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Table 2 Odds ratios for breast cancer computed by univariate and multivariate conditional logistic regression analyses on the contralateral breasts of patients with cancer and controls (n = 102, 51 women with a cancer diagnosis and 51 controls with benign biopsy, matched by age and year of magnetic resonance imaging)

From: Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer

Conditional logistic regression models

Variables included in conditional logistic regression analyses

Wash-in slope variance (WISV) (unit)

Signal enhancement ratio volume (SERV) (cm3)

BPE% (%)

OR (95 % CI); p value

OR (95 % CI); p value

OR (95 % CI); p value

WISV univariate

1.7 (1.1, 2.7); p = 0.014

-

-

SERV univariate

-

3.1 (1.3, 7.5); p = 0.014

-

WISV + SERV

1.7 (1.1, 2.8); p = 0.017

3.5 (1.2, 9.9); p = 0.019

-

Base factors + WISV + SERVa

1.8 (1.1, 2.9); p = 0.020

3.7 (1.2, 11.2); p = 0.020

-

BPE% univariate

-

-

3.1 (1.2, 7.9); p = 0.018

WISV + SERV + BPE%

1.7 (1.1, 2.8); p = 0.024

3.4 (1.1, 10.6); p = 0.038

1.1 (0.3, 3.8); p = 0.897

  1. Odds ratio (OR) for WISV is per 0.01-unit difference. OR for SERV is per 100-cm3 difference. OR for percentage background parenchymal enhancement relative to breast volume (BPE%) is per 20 % point difference. aBase factors = menopausal status (premenopausal vs postmenopausal), family history of breast cancer (yes/no, first to third degree family member), and Breast Imaging-Reporting and Data System (BI-RADS)-based mammographic density categories