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Table 3 Univariate and multivariate survival analysis results of 227 patients with GC

From: The red distribution width and the platelet distribution width as prognostic predictors in gastric cancer

Clinicopathological feature

Univariatea(OS)

Multivariateb(OS)

Univariatea(DFS)

Multivariateb(DFS)

HR (95% CI)

P value

HR(95% CI)

P value

HR (95% CI)

P value

HR(95% CI)

P value

RDW(<13/≥13)

1.801 (0.985–3.291)

0.056

  

1.807 (1.015–3.217)

0.044

  

PDW(<11.5/≥11.5)

0.701 (0.385–1.275)

0.244

  

0.754 (0.425–1.337)

0.333

  

Gender(Male/Female)

0.764 (0.355–1.648)

0.493

  

0.908 (0.452–1.827)

0.787

  

Age(<60/≥60)

1.541 (0.844–2.814)

0.160

  

1.535 (0.863–2.730)

0.044

  

Tumor diameter(≤4/>4)

2.890 (1.553–5.375)

0.001

  

2.633 (1.465–4.731)

0.001

  

Differentiation (Well/Moderate/ Poor)

1.968 (1.027–3.772)

0.041

  

1.650 (0.926–2.941)

0.089

  

Depth of tumor (T1 + T2/T3 + T4)

2.169 (1.613–2.916)

< 0.001

1.722(1.170–2.535)

0.006

2.097 (1.569–2.802)

< 0.001

1.655(1.130–2.422)

0.010

Lymph node metastasis (N0/N1 + N2 + N3)

5.548 (2.335–13.181)

< 0.001

  

4.548 (2.118–9.763)

< 0.001

  

Distance metastasis (M0/M1)

2.403 (1.112–5.193)

0.026

  

2.137 (0.996–4.584)

0.051

  

pStage(I + II/III + IV)

7.841 (3.075–19.994)

< 0.001

4.311(1.591–11.682)

0.004

6.179 (2.755–13.858)

< 0.001

3.517(1.470–8.413)

0.005

CEA(≤5/>5)

1.240 (0.552–2.788)

0.602

  

1.116 (0.500–2.492)

0.789

  

CA125(≤35/>35)

2.606 (0.353–19.240)

0.348

  

2.606 (0.353–19.240)

0.348

  

CA199(≤39/>39)

2.405 (1.173–4.930)

0.017

  

2.478 (1.249–4.917)

0.009

  
  1. Abbreviations: OS overall survival, DFS disease-free survival, HR hazard ratio, CI confidence interval, RDW red blood cell distribution width, CEA carcinoembryonic antigen, CA125 carbohydrate antigen 125, CA199 carbohydrate antigen 199
  2. aPerformed using the Kaplan–Meier analysis model and the log-rank test; values of P < 0.05 in the univariate analysis were entered into a multivariate analysis
  3. bperformed using Cox proportional hazards models with the forward likelihood method