Table 2 Univariate and multivariate logistic regression analyses to detect PCa and CS PCa

 1–2

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

 3

1.36

0.596

3.102

0.465

1.214

0.474

3.113

0.686

1.241

0.462

3.335

0.668

1.051

0.337

3.272

0.932

 4

3.024

2.275

4.019

< 0.001

2.398

1.745

3.296

< 0.001

3.775

2.78

5.126

< 0.001

3.29

2.316

4.674

< 0.001

 5

5.854

2.993

11.448

< 0.001

4.352

2.148

8.817

< 0.001

7.074

3.599

13.905

< 0.001

5.241

2.54

10.811

< 0.001

  < 0.1

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

 0.1–0.19

4.234

1.191

15.051

0.026

3.505

0.723

16.982

0.119

3.8

0.826

17.482

0.086

2.171

0.307

15.373

0.428

 0.19–0.23

2.099

1.087

4.053

0.027

3.237

1.026

10.213

0.045

2.132

0.974

4.666

0.058

4.787

0.974

23.536

0.054

  ≥ 0.23

3.97

2.622

6.01

< 0.001

1.904

1.063

3.411

0.03

4.185

2.564

6.83

< 0.001

2.087

1.089

4

0.027

  ≥ 0.24

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

 0.18–0.24

2.597

0.915

7.375

0.073

3.703

0.621

22.072

0.151

3.141

0.945

10.442

0.062

6.748

0.628

72.518

0.115

 0.14–0.18

1.493

0.88

2.533

0.137

0.845

0.383

1.866

0.677

1.795

0.984

3.275

0.056

1.124

0.396

3.193

0.827

  < 0.14

2.272

1.674

3.084

< 0.001

1.39

0.907

2.129

0.131

2.409

1.686

3.442

< 0.001

1.662

0.959

2.879

0.07

  < 4

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

 4–10

3.755

1.062

13.277

0.04

0.967

0.225

4.153

0.964

4.071

0.91

18.21

0.066

0.802

0.134

4.802

0.809

 10–20

2.608

1.379

4.932

0.003

0.563

0.186

1.708

0.31

2.847

1.343

6.035

0.006

0.62

0.18

2.14

0.45

  ≥ 20

3.154

2.03

4.9

< 0.001

0.208

0.045

1.062

0.051

3.585

2.147

5.987

< 0.001

0.333

0.072

1.54

0.159