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Abstract

Alpha-fetoprotein is an effective biomarker as an aid in hepatocellular carcinoma detection in many countries. However, alpha-fetoprotein has its limitations, especially in early hepatocellular carcinoma diagnosis. Protein induced by vitamin K absence or antagonist-II is another biomarker that is used for hepatocellular carcinoma detection. The aim of this study is to compare the diagnostic performance of alpha-fetoprotein and protein induced by vitamin K absence or antagonist-II alone and in combination to explore improving biomarker performance as an aid in early hepatocellular carcinoma detection. In this study a total of 582 serum samples including 132 hepatocellular carcinoma patients, 250 non-hepatocellular carcinoma patients, and 200 healthy volunteers were collected. Alpha-fetoprotein and protein induced by vitamin K absence or antagonist-II levels were measured by both chemiluminescent enzyme immunoassay on LUMIPULSE platform and by chemiluminescent microparticle immunoassay on ARCHITECT platform. Receiver operation characteristic curve analyses were performed for each biomarker and in combination. The results showed that Alpha-fetoprotein and protein induced by vitamin K absence or antagonist-II in combination have shown higher area under the curve compared to alpha-fetoprotein alone for diagnosis in whole patients (0.906 vs 0.870) in hepatocellular carcinoma early-stage patients (0.809 vs 0.77) and in hepatitis B virus–related hepatocellular carcinoma patients (0.851 vs 0.788) with ARCHITECT platform. Protein induced by vitamin K absence or antagonist-II showed higher area under the curve than alpha-fetoprotein for diagnosis of hepatitis B virus–related hepatocellular carcinoma patients (0.901 vs 0.788).We conclude that Combining alpha-fetoprotein and protein induced by vitamin K absence or antagonist-II may improve the diagnostic value for early detection of hepatocellular carcinoma. Protein induced by vitamin K absence or antagonist-II performs better than alpha-fetoprotein in diagnosis of hepatitis B virus–related hepatocellular carcinoma patients.

Keywords

Diagnosis alpha-fetoprotein protein induced by vitamin K antagonist-II hepatocellular carcinoma

Introduction

Liver cancer is the sixth most common cancer worldwide (for both sex) and the second most common cause of cancer death. About 745,000 people die annually around the world because of liver cancer.¹ In China, incidence and mortality of liver cancer have significantly increased in recent years. The incidence reached 29/100,000 persons while mortality reached 28.1/100,000 persons in 2010 making liver cancer to be second leading cause of cancer-related death.^2,3 Liver cancer treatment and prevention for general population is a big challenge in China.⁴

Alpha-fetoprotein (AFP) is the most commonly used biomarker for diagnosis of hepatocellular carcinoma (HCC) in China, which is also recommended by the National Health and Family Planning Commission (NHFPC) Guideline.⁵ However, AFP is not tumor specific, which can be produced and released from injured liver tissue or other tissues.^6–8 Elevated serum AFP levels also can be found in patients with non-cancerous liver diseases, for example, hepatitis or cirrhosis.⁹ AFP has limitations in detecting of HCC; thus, new biomarkers for detection of HCC are needed.

Protein induced by vitamin K absence or antagonist-II (PIVKA-II), also called des-gamma carboxyprothrombin (DCP) is another biomarker for HCC.^10–15 PIVKA-II and AFP are independently produced in human body and are not strongly correlated with each other.¹⁶ Therefore, measurement of PIVKA-II and AFP panel may have better diagnostic performances on HCC compared to either AFP or PIVKA-II alone.

The aims of this study were to compare the diagnostic performance of the biomarkers alone and in combination among HCC patients; in metastatic liver cancer patients; in other non-HCC patients including viral hepatitis, cirrhosis, and other benign liver diseases; and in healthy volunteers.

Materials and methods

Patients

From September 2015 to July 2016, 148 HCC patients were recruited, 16 subjects, who were identified as non-first diagnosed HCC, were excluded according to the protocol. A total of 200 healthy volunteers and 250 non-HCC patients including 50 cirrhosis patients, 100 viral hepatitis patients, 50 metastatic hepatic carcinoma patients, and 50 other benign liver diseases were enrolled as controls. This study was performed after approval by the respective institutional review board (IRB) of Beijing Youan Hospital, Capital Medical University. This study was conducted according to the principles expressed in the Declaration of Helsinki. All serum samples are leftover samples. Informed consent process is not required per IRB approval for the use of these types of samples for this exploratory study.

