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. 2023 Mar 6;10(3):331. doi: 10.3390/bioengineering10030331

Table 3.

Univariate and multivariate logistic regression analysis for LNM in cervical cancer.

Variable Univariate Analysis Multivariate Analysis
Odds Ratio (95 % CI) p Odds Ratio (95 % CI) p
APTw (%) 3.523 (1.676, 7.404) 0.001 3.115 (1.059, 9.162) 0.039
MK 1.005 (1.001, 1.008) 0.011 1.000 (0.991, 1.008) 0.911
MD (×10−3 mm2/s) 0.997 (0.994, 1.000) 0.029 0.998 (0.990, 1.005) 0.503
Age 1.017 (0.968, 1.068) 0.507
Tumor size 1.041 (1.008, 1.075) 0.016 0.949 (0.878, 1.025) 0.184
Menopausal status 1.565 (0.504, 4.856) 0.439
Histological classification 0.281 (0.032, 2.440) 0.250
Histologic grade 5.687 (1.585, 20.414) 0.008 1.628 (0.207, 12.781) 0.643
Depth of invasion 23.111 (2.808, 190.202) 0.003 25.473 (1.351, 480.376) 0.031
SCC-Ag level 3.231 (0.809, 12.896) 0.097
Vascular invasion 1.636 (0.490, 5.467) 0.424

All factors with p < 0.05 in univariate analysis were included in multivariate regression analysis. The bold typeface in the table indicates the logistic regression analysis with statistical significance. CI = confidence interval; LNM = lymph node metastasis; APTw = amide proton transfer-weighted; MK = mean kurtosis; MD = mean diffusivity; SCC-Ag = squamous cell carcinoma antigen.