Skip to main content

Table 4 LS-SVM models for the prediction of GRADE, STAGE, METASTASIS and RECURRENCE in prostate cancer

From: A kernel-based integration of genome-wide data for clinical decision support

Outcome

Model

NG*

NC†

AUC (SE)‡

p-value§

GRADE

     

   A

M

24

 

0.8304 (0.0623)

0.2727

 

G

 

8

0.7822 (0.0632)

0.0503

   C

MG

6

8

0.9006 (0.0413)

 

STAGE

     

   A

M

18

 

0.6576 (0.0778)

0.0191

 

G

 

32

0.7936 (0.0631)

0.3466

   C

MG

42

22

0.8528 (0.0550)

 

METASTASIS

     

   A

M

18

 

0.9759 (0.0178)

0.4392

 

G

 

12

0.8114 (0.0755)

0.0166

   C

MG

18

3

0.9868 (0.0121)

 

RECURRENCE

     

   A

M

24

 

0.7208 (0.0936)

0.5392

 

G

 

26

0.4481 (0.1433)

0.0354

   C

MG

32

2

0.7857 (0.0934)

 
  1. *Number of genes selected in each LOO iteration. †Number of copy number variations selected in each LOO iteration. ‡Area under the ROC curve (standard error) obtained with leave-one-out. §Comparison of AUC between each model and the best model in bold [46].
Back to article page

Genome Medicine

ISSN: 1756-994X

Contact us