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)
| 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 |
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