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Table 1: Univariate logistic regression analyses for predicting 1p/19q codeletion among the training dataset
Predictor Ratio Odds Ratio (95% CI) P Value
Maximum diameter (cm) 1st Quartile: 3rd quartile 1.33 (0.70–2.49) .381
Margins Irregular: sharp 1.04 (0.47–2.33) .917
Texture Homogeneous (<75%): homogeneous (>75%) 12.33 (4.66–31.58) <.001^{^a}
Peritumoral edema Yes: no 1.42 (0.62–3.23) .973
Hydrocephalus No: yes 2.32 (0.88–6.11) .089
Midline shift (cm)^{^b} 1st Quartile: 3rd quartile 4.27 (1.49–12.23) .027^{^a}
Enhancement Yes: no 1.28 (0.57–2.86) .555
Necrosis Yes: no 2.18 (0.61–7.69) .228
T2* blooming Yes: no 6.92 (2.04–23.49) .002^{^a}
Cortical infiltration Yes: no 2.02 (0.67–6.10) .212
Cyst No: yes 1.18 (0.48–2.91) .715
T2 FLAIR mismatch sign^{^c} No: yes 22.50 (6.26–∞) <.001^{^a}
Gliomatosis Yes: no 1.13 (0.18–7.08) .896
Primary lobe Frontal: nonfrontal 5.68 (2.08–15.44) .001^{^a}
Age 3rd Quartile: 1st quartile 3.38 (1.71–6.71) <.001^{^a}
Sex Female: male 1.55 (0.69–3.50) .283
↵a Significant.
↵b Analyzed as a restricted cubic spline function of the predictor.
↵c Median unbiased estimate derived with exact logistic regression.