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Table 2 Multivariate analyses in models including significant univariate analyses for all patients (Cox regression, backward conditional)

From: Disease-specific outcomes of Radical Prostatectomies in Northern Norway; a case for the impact of perineural infiltration and postoperative PSA-doubling time

Characteristic

BF (170 events)†

CF (36 events)

PCD (15 events)*

HR

CI95%

p

HR

CI95%

p

HR

CI95%

p

pT-stage

  

0.001

NS

  

NS

  

  pT2

1

        

  pT3a

1.70

1.14-2.54

0.010

      

  pT3b

2.40

1.45-3.97

0.001

      

Preop PSA

   

NE

  

NS

  

  PSA < 10

1

        

  PSA > 10

1.39

1.01-1.91

0.047

      

Gleason

  

0.032

  

0.019

  

0.087

  3 + 3

1

  

1

  

1

  

  3 + 4

1.05

0.70-1.56

0.81

2.45

0.78-6.90

0.09

3.71

0.41-33.2

0.242

  4 + 3

1.55

0.97-2.47

0.07

2.87

0.91-9.10

0.07

10.47

1.21-90.7

0.033

  4 + 4

1.42

0.68-2.97

0.36

2.73

0.52-14.2

0.23

7.43

0.46-121

0.159

  ≥9

2.39

1.31-4.35

0.004

6.74

2.21-20.6

0.001

15.26

1.65-141

0.016

PNI

  

0.090

  

0.012

  

0.047

  No

1

  

1

  

1

  

  Yes

1.35

0.95-1.92

 

2.48

1.23-5.04

 

3.17

1.02-9.87

 

Non-apical PSM±

  

0.003

  

0.002

NS

  

  No

1

  

1

     

  Yes

1.70

1.20-2.40

 

3.22

1.56-6.64

    

Apical PSM±

  

0.031

NE

  

NS

  

  No

1

        

  Yes

0.69

0.49-0.97

       
  1. Significant p-values in bold (threshold p ≤ 0.05).
  2. Abbreviations: BF biochemical failure, CF Clinical failure, LVI lymphovascular infiltration, NE not entered, due to non-significance in the univariate analyses, NS not significant, the characteristic is removed by the backward conditional analysis due to insignificance, PCD prostate cancer death, PNI Perineural infiltration, Post op RT postoperative radiotherapy, Preop preoperative, PSA Prostate specific antigen, PSM Positive surgical margin.
  3. Tumor Size, pN-stage and LVI were removed by the backward conditional model due to insignificance in all models.
  4. ±Only the subgroups (apical/non-apical PSM) of PSM were entered.
  5. *Due to the low number of events the model was carefully analyzed in advance with the inclusion and removal of variables in an enter analysis to find the most significant in advance before doing the final model with the three variables; Gleason score, perineural infiltration and positive non-apical margin.