JCB J Circ Biomark 2023; 12: 12-16ISSN 1849-4544 | DOI: 10.33393/jcb.2023.2453ORIGINAL RESEARCH ARTICLE Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb © 2023 The Authors. This article is published by AboutScience and licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Commercial use is not permitted and is subject to Publisher’s permissions. Full information is available at www.aboutscience.eu infection, or lesions identified on a surveillance ultrasound in patients with cirrhosis, chronic HBV infection, or prior HCC (2). The main two markers for HCC are alpha-fetoprotein (AFP) and new biomarker: protein induced by vitamin K absence- II or antagonist (PIVKA-II). These markers play an important role in diagnosis, differential diagnosis, and prognosis. A nomogram of both AFP and PIVKA-II can be used to differen- tiate HCC and intrahepatic cholangiocarcinoma with an area under the receiver operating characteristic (ROC) curve of 95.1% (3). Both biomarkers can be used as a prognostic fac- tor after several treatments such as radiofrequency, surgical resection, embolization, or radiotherapy (4-12). PIVKA-II level lower than 25 mAU/mL or equal after radiotherapy had long progression-free survival (p = 0.004) (4). Additionally, both biomarkers can indicate tumor size, tumor differentiation, vascular invasion, and those treated with hepatitis B/C anti- viral agents (13-16). As HCC is a lethal cancer with 5-year survival rate of under 15%, abdominal ultrasonography is used for HCC sur- veillance (17,18). However, its sensitivity was low at 63% (19). Biomarkers were studied and used as an alternative PIVKA-II or AFP has better diagnostic properties for hepatocellular carcinoma diagnosis in high-risk patients Tanita Suttichaimongkol1, Manoon Mitpracha2, Kawin Tangvoraphonkchai1, Phuangphaka Sadee1, Kittisak Sawanyawisuth1, Wattana Sukeepaisarnjaroen1 1Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen - Thailand 2Division of Gastroenterology, Department of Medicine, Khon Kaen Regional Hospital, Khon Kaen - Thailand ABSTRACT Background: Hepatocellular carcinoma (HCC) is a lethal cancer. Two biomarkers were used for HCC diagnosis including alpha-fetoprotein (AFP) and protein induced by vitamin K absence-II or antagonist (PIVKA-II). However, data on biomarkers and HCC diagnosis are not consistent. This study aimed to evaluate if PIVKA-II, AFP, or a com- bination of both biomarkers had the best diagnostic properties for HCC. Methods: This was a prospective study and enrolled patients 18 years or over with a high risk for HCC. AFP and PIVKA-II levels were calculated for HCC diagnosis. Diagnostic properties of both biomarkers were reported with sensitivity, specificity, and a receiver operating characteristic (ROC) curve. Results: There were 260 patients with high risk for HCC in this cohort. Of those, 219 patients were diagnosed with HCC: confirmed by biopsy in 7 patients (2.69%) and by imaging in the others. Median values of AFP and PIVKA-II were 56 ng/mL and 348 mAU/mL, respectively. PIVKA-II level of 40 mAU/mL had sensitivity of 80.80%, while AFP of 10 ng/mL had sensitivity of 75.80%. A combination of PIVKA-II at 100 mAU/mL or over and AFP of 11 ng/mL gave sensitivity of 60.30%. The ROC curve of PIVKA-II plus AFP was significantly higher than the AFP alone (0.855 vs. 0.796; p = 0.027), but not significantly different from the PIVKA-II alone (0.855 vs. 0.832; p = 0.130). Conclusion: PIVKA-II may have more diagnostic yield for HCC compared with AFP. It can be used alone without a combination with AFP. Keywords: Hepatitis B virus, Hepatitis C virus, Sensitivity, Specificity Received: July 8, 2022 Accepted: February 1, 2023 Published online: February 17, 2023 Corresponding author: Kittisak Sawanyawisuth Department of Medicine, Faculty of Medicine Khon Kaen University Khon Kaen, 40002 - Thailand kittisak@kku.ac.th Introduction Hepatocellular carcinoma (HCC) is a common cancer. It is the sixth most common cancer and the second highest in cancer-related death globally. In 2015, there were 854,000 new cases and 810,000 deaths in the world (1). There were three common causes of HCC: hepatitis B virus (HBV), alco- hol, and hepatitis C virus (HCV). These causes related to HCC deaths in 33%, 30%, and 21%, respectively (1). High-risk patients for HCC were patients with cirrhosis, chronic HBV https://doi.org/10.33393/jcb.2023.2453 https://creativecommons.org/licenses/by-nc/4.0/legalcode mailto:kittisak@kku.ac.th Suttichaimongkol et al J Circ Biomark 2023; 12: 13 © 2023 The Authors. Published by AboutScience - www.aboutscience.eu diagnostic method particularly for HCC including AFP