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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