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. 2022 Sep 20;12:916988. doi: 10.3389/fonc.2022.916988

Table 4.

Univariate and multivariable logistic analysis of clinical, MR and pathological features for predicting TNBC subtypes in the training set.

Variable No. Univariate analysis Multivariate analysis
OR (95%CI) P value OR (95%CI) P value
Clinicopathologic factors
Age (years) 1.003 (0.967,1.041) 0.853
Axillary lymph node 0.336 (0.102,1.112) 0.074
 Negative 55 Ref
 Positive 33
Menopausal status 1.242 (0.454,3.398) 0.672
 Premenopausal 52 Ref
 Postmenopausal 36
Location 1.429 (0.525,3.886) 0.485
 L 50 Ref
 R 38
Pathological grade 3.883 (1.359,11.096) 0.019 1.776 (0.444, 7.098) 0.417
 2 53 Ref
 3 35
DCIS present 0.223 (0.027,1.818) 0.161
 No 74 Ref
 yes 14
MR factors
Size (mm)
 ≤20 20 Ref
 >20and≤50 50 0.389 (0.062,2.438) 0.313
 >50 18 1.361 (0.382,4.852) 0.635
T2WI 0.415 (0.064,2.678) 0.356
 Hypo or isointense 83 Ref
 Hyperintense 5
T1WI 4.000 (0.901,17.753) 0.068
 Hypo or isointense 80 Ref
 Hyperintense 8
Shape 0.720 (0.249,2.080) 0.544
 Round/oval 26 Ref
 Irregular 62
Lesion type 0.059 (0.007,0.468) 0.007 0.009 (0,0.147) 0.001
 Mass 55 Ref
 Nonmass & both 33
Internal enhancement pattern 3.395 (1.209,9.535) 0.020 37.197 (4.210,328.681) 0.001
 Heterogeneous 59 Ref
 Rim enhancement 29

DCIS, ductal carcinoma in situ; TNBC, triple-negative breast cancer. P values ≤ 0.05 were considered statistically significant.

Bold means P values ≤0.05 were considered statistically significant.