All HCC patients were initially diagnosed by histological findings and without extrahepatic malignancy. HCC staging was determined by tumor–node–metastasis (TNM) staging system that was developed and maintained by the Union for International Cancer Control/American Joint Committee on Cancer (UICC/AJCC).¹⁷ Cirrhosis was diagnosed by histological examination or clinical findings of portal hypertension. Viral hepatitis includes hepatitis B virus (HBV) and hepatitis C virus (HCV) infected subjects, according to the measurement results for these viruses. Metastatic hepatic carcinoma was determined using TNM staging system in patients with documented cancer diagnosis in their medical histories. Benign liver diseases include alcohol or drug induced liver injury, fat liver, and hepatic hemangioma. For healthy volunteers, they were enrolled from those of healthy voluntary donation.

Samples were excluded if they met one of the following criteria: (1) Source patients received warfarin or vitamin K within 1 month, (2) samples are contaminated or with precipitants or floccules, (3) samples are not enough for testing. All the samples were stored at −80°C before testing.

Measurement of PIVKA-II and AFP

Samples were collected before the treatment for HCC groups. Concentrations of PIVKA-II and AFP in serum samples were determined by both chemiluminescent enzyme immunoassay (CLEIA) on LUMIPULSE^® G1200 (Fujirebio Diagnostics, Fujirebio, Japan) platform and chemiluminescent microparticle immunoassay (CMIA) on ARCHITECT^® i2000 (Abbott Diagnostics, Abbott, USA) platform, according to manufacturer’s instructions. The cutoff values for PIVKA-II and AFP are defined as 40 mAU/mL and 20 ng/mL, respectively.^10,12

Statistical analysis

All the statistical analyses were performed using SPSS statistics 22 software (IBM, USA) and MedCalc software version 12.2.1.0 (MedCalc Software, Belgium). Cutoff values of PIVKA-II and AFP are 20 ng/mL and 40 mAU/mL, respectively. The samples with either AFP ⩾ 20 ng/mL or PIVKA-II ⩾ 40 mAU/mL were defined as positives. We used one-way analysis of variance (ANOVA) for continuous variables. To summarize test performance, receiver operating characteristic (ROC) curve was plotted for each biomarker and in combination. Area under the ROC curve (AUC) and its 95% confidence interval (CI) were calculated. AUC Differences between single biomarker and the panel were calculated using logistic regression model.¹⁸

Results

Patient characteristics and biomarker levels

Table 1 shows the demographics of the study population, a total of 382 patients and 200 healthy volunteers were included in this study. Among 132 HCC patients (mean age of 57.5 ± 9.2 years in early stage of HCC and 55.9 ± 9.1 years in late stage of HCC), all were originally diagnosed. The viral hepatitis controls (mean age of 41.3 ± 11.8 years) and healthy controls (mean age of 33.1 ± 8.5 years) were younger than those with other diseases (p < 0.005 and p < 0.000, respectively). A male predominance in all group were found except in other benign liver disease control group. A total of 14 (22.2%) in early stage of HCC group and 41 (59.4%) in late stage of HCC group were HBsAg (surface antigen of the HBV) positive. Besides, 80 (80%) viral hepatitis controls and 28 (56%) cirrhosis patients were induced by HBV infection. The TNM stages of enrolled HCC patients were 27 (20.5%) in stage I, 36 (27.3%) in stage II, 66 (50%) in stage III, and 3 (2.2%) in stage IV.

Table 1.

Characteristics of patients enrolled in this study.

