Predicting hepatocellular carcinoma: A new non-invasive model based on shear wave elastography

Table 3 Diagnostic performance of multivariable model, maximal elasticity of the tumors, mean elasticity of the periphery of tumors, platelet count, cirrhosis, blood and number for the diagnosis of malignant tumor in the experimental cohort (n = 720)

Parameter	AUC	Cutoff value1	Sensitivity (%)	Specificity (%)	Positive predictive value (%)	Negative predictive value (%)	Diagnostic accuracy (%)
Multivariable model	0.77 (0.73, 0.81)	0.653	84	61	85	60	78
Emean of the periphery of tumors	0.69 (0.64, 0.73)	1.375	59	71	84	40	62
Emax of the tumors	0.67 (0.63, 0.72)	2.205	61	65	82	39	62
Edge echo	0.61 (0.57, 0.65)	0.500	39	83	85	34	51
Blood	0.62 (0.56, 0.66)	0.500	70	52	79	40	065
Number	0.46 (0.41, 0.50)	0.500	19	72	64	25	34
PLT	0.34 (0.30, 0.39)	39.500	100	1	72	5	72

¹Cutoff values that maximized the sum of sensitivity and specificity were chosen.

PLT: Platelet count; Emax: Maximal elasticity; Emean: Mean elasticity; AUC: Area under the curve.