Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography

Table 1 Patients’ characteristics, n (%)

Characteristics	Patients (n = 212)
Gender
Male	200 (94.3)
Female	12 (5.7)
Age (mean ± SD; range)	58.8 ± 8.9 (34-80)
Height (cm), mean ± SD	166.0 ± 6.5
Weight (kg), mean ± SD	61.7 ± 11.3
BMI (kg/m2), mean ± SD	22.3 ± 3.6
Histological subtype
Adenocarcinoma	7 (3.3)
Squamous cell carcinoma	205 (96.7)
T stage
T1	11 (5.2)
T2	7 (3.3)
T3	178 (84.0)
T4	16 (7.5)
N stage
N0	15 (7.1)
N1	63 (29.7)
N2	82 (38.7)
N3	52 (24.5)
M stage
M0	182 (86.3)
M1	29 (13.7)
ECOG
0	25 (11.8)
1	169 (79.7)
≥ 2	8 (3.8)
NA	10 (4.7)
CT follow-up date from first CCRT (days), mean ± SD	105.4 ± 38.0
Surgery treatment	95 (44.8)
Surgery date from first CCRT (days), mean ± SD	96.5 ± 82.3
Survival rate
1-year	149 (70.3)
2-year	101 (47.6)
3-year	82 (38.7)

BMI: Body mass index; ECOG: Eastern Cooperative Oncology Group; NA: Not available; CT: Computed tomography; CCRT: Concurrent chemoradiotherapy.