Table 1 Patient cohort characteristics for training datasets (n = 593)
From: Establishment of a machine learning model for predicting splenic hilar lymph node metastasis
Characteristics | Values | |
|---|---|---|
Age (years, mean [±std]) | 61.97 ( ± 11.2) | |
Sex | Male | 418 (70.5%) |
Female | 175 (29.5%) | |
Neoadjuvant chemotherapy | 90 (15.2%) | |
Main location | EGJ/upper | 348 (58.7%) |
Middle/lower/whole | 245 (41.3%) | |
Cross-sectional parts | Anterior wall | 56 (9.4%) |
Greater curvature | 82 (13.8%) | |
Lesser curvature | 255 (43.0%) | |
Posterior wall | 104 (17.5%) | |
Circumferential involvement | 96 (16.2%) | |
Greater curvature invasion | 212 (35.8%) | |
Macroscopic type | Type 0 | 64 (10.8%) |
Type 1 | 33 (5.6%) | |
Type 2 | 169 (28.5%) | |
Type 3 | 171 (28.8%) | |
Type 4 | 131 (22.1%) | |
Type 5 | 25 (4.2%) | |
Tumor diameter (mm, mean [±std]) | 85.9 ( ± 46.8) | |
Tumor depth | pT2 | 63 (10.6%) |
pT3 | 234 (39.5%) | |
pT4a | 269 (45.4%) | |
pT4b | 27 (4.6%) | |
Histology 1 | tub1 | 89 (15.0%) |
tub2 | 111 (18.7%) | |
pap | 23 (3.9%) | |
por1 | 70 (11.8%) | |
por2 | 249 (42.0%) | |
sig | 16 (2.7%) | |
muc | 19 (3.2%) | |
Special type | 16 (2.7%) | |
Histology 2 | tub1 | 62 (10.5%) |
tub2 | 119 (20.1%) | |
pap | 21 (3.5%) | |
por1 | 42 (7.1%) | |
por2 | 71 (12.0%) | |
sig | 150 (25.3%) | |
muc | 8 (1.3%) | |
Special type | 3 (0.5%) | |
None | 117 (19.7%) | |
Lymph node | #1 | 186 (31.4%) |
#2 | 85 (14.3%) | |
#3 | 297 (50.1%) | |
#4sa | 71 (12.0%) | |
#4sb | 71 (12.0%) | |
#4d | 135 (22.8%) | |
#5 | 19 (3.2%) | |
#6 | 52 (8.8%) | |
#7 | 127 (21.4%) | |
#8 | 49 (8.3%) | |
#9 | 57 (9.6%) | |
#11p | 78 (13.2%) | |
#11d | 43 (7.3%) | |
#12a | 7 (1.2%) | |
#10 | 48 (8.1%) | |
