 df, p=0, n=194
Wald test = 19.07844 on 1 df, p = 1.254542e-05

Covariance-Matrix:
            [,1]        [,2]
[1,]  0.06134776 -0.06134776
[2,] -0.06134776  2.08724684
logistf(formula = Gold_A ~ NAB_A + B_Cyfra21_1 + B_CEA + B_SCC_Ag + 
    C_CYFRA + C_CEA + C_SCC, data = data)

Model fitted by Penalized ML
Confidence intervals and p-values by Profile Likelihood Profile Likelihood Profile Likelihood Profile Likelihood Profile Likelihood Profile Likelihood Profile Likelihood Profile Likelihood 

                    coef    se(coef)  lower 0.95  upper 0.95      Chisq
(Intercept) -1.527820860 0.555646102 -3.87967815 -0.24122715  7.0956858
NAB_A        9.106365300 2.959931337  3.87269330 29.91667919 67.3964838
B_Cyfra21_1 -0.192331369 0.059769774 -0.55207634 -0.08571002  6.1139287
B_CEA       -0.008910962 0.009015956 -0.04927034  0.32771533  0.2362012
B_SCC_Ag    -0.798284187 0.643496709 -2.75433349  0.97015848  0.0000000
C_CYFRA      0.175714873 0.052084983  0.08149320  0.41756999 28.1277469
C_CEA       -0.090837357 0.026962626 -0.22168869 -0.04196320  1.7232354
C_SCC       -0.030847701 0.015643311 -0.14500638  0.00305560  7.5747991
                       p
(Intercept) 7.726972e-03
NAB_A       2.220446e-16
B_Cyfra21_1 1.341207e-02
B_CEA       6.269634e-01
B_SCC_Ag    1.000000e+00
C_CYFRA     1.135660e-07
C_CEA       1.892771e-01
C_SCC       5.918998e-03

Likelihood ratio test=153.7797 on 7 df, p=0, n=194
Wald test = 19.7219 on 7 df, p = 0.006202749

Covariance-Matrix:
              [,1]        [,2]          [,3]          [,4]          [,5]
[1,]  0.3087425910  0.46457682  0.0006522633 -2.183251e-03 -2.237745e-01
[2,]  0.4645768194  8.76119352 -0.1309908363 -2.061923e-02 -1.163286e+00
[3,]  0.0006522633 -0.13099084  0.0035724259  2.273802e-04  1.670109e-02
[4,] -0.0021832514 -0.02061923  0.0002273802  8.128747e-05  2.858403e-03
[5,] -0.2237745403 -1.16328616  0.0167010927  2.858403e-03  4.140880e-01
[6,] -0.0078396633  0.07466233 -0.0026991390 -6.444653e-05 -9.767511e-03
[7,]  0.0039261674 -0.04047442  0.0013822463  3.615958e-05  5.124487e-03
[8,]  0.0009580604 -0.02729539  0.0005375455  5.680165e-05 -3.364965e-05
              [,6]          [,7]          [,8]
[1,] -7.839663e-03  3.926167e-03  9.580604e-04
[2,]  7.466233e-02 -4.047442e-02 -2.729539e-02
[3,] -2.699139e-03  1.382246e-03  5.375455e-04
[4,] -6.444653e-05  3.615958e-05  5.680165e-05
[5,] -9.767511e-03  5.124487e-03 -3.364965e-05
[6,]  2.712845e-03 -1.393553e-03 -3.952432e-04
[7,] -1.393553e-03  7.269832e-04  2.069251e-04
[8,] -3.952432e-04  2.069251e-04  2.447132e-04
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Setting levels: control = 0, case = 1
Setting direction: controls < cases

Call:
roc.default(response = data$Gold_A, predictor = fit5$predict,     ci = T)

Data: fit5$predict in 55 controls (data$Gold_A 0) < 139 cases (data$Gold_A 1).
Area under the curve: 0.9173
95% CI: 0.8863-0.9483 (DeLong)

Call:
roc.default(response = data$Gold_A, predictor = fit6$predict,     ci = T)

Data: fit6$predict in 55 controls (data$Gold_A 0) < 139 cases (data$Gold_A 1).
Area under the curve: 0.9802
95% CI: 0.9641-0.9964 (DeLong)

    DeLong's test for two correlated ROC curves

data:  roc5 and roc6
Z = -4.4666, p-value = 7.946e-06
alternative hypothesis: true difference in AUC is not equal to 0
sample estimates:
AUC of roc1 AUC of roc2 
  0.9172662   0.9802485