Table 3.

Multivariate logistic regression models predicting PCa in patients undergoing biopsy.

Model	Covariates	B	SE	OR	95%CI of OR		p-Value
					INF	SUP
A	Age	0.055	0.013	1.056	1.030	1.084	<0.0001
	CII	−1.693	0.295	0.184	0.103	0.328	<0.0001
	Intercept	−3.478	0.867	0.031			<0.0001
B	Age	0.058	0.13	1.060	1.033	1.088	<0.0001
	CII × age	−0.025	0.04	0.975	0.967	0.984	<0.0001
	Intercept	−3.714	0.870	0.024			<0.0001
C	PSA	0.086	0.029	1.090	1.030	1.153	0.003
	CII	−1.666	0.293	0.189	0.106	0.336	<0.0001
	Intercept	−0.447	0.220	0.639			0.042
D	PSA	0.118	0.032	1.125	1.056	1.198	<0.0001
	CII × PSA	−0.188	0.038	0.829	0.769	0.893	<0.0001
	Intercept	−0.714	0.231	0.489			0.002
E	PV	−0.050	0.007	0.952	0.938	0.966	<0.0001
	CII	−1.581	0.305	0.206	0.113	0.374	<0.0001
	Intercept	2.068	0.302	7.913			<0.0001
F	PV	−0.045	0.007	0.956	0.943	0.970	<0.0001
	CII × PV	−0.037	0.008	0.964	0.948	0.980	<0.0001
	Intercept	1.839	0.293	6.285			<0.0001

PCa, prostate cancer; PSA, prostate specific antigen; PV, prostate volume; CII, chronic inflammatory infiltrate; B, regression coefficient; SE, standard error; OR, odds ratio.