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Table 2 Correlation analysis between ESCC-PS and patient characteristics

From: From pixels to patient care: deep learning-enabled pathomics signature offers precise outcome predictions for immunotherapy in esophageal squamous cell cancer

Patient characteristics

ESCC-PS 1

(N = 19)

ESCC-PS 2

(N = 13)

ESCC-PS 3

(N = 11)

P value

Age

    

  ≤ 60

10 (52.6%)

8 (61.5%)

6 (54.5%)

0.879

 > 60

9 (47.4%)

5 (38.5%)

5 (45.5%)

 

Gender

    

 Male

15 (78.9%)

11 (84.6%)

8 (72.7%)

0.892

 Female

4 (21.1%)

2 (15.4%)

3 (27.3%)

 

Smoking history

    

 No

12 (63.2%)

7 (53.8%)

6 (54.5%)

0.838

 Yes

7 (36.8%)

6 (46.2%)

5 (45.5%)

 

Drinking history

    

 No

9 (47.4%)

8 (61.5%)

6 (54.5%)

0.730

 Yes

10 (52.6%)

5 (38.5%)

5 (45.5%)

 

T stage

    

 T1-T2

1 (5.3%)

3 (23.1%)

1 (9.1%)

0.413

 T3-T4

18 (94.7%)

10 (76.9%)

10 (90.9%)

 

N stage

    

 N0-N1

5 (26.3%)

8 (61.5%)

4 (36.4%)

0.131

 N2-N3

14 (73.7%)

5 (38.5%)

7 (63.6%)

 

Stage

    

 III

6 (31.6%)

5 (38.5%)

2 (18.2%)

0.581

 IV

13 (68.4%)

8 (61.5%)

9 (81.8%)

 

Lung metastasis

    

 No

14 (73.7%)

11 (84.6%)

9 (81.8%)

0.892

 Yes

5 (26.3%)

2 (15.4%)

2 (18.2%)

 

Bone metastasis

    

 No

18 (94.7%)

13 (100.0%)

10 (90.9%)

0.726

 Yes

1 (5.3%)

0 (0.0%)

1 (9.1%)

 

Liver metastasis

    

 No

16 (84.2%)

13 (100.0%)

9 (81.8%)

0.351

 Yes

3 (15.8%)

0 (0.0%)

2 (18.2%)

 

Radiotherapy

    

 No

8 (42.1%)

2 (15.4%)

2 (18.2%)

0.217

 Yes

11 (57.9%)

11 (84.6%)

9 (81.8%)

 

Chemotherapy

    

 No

5 (26.3%)

4 (30.8%)

3 (27.3%)

0.961

 Yes

14 (73.7%)

9 (69.2%)

8 (72.7%)

 

PD-L1

    

 < 57.5%

17 (89.5%)

10 (76.9%)

7 (63.6%)

0.218

  ≥ 57.5%

2 (10.5%)

3 (23.1%)

4 (36.4%)