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. 2022 Feb;12(2):1311–1323. doi: 10.21037/qims-21-189

Table 4. Logistic regression analyses for identifying high- and low-grade EA.

Parameters Univariate analyses Multivariate analyses
OR (95% CI) P value OR (95% CI) P value
Age (year) 1.181* (0.736–1.896) 0.491
Tumor size (mm) 1.521* (0.949–2.436) 0.081 1.553* (0.763–3.161) 0.255
FIGO stage 1.560 (1.247–1.950) <0.001 1.113 (0.825–1.502) 0.482
MTRasym (3.5 ppm) (%) 3.083* (1.663–5.716) <0.001 2.509* (1.052v5.985) 0.038#
ADC (×10−3 mm2/s) 0.394* (0.214–0.725) 0.003 1.258* (0.451–3.513) 0.661
D (×10−3 mm2/s) 0.178* (0.078–0.406) <0.001 0.152* (0.034–0.677) 0.013#
D* (×10−3 mm2/s) 0.872* (0.538–1.412) 0.576
F (%) 1.985* (1.130–3.485) 0.017 1.789* (0.783–4.087) 0.168
DDC (×10−3 mm2/s) 0.481* (0.281–0.823) 0.008 1.884* (0.688–4.871) 0.284
α 3.631* (1.775–7.428) <0.001 1.830* (0.754–5.241) 0.226

*, OR for per 1 standard deviation. #, statistically significant. All factors with P<0.1 in univariate analyses were included in multivariate regression analyses. MTRasym (3.5 ppm), magnetization transfer ratio asymmetry; ADC, apparent diffusion coefficient; D, diffusion coefficient; D*, pseudo-diffusion coefficient; f, perfusion fraction; DDC, distributed diffusion coefficient; α, water molecular diffusion heterogeneity index; OR, odds ratio; CI, confidence interval.