Table 4 Important features in large SNPs model.

From: Predictive model of castration resistance in advanced prostate cancer by machine learning using genetic and clinical data: KYUCOG-1401-A study

#

Parameter

Gene name

Score

Median weight

1

rs12979986

ZNF702P

0.988

−0.106

2

rs9625031

SRRD

0.968

−0.098

3

M-category

 

0.629

−0.038

4

rs1931229

VGLL2

0.512

−0.103

5

rs1660281

—

0.488

0.064

6

rs10064620

—

0.459

0.060

7

Gleason score

 

0.432

−0.066

8

rs10860210

RMST

0.395

−0.048

9

rs941207

BAZ2A

0.385

0.057

10

rs9868579

RPN1

0.317

−0.031

11

rs62174680

—

0.300

0.040

12

rs11232056

LOC101928443

0.259

0.040

13

rs8124833

C20orf78

0.251

0.037

14

rs74522810

—

0.234

−0.049

15

rs74369678

LRRN1

0.205

−0.036

16

NA (chr3:74213366)

—

0.190

0.104

17

rs2035081

PRIM1

0.188

−0.045

18

T-Bil

 

0.176

0.033

19

Glucose

 

0.149

−0.041

20

rs79404120

FAM19A5

0.146

0.058

21

rs11672661

COL5A3

0.129

−0.030

22

rs28625772

—

0.112

0.028

23

rs9298681

—

0.105

−0.036

  1. NA not available, SNP single nucleotide polymorphism, T-Bil total bilirubin.