Sequential algorithms combining non-invasive markers and biopsy for the assessment of liver fibrosis in chronic hepatitis B

Table 2 Performance of the non-invasive methods and of the algorithm A in detecting significant fibrosis (≥ F2 by METAVIR) in patients with CHB

	Fibrotest	Forns		APRI		GUCI	Hui’s model	Algorithm A
Classified cases (%)	100	63.3		66.2		100	100	100
Cut-off	F2	4.2	6.9	0.5	1.5	0.2	0.15	na
Sensitivity (%)	80.8	58.3	14.6	70.8	27.1	66.7	50	100
Specificity (%)	90	78.3	100	87	95.7	95.7	90.9	91.3
PPV (%)	95.5	90.6	100	94.1	97.9	97.9	96.3	96
NPV (%)	64.3	53.5	35.9	62.2	39.7	58.9	45.8	100
LR +	8.1	2.69	0.146	5.45	6.3	15.5	5.49	11.49
LR -	0.21	0.53	0.85	0.36	0.76	0.35	0.55	0
Accuracy (%)	83.3	64.8	42.3	76.1	49.3	76.1	62.2	97.2
AUC (95% CI)	0.85 (0.75-0.95)	0.63 (0.50-0.76)		0.72 (0.58-0.86)		0.81 (0.70-0.92)	0.71 (0.56-0.86)	0.96 (0.92-1)

APRI: aspartate aminotransferase to platelets ratio; GUCI: Goteborg University Cirrhosis Index; na: not available; PPV: positive predictive value; NPV: negative predictive value; LR+: positive likelihood ratio; LR-: negative likelihood ratio; AUC: area under the curve; CI: confidence interval.