Noninvasive models for assessment of liver fibrosis in patients with chronic hepatitis B virus infection

Table 1 Advantages and disadvantages of liver biopsy and noninvasive models for detecting liver fibrosis

	Liver biopsy	Noninvasive models
Advantages	Gold standard to assess fibrosis	Non-invasive
	Direct observation and quantitative assessment of fibrosis, inflammation and steatosis	Inter-laboratory reproducibility
	Different stage by different scoring systems	High applicability and wide availability for repeated assays
	Diagnosing different forms of liver disease	Reasonable cost
	Accurately assessing progression of liver disease or the effect of therapy	Accurate assessment of cirrhosis and minimal/no fibrosis
Disadvantages	Invasive	Less accurate for intermediate fibrosis stages
	Sampling error and inter-observer differences	False positive values
	Unsuitable for repeated assays	Scores may change in different disease stages
	Risk of complications, rare major complications, morbidity and mortality	Unsuitable for diagnosing liver disease
	Expensive	Not quantitative

Table 2 Performance of noninvasive tests for diagnosis of significant fibrosis (≥ F2) and cirrhosis (F4) in hepatitis B virus-infected patients

Ref.	Year	n	Diagnosis of significant fibrosis				Diagnosis of cirrhosis
			AUC	Cutoff	Se/Sp (%)	PPV/NPV (%)	AUC	Cutoff	Se/Sp (%)	PPV/NPV (%)
Myers et al[68]	2003	209	0.78	< 0.2	89/52	43/92	NA
				> 0.8	18/99	92/75	NA
Zeng et al[52]	2005	373	0.84	< 3.0	94.8/44.1	70.1/86.1	0.84	> 8.7	35.3/95.2	91.1/51.6
Hui et al[51]	2005	235	0.79	≤ 0.15	51.5/84.6	74.5/66.7	NA
				> 0.5	16.2/97.4	84.6/57.1	NA
Zeng et al[19]	2013	198	NA				0.89	-1.03	88.0/88.1	68.7/96.1
Zeng et al[21]	2015	237	NA				0.87	-1.89	88.6/78.2	48.2/96.8
Seto et al[59]	2011	237	0.776	< 1.662	73.3/78.2	56.4/88.4	NA
Zhang et al[31]	2008	137	NA	NA	45.3/98.9	93.7/91.3	NA
Kim et al[55]	2007	346	NA				0.89	> 12	35.6/99.6	96.3/82.8
			NA					< 5	100/32	32/100
Chen et al[56]	2008	653	NA				0.907	0.1	92.8/74.1	52/97.1
Zhou et al[57]	2010	386	0.81	< 0.1	90.41/23.95	60.92/65.57	0.89	≥ 1.5	27.27/97.73	52.94/93.50
Taefi et al[62]	2015	152	NA				0.77	0.0880	82.7/61.0	52.4/87.1
Gümüşay et al[48]	2013	58	NA	NA	90/100	100/96.4	NA
Wang et al[42]	2013	349	0.856	0.75	56.5/94.1	92.9/61.5	0.956	0.9800	64.3/94.6	47.4/97.2
Lee et al[63]	2015	482	0.747	0.0625	72.3/67.7	93.4/58.0	0.811	0.0685	88.6/66.0	67.6/87.9
Liu et al[32]	2012	114	0.762	< 1.68	72.4/69.6	71.2/70.8	0.781	< 2.53	72.7/84.5	33.4/96.7
Mohamadnejad et al[66]	2006	276	0.91	4.72	97/52	26/99	NA
Fung et al[67]	2008	1268	0.85	6.87	82.1/73.5	67.6/85.9	0.89	8.93	78.0/85.7	69.6/90.3

AUC: Area under receiver operating curve; NA: Not available; NPV: Negative predictive value; PPV: Positive predictive value.

Table 3 Performance of noninvasive tests for identification of fibrosis in hepatitis B virus-infected patients with normal or minimally elevated serum alanine transaminase

Ref.	Year	n	Fibrosis	Cutoff	AUC	Se/Sp, %	PPV/NPV, %
Zeng et al[30]	2014	278	F4	0.62	0.830	86.7/75.0	49.6/95.2
FIB-4
Seto et al[59]	2011	237	F2		0.726	NA	NA
Wang et al[35]	2013	239	F2		0.770	54/85	86/78
			F3		0.810	67/80	37/97
APRI
Seto et al[59]	2011	237	F2		0.727	NA	NA
Wang et al[35]	2013	239	F2		0.770	59/79	59/70
			F3		0.770	63/72	28/94
Park et al[69]	2011	124	F3	16.5	0.800	90.6/50.0	NA
				18.5	0.800	31.3/89.5	NA
Seto et al[59]	2011	237	F2		0.797	NA	NA
Wang et al[70]	2015	283	F2		0.820	NA	NA

AUC: Area under receiver operating curve; NA: Not available; NPV: Negative predictive value; PPV: Positive predictive value.