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Table 3 Univariate and multivariate logistic regression predicting PCa and csPCa (logistic regression analysis)

From: Development and internal validation of PI-RADs v2-based model for clinically significant prostate cancer

 

PCa

csPCa

 

Univariate analysis

Multivariate analysis

Univariate analysis

Multivariate analysis

 

OR (95% CI)

p value

OR (95% CI)

p value

OR (95% CI)

p value

OR (95% CI)

p value

PSA

1.06 (1.04–1.09)

< 0.001

1.04 (0.94–1.08)

0.14

1.02 (1.01–1.03)

< 0.001

1.00 (0.98–1.02)

0.63

PV

0.99 (0.98–1.00)

0.003

0.97 (0.93–1.04)

0.11

1.00 (0.99–1.01)

0.76

0.99 (0.98–1.00)

0.12

PSAD*10

1.55 (1.34–1.79)

< 0.001

1.32 (1.01–1.72)

0.04

1.07 (1.03–1.11)

0.001

1.01 (1.00–1.02)

0.01

Age

1.11 (1.08–1.16)

< 0.001

1.15 (1.10–1.21)

< 0.001

1.17 (1.13–1.22)

< 0.001

1.18 (1.12–1.23)

< 0.001

PIRADS

1.18 (1.04–1.31)

0.03

2.22 (1.07–4.63)

0.03

1.29 (1.03–1.77)

0.01

2.54 (1.25–5.17)

0.01

  1. PCa prostate cancer, csPCa clinically significant prostate cancer; prostate-specific antigen, PSAD*10 prostate-specific antigen density*10, PIRADS v2 Prostate Imaging Reporting and Data System version 2, PV prostate volume, OR odds ratio