Variables	HCC stage	HCC stage	Viral hepatitis	Liver cirrhosis	Metastatic hepatic carcinoma	Other benign liver diseases	Healthy
Variables	Early	Late	Viral hepatitis	Liver cirrhosis	Metastatic hepatic carcinoma	Other benign liver diseases	Healthy
Sample size	63	69	100	50	50	50	200
Age	57.5 ± 9.2	55.9 ± 9.1	41.3 ± 11.8	54.7 ± 10.3	57.9 ± 9.8	50.7 ± 11.6	33.1 ± 8.5 *
Gender
Male (%)	48 (76.2)**	48 (69.6)**	55 (55)	30 (60)	31 (62)	25 (50)	153 (76.5)
Female (%)	15 (23.8)	21 (30.4)	45 (45)	20 (40)	19 (38)	25 (50)	47 (23.5)
Etiology
HBV (%)	14 (22.2)	41 (59.4)	80 (80)	28 (56)
HCV (%)	1 (1.6)	6 (8.7)	17 (17)	7 (14)
HBV and HCV (%)	1 (1.6)	2 (2.9)	3 (3)
Alcohol (%)				8 (16)		13 (26)
Gastrointestinal tumor (%)					37 (74)
Gynecological tumor (%)					9 (18)
Lung tumor (%)					2 (4)
Drug (%)						29 (58)
Obesity (%)						2 (4)
AILD (%)					3 (6)
Others (%)	47 (74.6)	20 (29.0)		7 (14)	2 (4)	3 (6)
HCC stage I/II/III/IV	27 (20.5%)/36 (27.3%)/66 (50%)/3 (2.2%)
Abbott AFP level (ng/mL)	454.0 ± 752.3	990.7 ± 912.3	32.6 ± 78.0	15.7 ± 36.6	85 ± 395.1	84.5 ± 395.1	1.7 ± 1.1
Abbott PIVKA-II level (mAU/mL)	4855.4 ± 9957.5	9355.8 ± 12203.4	188.8 ± 1677.5	90.4 ± 343.4	477.2 ± 2350.4	539.4 ± 2364.4	16.7 ± 7.5
Fujirebio AFP level (ng/mL)	466.9 ± 755.3	1011.2 ± 910.3	38.2 ± 91.2	17.5 ± 40.0	86.8 ± 394.9	86.3 ± 394.8	2.5 ± 1.4
Fujirebio PIVKA-II level (mAU/mL)	9560.3 ± 21879.0	18325.0 ± 27664.8	171.1 ± 1498.9	83.2 ± 361.5	608.9 ± 3026.6	667.0 ± 3037.0	13.7 ± 5.1

HCC: hepatocellular carcinoma; HBV: hepatitis B virus; HCV: hepatitis C virus; AILD: angioimmunoblastic lymphadenopathy; AFP: alpha-fetoprotein; PIVKA-II: protein induced by vitamin K absence-II, SD: standard deviation.

Values are mean ± SD, unless otherwise indicated.

Compared to HCC and non-HCC groups, p < 0.001.

Compared to female, p < 0.05.

Serum levels of AFP and PIVKA-II are significantly elevated in HCC group especially in late stage of HCC patients compared to non-HCC and healthy controls. Both Abbott and Fujirebio assays show that geometric AFP average value for HCC is higher than non-HCC groups (p < 0.001). Geometric PIVKA-II average level for HCC is higher than non-HCC groups (p < 0.001).

Comparison of AUC, sensitivity, and specificity of the two biomarkers alone and in combination to distinguish HCC from non-HCC patients and healthy controls

As shown in Table 2, Abbott PIVKA-II (40 mAU/mL) has better sensitivity (80%) but decreased specificity (89%) compared to AFP (20 ng/mL). It also has the best overall sensitivity and specificity performances among all four markers.

Table 2.

Diagnostic performances of two biomarkers alone and in combination for HCC diagnosis with control groups.

Markers	Total subjects (n = 582)
	SN	SP	SN + SP	PPV	NPV	AUC	95% confidence interval
Abbott AFP	0.68	0.91	1.59	0.7	0.91	0.870	0.840	0.897
Abbott PIVKA-II	0.8	0.89	1.69	0.68	0.94	0.905	0.878	0.927
Fujirebio AFP	0.7	0.91	1.61	0.7	0.91	0.859	0.829	0.887
Fujirebio PIVKA-II	0.8	0.88	1.68	0.67	0.94	0.898	0.870	0.921
Abbott AFP + PIVKA-II	0.87	0.82	1.69	0.59	0.96	0.906*	0.880	0.929
Fujirebio AFP + PIVKA-II	0.88	0.81	1.69	0.58	0.96	0.883*	0.854	0.908

HCC: hepatocellular carcinoma; SN: sensitivity; SP: specificity; PPV: positive predictive value; NPV: negative predictive value; AUC: area under the curve; AFP: alpha-fetoprotein; PIVKA-II: protein induced by vitamin K absence.

