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. Author manuscript; available in PMC: 2022 Nov 1.
Published in final edited form as: Urol Oncol. 2021 Sep 25;39(11):791.e17–791.e24. doi: 10.1016/j.urolonc.2021.08.018

Table 2.

Univariable and multivariable Cox models for predictors of metastasis-free probability (N=254)

Univariable Multivariable
N(E) HR [95% CI] p-value N(E) HR [95% CI] p-value
VHL Yes 152 (48) 1.41 [0.86 2.32]
-
0.18 ---
No 102 (23) REF ---
PBRM1 Yes 91 (34) 1.78 [1.112.83]
-
0.016 1.41 [0.85 2.35]
-
0.18
No 163 (37) REF ---
SETD2 Yes 32 (19) 3.30 [1.94 5.59]
-
<.001 2.09 [1.19 3.67]
-
0.011
No 222 (52) REF ---
BAP1 Yes 19 (9) 2.44 [1.21 4.93]
-
0.013 0.83 [0.37 1.87]
-
0.65
No 235 (62) REF ---
KDM5C Yes 19 (8) 1.58 [0.76 3.31]
-
0.22 ---
No 235 (63) REF ---
Nomogram Linear Predictor* 254 (71) 2.62 [2.10 3.27]
-
<.001 2.58 [2.01 3.30]
-
<.001
*

The nomogram linear predictor includes the following factors: age, gender, mode of presentation, evidence of lymphadenopathy, evidence of necrosis and tumor size based on preoperative imaging.

The following equation from Raj et al, was used to calculate the value of the nomogram linear predictor: −3.1830084 − 0.00065242845*age + 0.10166342*gender + 0.56585476*presentation + 1.0072686*lymphadenopathy + 0.26592168*necrosis + 0.65408506*size - 0.0086883408*max(size-2, 0)**3 + 0.013366678*max(size-4.8, 0)**3-0.0046783373*max(size-10, 0)**3. Size was treated as a cubic spline.

N = Total # patients for level; E = # events for level; HR = hazard ratio; 95%CI = 95% confidence interval