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.

Table 2 The features selected from feature subset 1 using least absolute shrinkage and selection operator, with the Cox regression analysis

Covariate	HR (95%CI)	P value
clinical_T	1.90 (1.27-2.84)	0.002
clinical_N	1.32 (1.08-1.61)	0.006
clinical_M	2.04 (1.30-3.18)	0.002
ECOG	1.60 (1.38-2.02)	0.024
sarco0	1.42 (1.35-1.50)	0.044
TATSMR1	1.23 (0.93-1.33)	0.047
delta_SAT	1.00 (1.00-1.37)	0.024

HR: Hazard ratio; CI: Confidence interval; ECOG: Eastern Cooperative Oncology Group; sarco: Sarcopenia; 0: Pretreatment; TATSMR1: Total adipose tissue index/skeletal muscle index ratio; 1: Follow-up; SAT: Subcutaneous adipose tissue.

Table 3 The features selected from feature subset 2 using least absolute shrinkage and selection operator, with the Cox regression analysis

Covariate	HR (95%CI)	P value
clinical_M	2.13 (1.26-3.60)	0.005
clinical_T	1.91 (1.23-2.95)	0.004
MUSCLE_shape_Sphericity0	0.00 (0.00-0.01)	0.014
VAT_firstorder_Mean0	1.02 (0.99-1.06)	0.016
VAT_glcm_ClusterShade0	1.17 (1.00-1.37)	0.047
VAT _shape_Elongation0	33.31 (2.14-519.51)	0.012
VAT_shape_Sphericity0	0.00 (0.00-0.00)	0.001
VAT_shape_SurfaceVolumeRatio0	1.76 (0.97-3.21)	0.045

HR: Hazard ratio; CI: Confidence interval; VAT: Visceral adipose tissue; glcm: Gray-level co-occurrence matrix; 0: Pretreatment.

Table 4 The features selected from feature subset 3 using least absolute shrinkage and selection operator, with the Cox regression analysis

Covariate	HR (95%CI)	P value
clinical_M	2.13 (1.26-3.60)	0.005
clinical_T	1.91 (1.23-2.95)	0.004
MUSCLE_original_glszm_LargeAreaEmphasis1	1.00 (1.00-1.00)	0.003
VAT_original_firstorder_10Percentile1	1.01 (1.01-1.03)	0.032
VAT_original_firstorder_90Percentile1	1.11 (1.04-1.19)	0.002
VAT_original_firstorder_Mean1	1.04 (1.01-1.07)	0.002
VAT_original_firstorder_Minimum1	1.26 (1.26-6.01)	0.049
VAT_original_glcm_JointEnergy1	12.19 (1.38-394.85)	0.016
VAT_original_glcm_JointEntropy1	1.71 (1.32-2.58)	0.040
VAT_original_gldm_DependenceVariance1	0.94 (0.91-0.98)	0.002
VAT_original_glrlm_LongRunLowGrayLevelEmphasis1	1.06 (1.05-3.39)	0.009
VAT_original_glrlm_RunEntropy1	0.09 (0.02-0.37)	0.001
VAT_original_glszm_GrayLevelNonUniformityNormalized1	1.03 (1.00-6.68)	0.012
VAT_original_glszm_SizeZoneNonUniformityNormalized1	1.06 (1.00-10.47)	0.029

HR: Hazard ratio; CI: Confidence interval; VAT: Visceral adipose tissue; glcm: Gray-level co-occurrence matrix; 1: Follow-up; glszm: Gray-level size zone matrix; glrlm: Gray-level run length matrix; gldm: Gray-level dependence matrix.

Table 5 The features selected from feature subset 4 using least absolute shrinkage and selection operator, with the Cox regression analysis

Covariate	HR (95%CI)	P value
clinical_M	2.13 (1.26-3.60)	0.005
clinical_T	1.91 (1.23-2.95)	0.004
MUSCLE_original_glszm_LargeAreaEmphasis1	1.00 (1.00-1.00)	0.003
MUSCLE_original_shape_Sphericity0	1.02 (1.00-1.03)	0.049
SAT_original_firstorder_Skewness0	0.71 (0.46-0.99)	0.041
VAT_original_firstorder_10Percentile1	1.01 (1.00-1.03)	0.032
VAT_original_firstorder_90Percentile1	1.11 (1.04-1.19)	0.002
VAT_original_firstorder_Mean1	1.04 (1.01-1.07)	0.002
VAT_original_glcm_JointEnergy1	12.19 (0.38-394.85)	0.042
VAT_original_gldm_DependenceVariance1	0.94 (0.91-0.98)	0.002
VAT_original_glrlm_LongRunLowGrayLevelEmphasis1	0.00 (0.00-2.39)	0.049
VAT_original_glrlm_RunEntropy1	0.09 (0.02-0.37)	0.001
VAT_original_glszm_GrayLevelNonUniformityNormalized1	5606.87 (0.12-270661365.71)	0.041
VAT_original_shape_SurfaceVolumeRatio0	1.76 (0.97-3.21)	0.045
delta_VAT_original_shape_Sphericity1	0.24 (0.06-1.02)	0.042

HR: Hazard ratio; CI: Confidence interval; VAT: Visceral adipose tissue; glcm: Gray-level co-occurrence matrix; glszm: Gray-level size zone matrix; glrlm: Gray-level run length matrix; gldm: Gray-level dependence matrix; 0: Pretreatment; 1: Follow-up.

