Skip to main content
Insights into Imaging

Table 4 Construction of clinical, DLCT, and combined models through multivariate logistic analysis

From: Dual-layer spectral-detector CT for predicting microsatellite instability status and prognosis in locally advanced gastric cancer

Models

β

S.E

Wald

p value

OR

95% CI for OR

Lower

Upper

Clinical

 Tumor location (antrum/pylorus)

1.468

0.366

16.117

 < 0.001

4.343

2.120

8.894

 CT_N Staging (N0)

1.752

0.492

12.697

 < 0.001

5.768

2.200

15.121

 Constant

 − 1.841

0.269

46.814

 < 0.001

0.159

  

DLCT

 NIDVP

 − 12.899

2.925

19.448

 < 0.001

2.500E − 6

8.097E − 9

0.001

 ZeffVP

 − 1.405

0.506

7.715

0.005

0.245

0.091

0.661

 λHUVP

 − 0.943

0.310

9.222

0.002

0.390

0.212

0.716

 Constant

15.922

4.414

13.013

 < 0.001

8.216E + 06

  

Combined

 Tumor location (antrum/pylorus)

1.194

0.441

7.333

0.007

3.301

1.391

7.837

 CT_N Staging (N0)

1.280

0.561

5.201

0.023

3.597

1.197

10.808

 CDLCT

0.937

0.171

30.074

 < 0.001

2.552

1.826

3.567

 Constant

 − 0.740

0.318

5.404

0.020

0.477

  
  1. A stepwise forward method was used to assess the best independent predictor of microsatellite instability status
  2. β Coefficient, CDLCT Combined DLCT parameters, CI Confidence interval, DLCT Dual-layer spectral detector CT, λHU The slope of the spectral curve, NID Normalized iodine density, OR Odds ratio, S.E. Standard error, VP Venous phase, Wald Wald chi-square, Zeff Effective atomic number
Back to article page