Cutoff values: AFP ⩾ 20 ng/mL, PIVKA-II ⩾ 40 mAU/mL, and in combination: AFP ⩾ 20 ng/mL or PIVKA-II ⩾ AU/mL.

Control groups included non-HCC patients and healthy subjects.

Compared to AFP alone, p < 0.05.

Compared to AFP, AFP and PIVKA-II panel shows significantly a better AUC (0.906, 95% CI: 0.880–0.929) for the diagnosis of HCC with sensitivity of 87% and specificity of 82%, using the currently recommended clinical cutoffs for AFP (20 ng/mL) and PIVKA-II (40 mAU/mL). The AUC of Abbott AFP was 0.870 (95% CI: 0.840–0.897), sensitivity was 68%, and specificity was 91%. The AUC for Abbott PIVKA-II was 0.905 (95% CI: 0.878–0.927), sensitivity was 80%, and specificity was 89%. Fuji assays showed the same tendency as Abbott assays that two markers in combination had better performance in HCC diagnosis than AFP alone. No significant difference was found between Abbott and Fujirebio assays.

Comparison of AUC, sensitivity, and specificity of the two biomarkers alone and in combination to distinguish early stage of HCC from non-HCC patients

A total of 63 (47.7%) patients in early stage of HCC (TNM stage I or II) and 250 non-HCC patients were included. As shown in Table 3, single PIVKA-II (Abbott) has sensitivity of 71% with specificity of 80% indicating better sensitivity and slightly decreased specificity compared to AFP. In combination, Abbott PIVKA-II and AFP showed the better AUC of 0.809 (95% CI: 0.761–0.851) compared to AFP alone, the sensitivity for early HCC diagnosis was increased to 83% with specificity of 68%.

Table 3.

Diagnostic performances of two biomarkers alone and in combination for early-stage HCC diagnosis with control groups.

Markers	Total subjects (n = 313)
	SN	SP	SN + SP	PPV	NPV	AUC	95% confidence interval
Abbott AFP	0.59	0.84	1.43	0.49	0.89	0.770	0.720	0.816
Abbott PIVKA-II	0.71	0.80	1.52	0.48	0.92	0.820	0.773	0.861
Fujirebio AFP	0.60	0.84	1.44	0.49	0.89	0.761	0.709	0.807
Fujirebio PIVKA-II	0.71	0.79	1.51	0.46	0.92	0.798	0.749	0.841
Abbott AFP + PIVKA-II	0.83	0.68	1.51	0.39	0.94	0.809*	0.761	0.851
Fujirebio AFP + PIVKA-II	0.83	0.67	1.49	0.39	0.94	0.789*	0.739	0.833

Cutoff values: AFP ⩾ 20 ng/mL, PIVKA-II ⩾ 40 mAU/mL, and in combination: AFP ⩾ 20 ng/mL or PIVKA-II ⩾ 40 mAU/mL.

Control groups included non-HCC patients and healthy subjects.

Compared to AFP alone, p < 0.05.

Comparison of AUC, sensitivity, and specificity of the two biomarkers alone and in combination to distinguish HCC from non-HCC patients induced by HBV

We also evaluated the performance of AFP and PIVKA-II in HBsAg-positive patients including 55 HCC patients, 28 cirrhosis patients, and 80 hepatitis patients. As shown in Table 4, Abbott PIVKA-II showed better sensitivity (85%) and specificity (93%) compared to AFP (sensitivity of 73% and specificity of 73%). The AUC of Abbott PIVKA-II is 0.901 (95% CI: 0.845–0.942), which is significantly better than Abbott AFP alone (AUC: 0.788; 95% CI: 0.717–0.848; p < 0.05) and in combination (AUC: 0.851; 95% CI: 0.763–0.884; p < 0.05) as shown in Figure 1(a). The ROC of Fuji also showed the same tendency as Abbott assays that PIVKA-II alone showed the best AUC compared to AFP alone and in combination (Figure 1(b)).

