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Table 4 Variables with independent predictive value obtained from combining different magnetic resonance techniques (multivariate logistic regression) in primary brain tumors

From: Added value of advanced over conventional magnetic resonance imaging in grading gliomas and other primary brain tumors

MR Technique N Predictor variables OR 95% CI P Coefficient (β) Standard error AUC Sensitivity (%) Specificity (%) PPV (%) NPV (%)
MRI 129 Enhancement 23.37 5.85-93.25 <0.0001 3.15 0.71 0.890 95.9 70 91.3 84
Necrosis 9.04 2.61-31.25 0.001 2,20 0.63
MRI 71 Enhancement 11.63 2.35-58.82 0.003 2.46 0.81 0.871 98.2 46.7 87.3 87.5
PWI
DWI
Necrosis 8.48 1.95-37.04 0.005 2.13 0.77
MRS
MRI   Enhancement 16.95 3.89-71.43 <0.0001 2.83 0.75      
PWI 120 Necrosis 5.40 1.32-21.74 0.019 1.69 0.72 0.923 98.9 75.9 92.8 95.6
DWI   rADC 0.22 0.50-0.97 0.045 −1.51 0.75      
  1. AUC, area under the receiver operating characteristic curve; CI, confidence interval; DWI, diffusion-weighted imaging; MRI, magnetic resonance imaging; MRS, MR spectroscopy; N, number of cases from which each classifier was constructed; PWI, perfusion-weighted imaging; rADC, relative apparent diffusion coefficient; OR, odds ratio; PPV, positive predictive value; NPV, negative predictive value.