Research Article
A Recurrence-Specific Gene-Based Prognosis Prediction Model for Lung Adenocarcinoma through Machine Learning Algorithm
Table 1
Clinical characteristics of included patients for survival model construction and validation.
| | TCGA training cohort (288) | TCGA testing cohort (128) | External validation cohort (335) |
| | Sex | | | | | Female | 167 (56.04%) | 64 (50%) | 189 (56.42%) | | Male | 131 (43.96%) | 64 (50%) | 146 (43.58%) | | Age | | | | | ≥60 | 201 (67.45%) | 95 (74.22%) | 234 (69.85%) | | <60 | 88 (29.53%) | 32 (25%) | 101 (30.15%) | | Unknown | 9 (3.02%) | 1 (0.78%) | 0 (0%) | | Pathologic T | | | | | T1 | 109 (36.58%) | 41 (32.03%) | 110 (32.84%) | | T2 | 160 (53.69%) | 67 (52.34%) | 202 (60.29%) | | T3 | 21 (7.05%) | 13 (10.16%) | 16 (4.78%) | | T4 | 6 (2.01%) | 6 (4.69%) | 5 (1.49%) | | Unknown | 2 (0.67%) | 1 (0.78%) | 2 (0.60%) | | Pathologic N | | | | | N0 | 201 (67.45%) | 80 (62.50%) | 299 (89.25%) | | N1 | 52 (17.45%) | 26 (20.31%) | 88 (26.27%) | | N2 | 38 (12.75%) | 17 (13.28%) | 53 (14.93%) | | N3 | 2 (0.67%) | 0 (0%) | 0 (0%) | | Unknown | 5 (1.68%) | 5 (3.91%) | 0 (0%) | | Pathologic M | | | NA | | M0 | 192 (64.43%) | 83 (64.84%) | 0 (0%) | | M1 | 12 (4.03%) | 5 (3.91%) | 0 (0%) | | Unknown | 94 (31.54%) | 40 (31.25%) | 335 (100%) | | Tumor stage | | | | | I | 171 (57.38%) | 64 (50.00%) | 150 (33.86%) | | II | 69 (23.15%) | 33 (25.78%) | 252 (56.88%) | | III | 43 (14.43%) | 21 (16.41%) | 29 (6.55%) | | IV | 12 (4.03%) | 6 (4.69%) | 12 (2.71%) | | Unknown | 3 (1.01%) | 4 (3.13%) | 0 (0%) |
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