Table 4.

Diagnostic performances of two biomarkers alone and in combination for HBV-related HCC diagnosis with hepatitis and cirrhosis.

Markers	Total subjects (HCC = 55, cirrhosis = 28, and viral hepatitis = 80)
	SN	SP	SN + SP	PPV	NPV	AUC	95% confidence interval
Abbott AFP	0.73	0.73	1.46	0.58	0.84	0.788	0.717	0.848
Abbott PIVKA-II	0.85	0.93	1.78	0.85	0.93	0.901*	0.845	0.942
FUjirebio AFP	0.75	0.72	1.47	0.58	0.85	0.786	0.715	0.847
Fujirebio PIVKA-II	0.85	0.90	1.75	0.81	0.92	0.893*	0.835	0.936
Abbott AFP + PIVKA-II	0.89	0.69	1.58	0.59	0.93	0.851*	0.763	0.884
Fujirebio AFP + PIVKA-II	0.91	0.67	1.58	0.58	0.94	0.849*	0.731	0.859

HBV: hepatitis B virus; HCC: hepatocellular carcinoma; SN: sensitivity; SP: specificity; PPV: positive predictive value; NPV: negative predictive value; AUC: area under the curve; AFP: alpha-fetoprotein; PIVKA-II: protein induced by vitamin K absence.

Cutoff values: AFP ⩾ 20 ng/mL, PIVKA-II ⩾ 40 mAU/mL, and in combination: AFP ⩾ 20 ng/mL or PIVKA-II ⩾ 40 mAU/mL.

Control groups included HBV-related HCC patients, HBV hepatitis patients, and cirrhosis patients.

Compared to AFP alone, p < 0.05.

Figure 1.

ROC curve of AFP, PIVKA-II, and in combination for the diagnosis of HCC with non-HCC patients infected by HBV. (a) ROC of Abbott assays. (b) ROC of Fujirebio assay performance.

Discussion

This control evaluation study demonstrated that panel of PIVKA-II and AFP has better diagnostic value for HCC compared to AFP, even in early stage. PIVKA-II showed better performance in HBV-related HCC patients than AFP.

HCC early detection with imaging diagnosis has been developed in recent years; tumor markers are still commonly used in HCC detection and follow-up visits. AFP has been widely used for HCC diagnosis for many years. However, about 30% of HCC patients have false negative results, especially in early stage.^19–22 Other benign liver diseases might also have elevated AFP including patients with cirrhosis or chronic viral hepatitis.^9,23 In our study, AFP significantly increased in HCC patients included in early stage. AFP has a sensitivity of 68% and specificity of 91% in diagnosis of HCC, and the sensitivity decreased to 59% in early stage. Our data are consistent with previous publications that showed that AFP has limitations in HCC detection.^24,25

It was reported that PIVKA-II has better sensitivity and specificity than AFP.^26–28 However, other researchers had different opinions.^29,30 The current data of all patients showed that AUC of PIVKA-II for HCC detection was 0.905, which is higher than that of AFP. However, the difference is not significant in this study. If focusing on patients with HBV infection, AUC of PIVKA-II was significantly higher than AFP. PIVKA-II also has better sensitivity and specificity compared to AFP in these patients. The data are consistent with previous publications which reported that PIVKA-II has better performance in patients with viral etiology including HBV or HCV.¹⁰ About 80% of all newly diagnosed HCC were developed from chronic HBV infection in China that was higher than western countries.^31,32 In our study, about 41.7% HCC patients had positive HBsAg. Etiology difference should be considered for the contrary PIVKA-II performance compared to AFP in China and in western countries.

In our study, the panel of AFP and PIVKA-II improves sensitivity to 87% in all stages of HCC patients. In HCC early stage, the sensitivity increased to 83%. In addition, the panel showed significantly increased AUC (0.906 in whole patients and 0.809 in HCC early-stage patients) compared to AFP. These results suggested that these two biomarkers in combination should be used with imaging to improve the diagnostic value in HCC patients.

Two platforms were used in our study to validate our results. No significant difference was found between Abbott and Fujirebio assays in HCC detection in all the HCC patients. However, in HCC early-stage detection, Abbott AFP showed better AUC (0.770) compared to Fujirebio AFP (0.761), Abbott PIVKA-II (AUC 0.820) performed better than Fujirebio PIVKA-II (AUC 0.798) in these patients. On combining these two biomarkers, Abbott assay performed better (AUC 0.809).