Table 6 Summary of all final selected clinical, body composition analysis, and radiomic features across feature subsets 1 to 4

	Feature subset 1	Feature subset 2	Feature subset 3	Feature subset 4
Clinical	clinical_T, clinical_N, clinical_M, ECOG	clinical_T, clinical_M	clinical_T, clinical_M	clinical_T, clinical_M
BOA	delta_SAT, TAT/SMI, sarco0
Radiomics (pretreatment)		MUSCLE_original_shape_Sphericity0, VAT_shape_Elongation0, VAT_shape_Sphericity0, VAT_shape_SurfaceVolumeRatio0, VAT_firstorder_Mean0, VAT_glcm_ClusterShade0		MUSCLE_original_shape_Sphericity0, VAT_shape_SurfaceVolumeRatio0, SAT_firstorder_Skewness0
Radiomics (f/u)			MUSCLE_original_glszm_LargeAreaEmphasis1, VAT_firstorder_10Percentile1, VAT_firstorder_90Percentile1, VAT_firstorder_Mean1, VAT_firstorder_Minimum1, VATl_glcm_JointEnergy1, VAT_glcm_JointEntropy1, VAT_gldm_DependenceVariance1, VAT_glrlm_LongRunLowGrayLevelEmphasis1, VAT_glrlm_RunEntropy1, VAT_glszm_GrayLevelNonUniformityNormalized1, VAT_glszm_SizeZoneNonUniformity1	MUSCLE_glszm_LargeAreaEmphasis1, VAT_firstorder_10Percentile1, VAT_firstorder_90Percentile1, VAT_firstorder_Mean1, VAT_glcm_JointEnergy1, VAT_gldm_DependenceVariance1, VAT_glrlm_LongRunLowGrayLevelEmphasis1, VAT_glrlm_RunEntropy1, VAT_glszm_GrayLevelNonUniformityNormalized1, delta_VAT_shape_Sphericity1

ECOG: Eastern Cooperative Oncology Group; sarco: Sarcopenia; 0: Pretreatment; TATSMR1: Total adipose tissue index/skeletal muscle index ratio; SAT: Subcutaneous adipose tissue; 1: Follow-up; VAT: Visceral adipose tissue; glcm: Gray-level co-occurrence matrix; glszm: Gray-level size zone matrix; glrlm: Gray-level run length matrix; Gldm: Gray-level dependence matrix; f/u: Follow-up; BOA: Body organ analysis.

Table 7 Model performances across different input combinations for 1-year, 2-year, and 3-year survival prediction

Input	Models	1-year			2-year			3-year
		AUC	Sensitivity	Specificity	AUC	Sensitivity	Specificity	AUC	Sensitivity	Specificity
Subset 1: No-radiomics	SVC	0.691	0.46	0.83	0.73	0.70	0.66	0.64	0.73	0.51
	LR	0.67	0.58	0.73	0.841	0.73	0.82	0.66	0.63	0.68
	ETC	0.66	0.50	0.78	0.77	0.65	0.78	0.71	0.88	0.45
	Nomogram	0.67	0.51	0.76	0.70	0.86	0.44	0.711	0.65	0.71
Subset 2: Pretreatment	SVC	0.66	0.81	0.47	0.73	0.82	0.54	0.68	0.75	0.52
	LR	0.65	0.67	0.56	0.771	0.70	0.70	0.761	0.67	0.80
	ETC	0.64	0.65	0.54	0.76	0.80	0.56	0.68	0.49	0.85
	Nomogram	0.711	0.77	0.61	0.69	0.74	0.54	0.69	0.82	0.47
Subset 3: Follow-up	SVC	0.60	0.55	0.65	0.74	0.69	0.67	0.53	0.68	0.45
	LR	0.61	0.62	0.60	0.811	0.71	0.80	0.53	0.58	0.59
	ETC	0.60	0.56	0.63	0.76	0.78	0.61	0.64	0.61	0.64
	Nomogram	0.701	0.73	0.59	0.71	0.71	0.64	0.701	0.75	0.61
Subset 4: Combination	SVC	0.60	0.42	0.79	0.84	0.63	0.82	0.59	0.47	0.66
	LR	0.61	0.80	0.36	0.911	0.81	0.88	0.55	0.68	0.54
	ETC	0.60	0.51	0.70	0.81	0.62	0.85	0.64	0.62	0.64
	Nomogram	0.731	0.85	0.52	0.73	0.64	0.69	0.741	0.72	0.67

¹The highest area under the curve values within each feature subset for each time point.

AUC: Area under the time-dependent receiver operating characteristic curve; SVC: Support vector classifier; LR: Logistic regression; ETC: Extra trees classifier.