Table 4.

Univariate and multivariate logistic regression analysis for predicting lymph node metastasis of prostate cancer

Variable	Univariate analysis				Multivariate analysis*
	β	SE	OR	P	β	SE	OR	P
Serum PSA	0.056	0.020	1.058	0.004
Biopsy Gleason grade groups	0.932	0.320	2.539	0.004
PCa stiffness at 60 Hz	2.167	0.642	8.732	0.001	3.007	1.215	20.223	0.013
PCa stiffness at 90 Hz	2.219	0.740	9.201	0.003	2.069	0.833	7.920	0.013
Maximum diameter of PCa	1.271	0.388	3.566	0.001	1.521 (1.033**)	0.762 (0.515)	4.575 (2.810)	0.046 (0.045)
ADC	−7.413	3.383	0.001	0.028
PCa invasiveness	3.011	1.100	20.308	0.006
LN with restricted diffusion	2.344	1.095	10.421	0.032

SE standard error, OR odds ratio, PSA prostate specific antigen, RP radical prostatectomy, PCa prostate cancer, MRE MR elastography, ADC apparent diffusion coefficient, LN lymph node

^*Because there was collinearity between PCa MRE stiffness at 60 Hz and at 90 Hz, two multivariable models were fitted, respectively, according to forward stepwise regression based on maximum likelihood estimation. In model 1, PCa MRE stiffness at 60 Hz and maximum diameter were independent significant variables for predicting LNM of PCa. In model 2, PCa MRE stiffness at 90 Hz and maximum diameter were independent significant predictors

^**The numbers in parentheses indicated that the corresponding values in model 2