ROC curve was drawn to compare AFP, PIVKA-II, and in combination diagnosis value in HCC patients with positive HBsAg. The results revealed that PIVKA-II alone has the highest AUC (0.901) compared to AFP alone (0.788) and in combination (0.851). PIVKA-II was expected to play more important role in the setting of HBsAg-positive HCC diagnosis.

Limitation of our study is that the small size of HBsAg-positive HCC early-stage patients (10.6%) was enrolled. Most of HBsAg-positive HCC patients came at late stage. Further studies are needed to investigate the performance of PIVKA-II in large number of early-stage HCC patients with HBV infection, as well as potential future intent to use high-risk populations where the biomarker utilization may aid in early identification of HCC.

In conclusion, we demonstrated that PIVKA-II can be used as effective as AFP in HCC diagnosis, PIVKA-II combined with AFP performed better than AFP alone in HCC diagnosis, especially in early stage. PIVKA-II has better performance than AFP in HBsAg-positive HCC patients.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Abbott Diagnostics Division.

Open access

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

References

Globocan 2012: Estimated cancer incidence, mortality and prevalence worldwide in 2012, http://globocan.iarc.fr/Default.aspx

Wang

Chen

Zhang

. Incidence and mortality of liver cancer in mainland China: changes in first decade of 21st century. Hepatogastroenterology 2015; 62(137): 118–121.

Chen

Zheng

Zuo

. National cancer incidence and mortality in China, 2012. Chin J Cancer Res 2016; 28(1): 1–11.

Bode

Dong

Wang

. Cancer prevention and control: alarming challenges in China. Natl Sci Rev 2016; 3(1): 117–127.

National Health and Family Planning Commission of the PRC. Diagnosis management and treatment of hepatocellular carcinoma. Chin Clin Oncol 2011; 16(10): 929–946.

Yin

Wang

. Research advances on alpha-fetoprotein physiological function and clinical potential. Ai Zheng 2003; 22(1): 108–111.

Nunez

. Biological role of alpha-fetoprotein in the endocrinological field: data and hypotheses. Tumour Biol 1994; 15(2): 63–72.

Wong

Ahmed

Gish

. Elevated alpha-fetoprotein: differential diagnosis—hepatocellular carcinoma and other disorders. Clin Liver Dis 2015; 19(2): 309–323.

Bloomer

Waldmann

McIntire

. alpha-fetoprotein in noneoplastic hepatic disorders. JAMA 1975; 233(1): 38–41.

10.

Viggiani

Palombi

Gennarini

. Protein induced by vitamin K absence or antagonist-II (PIVKA-II) specifically increased in Italian hepatocellular carcinoma patients. Scand J Gastroenterol 2016; 51(10): 1257–1262.

11.

Ding

Tan

. Performance of protein induced by Vitamin K absence or antagonist-II (PIVKA-II) for hepatocellular carcinoma screening in Chinese population. Hepat Mon 2015; 15(7): e28806.

12.

Meguro

Mizuguchi

Nishidate

. Prognostic roles of preoperative α-fetoprotein and des-γ-carboxy prothrombin in hepatocellular carcinoma patients. World J Gastroenterol 2015; 21(16): 4933–4945.

13.

Poté

Cauchy

Albuquerque

. Performance of PIVKA-II for early hepatocellular carcinoma diagnosis and prediction of microvascular invasion. J Hepatol 2015; 62(4): 848–854.

14.

Kamel

Saad

Mahmoud

. Evaluation of serum PIVKA-II and MIF as diagnostic markers for HCV/HBV induced hepatocellular carcinoma. Microb Pathog 2014; 77: 31–35.

15.

Wang

Tan

Gao

. Elevated PIVKA-II is associated with early recurrence and poor prognosis in BCLC 0-A hepatocellular carcinomas. Asian Pac J Cancer Prev 2014; 15(16): 6673–6678.

16.

Liu

. PIVKA-II is an independent prognostic factor for overall survival of HCC patients and maybe associated with epithelial-mesenchymal transition. J Hepatol 2015; 63(4): 1040–1041.

