Table 1 Multivariate Cox regression of GC patients’ prognosis in Cohort 3

From: Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer

Characteristics

Classification

P-value

Hazard ratio

95% Cl

TNM staging

I

0.010

Reference

 

II

 

1.19

0.07–20.88

III

 

4.02

0.24–66.59

IV

 

12.86

0.70–237.08

Macroscopic appearance

Borrmann I

0.789

Reference

 

Borrmann II

 

3.69

0.47–28.78

Borrmann III

 

3.35

0.43–25.97

Borrmann IV

 

3.45

0.41–29.25

EGC

 

1.96

0.06–60.26

Vascular tumor embolus

No

0.463

Reference

 

Yes

 

1.38

0.59–3.24

Metabolic risk factor*

Low

5.276 × 10−5

Reference

 

High

 

7.53

2.83–20.04

  1. Multivariate Cox regression was applied to the 28-PM model and clinical parameters to identify independent prognostic factors. Parameters with P < 0.05 are recognized as statistically significant, signifying their role as independent prognostic factors for GC. P-values were calculated based on data from n = 179 independent patient samples and Wald test.
  2. CI confidence interval, EGC early gastric cancer.
  3. *The classifier was derived from the 28-PM model cutoff value, represents as a high-risk group and a low-risk group for the GC patients.
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