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Table 3 Univariate and multivariate logistic regression analyses of clinical features

From: The practical clinical role of machine learning models with different algorithms in predicting prostate cancer local recurrence after radical prostatectomy

Variable

Univariate analysis

Multivariate analysis

Odds ratio (95% CI)

P-value

Odds ratio (95% CI)

P-value

Age

1.040 (0.980–1.103)

0.199

  

Pre-operative PSA

1.004 (0.996–1.011)

0.342

  

Surgical Gleason score

1.583 (1.137–2.203)

0.006

1.503 (0.923–2.448)

0.102

Pathological T stage

1.066 (0.770–1.475)

0.701

  

SVI

1.846 (0.776–4.390)

0.165

  

PNI

0.921 (0.428–1.982)

0.834

  

PSM

1.311 (0.609–2.821)

0.489

  

PI-RADS

2.542 (1.354–4.771)

0.004

2.116 (0.901–4.970)

0.085

PI-RR

3.283 (2.232–4.831)

< 0.001

3.283 (2.175–4.956)

< 0.001

  1. 95% CI = 95% confidence interval; PSA = prostate specific antigen; SVI = seminal vesicle invasion; PNI = perineural invasion; PSM = positive surgical margins; PI-RADS = Prostate Imaging Reporting and Data System; PI-RR = Prostate Imaging for Recurrence Reporting
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Cancer Imaging

ISSN: 1470-7330

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