17.

Edge

Compton

. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol 2010; 17(6): 1471–1474.

18.

DeLong

Clarke-Pearson

. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988; 44(3): 837–845.

19.

Kawano

Sasaki

Kai

. Short- and long-term outcomes after hepatic resection for hepatocellular carcinoma with concomitant esophageal varices in patients with cirrhosis. Ann Surg Oncol 2008; 15(6): 1670–1676.

20.

Matsuda

Asakawa

Amemiya

. Lens culinaris agglutinin-reactive fraction of AF is a useful prognostic biomarker for survival after repeat hepatic resection for HCC. J Gastroenterol Hepatol 2011; 26(4): 731–738.

21.

Sherman

Peltekian

Lee

. Screening for hepatocellular carcinoma in chronic carriers of hepatitis B virus: incidence and prevalence of hepatocellular carcinoma in a North American urban population. Hepatology 1995; 22(2): 432–438.

22.

Cui

Zhang

. Diagnostic value of protein induced by vitamin K absence (PIVKAII) and hepatoma-specific band of serum gamma-glutamyl transferase (GGTII) as hepatocellular carcinoma markers complementary to alpha-fetoprotein. Br J Cancer 2003; 88(12): 1878–1882.

23.

Johnson

. The role of serum alpha-fetoprotein estimation in the diagnosis and management of hepatocellular carcinoma. Clin Liver Dis 2001; 5(1): 145–159.

24.

Choi

Jung

Kim

. Diagnostic value of AFP-L3 and PIVKA-II in hepatocellular carcinoma according to total-AFP. World J Gastroenterol 2013; 19(3): 339–346.

25.

Song

Feng

Inagaki

. Clinical utility of simultaneous measurement of alpha-fetoprotein and des-γ-carboxy prothrombin for diagnosis of patients with hepatocellular carcinoma in China: a multi-center case-controlled study of 1,153 subjects. Biosci Trends 2014; 8(5): 266–273.

26.

Zakhary

Khodeer

Shafik

. Impact of PIVKA-II in diagnosis of hepatocellular carcinoma. J Adv Res 2013; 4(6): 539–546.

27.

Gotoh

Nakatani

Masuda

. Prediction of invasive activities in hepatocellular carcinomas with special reference to alpha-fetoprotein and des-gamma-carboxyprothrombin. Jpn J Clin Oncol 2003; 33(10): 522–526.

28.

El-Assaly

El Ashry

Mostafa

. Serum chromogranin-A and serum PIVKA-II as useful complementary and diagnostic markers for HCC. Res J Med Med Sci 2008; 4(2): 391–301.

29.

Grazi

Mazziotti

Legnani

. The role of tumor markers in the diagnosis of hepatocellular carcinoma, with special reference to the des-gamma-carboxy prothrombin. Liver Transpl Surg 1995; 1(4): 249–255.

30.

Marrero

Feng

Wang

. Alpha-fetoprotein, des-gamma carboxyprothrombin, and lectin-bound alpha-fetoprotein in early hepatocellular carcinoma. Gastroenterology 2009; 137(1): 110–118.

31.

Torre

Bray

Siegel

. Global cancer statistics, 2012. CA Cancer J Clin 2015; 65(2): 87–108.

32.

El-Serag

. Epidemiology of viral hepatitis and hepatocellular carcinoma. Gastroenterology 2012; 142(6): 1264–1273.

Diagnostic performance of tumor markers AFP and PIVKA-II in Chinese hepatocellular carcinoma patients

Abstract

Keywords

Introduction

Materials and methods

Patients

Measurement of PIVKA-II and AFP

Statistical analysis

Results

Patient characteristics and biomarker levels

Comparison of AUC, sensitivity, and specificity of the two biomarkers alone and in combination to distinguish HCC from non-HCC patients and healthy controls

Comparison of AUC, sensitivity, and specificity of the two biomarkers alone and in combination to distinguish early stage of HCC from non-HCC patients

Comparison of AUC, sensitivity, and specificity of the two biomarkers alone and in combination to distinguish HCC from non-HCC patients induced by HBV

Discussion

Footnotes

Declaration of conflicting interests

Funding

Open access

References