and PIVKA-II (20-22). The advantage of AFP is widely available, while PIVKA-II is highly specific to HCC. Data on biomark- ers and HCC diagnosis are not consistent. A report from the USA found that AFP was more sensitive than PIVKA-II (70% vs. 66%) in patients with HCC compared with patients with cirrhosis (23). On the other hand, a study from Nigeria found that PIVKA-II was more sensitive than AFP (96.8% vs. 62.9%) in patients with HCC vs. control with benign liver disease (24). A study from Korea recommends to use PIVKA-II combined with AFP to diagnose HCC in patients with HBV infection (25). These results showed that data on biomarkers and HCC diagnosis are not consistent and var- ied among countries, in which more data on this issue are required. This study aimed to evaluate if PIVKA-II, AFP, or a combination of both biomarkers had the best diagnostic properties for HCC. Materials and methods This was a prospective study conducted at University Hospital, Khon Kaen University, Thailand. Data were col- lected from the HCC project. The inclusion criteria were patients 18 years or over with a high risk for HCC. The high risk for HCC was defined by the American Association for the Study of Liver Diseases (AASLD) guidelines for HCC manage- ment (17): cirrhosis or presence of liver nodule(s) of 1 cm or over in size. Those with pregnancy, obstructive jaundice, vitamin K, or warfarin administration and presence of extra- hepatic malignancy were excluded. The study protocol was approved by the ethics committee in human research, Khon Kaen University, Thailand (HE621134). This study was a part of HCC project of Khon Kaen University, Thailand. Eligible patients provided a written informed consent prior to study participation. Data were collected as follows: baseline characteristics, laboratory results, and radiographic findings. Baseline characteristics included age, sex, etiology of cirrhosis, comorbid diseases, and the Child-Pugh score for cirrhosis. Laboratory tests in the study were platelet count, serum creatinine, prothrombin time, liver function test, AFP, and PIVKA-II. All samples were tested for AFP and PIVKA-II by using a test kit (µTASWako i30; FUJIFILM Wako Pure Chemical Corporation). Radiographic findings were numbers of liver mass, largest mass size (cm), and portal vein invasion. HCC was diagnosed by either confirmation by pathological find- ings or radiographic findings of arterial hypervascularity followed by venous and/or delayed phase or washout of con- trast (17). Statistical analyses Descriptive statistics were used to calculate mean (1st- 3rd interquartile ranges) or number (percentage) of the study population. AFP and PIVKA-II levels were calculated for HCC diagnosis by logistic regression analysis. Results were shown as various cutoff points with their diagnostic properties including sensitivity, specificity, positive likeli- hood ratio, negative likelihood ratio, a ROC curve, and an area under the ROC curve with 95% confidence interval (CI). All statistical analyses were performed using STATA software version 10.1. Results There were 260 patients with a high risk for HCC in this cohort. Of those, 219 patients were diagnosed with HCC: confirmed by biopsy in 7 patients (2.69%) and by imaging in the others. The other 41 patients had a diagnosis of dys- plastic nodule (25 patients; 60.98%), regenerative nodule (8 patients; 19.51%), hemangioma (5 patients; 12.20%), liver cyst (1 patient; 2.44%), fibronodular hyperplasia (1 patient; 2.44%), and hepatic adenoma (1 patient; 2.44%). Baseline characteristics and laboratory results are shown in Tables I and II. The median age was 58 years with male predominance (81.15%). The most common cause of HCC was HCV (43.85%) with a proportion of cirrhosis of 98.46%: mostly Child-Pugh score class A (81.15%). The median largest size of liver mass was 3.5 cm. The median values of AFP and PIVKA-II were 56 ng/mL and 348 mAU/mL, respectively. The PIVKA-II level of 40 mAU/mL had sensitivity of 80.80% with 75.60% specificity, while AFP of 10 ng/mL had sensi- tivity of 75.80% with 65.90% specificity (Tabs. III and IV). A combination of PIVKA-II at 100 mAU/mL or over and AFP of 11 ng/mL gave sensitivity of 60.30% with 92.70% specificity. The ROC curve of PIVKA-II plus AFP was significantly higher than the AFP alone (0.855 vs. 0.796; p value = 0.027), but not significantly different from PIVKA-II alone (0.855 vs. 0.832; p value = 0.130), as shown in Figure 1. TABLE I - Baseline characters of patients with a high risk for hepa- tocellular carcinoma (n = 260) Factors Median (1st-3rd quartile) or number (percentage) Age, years 58 (54-63) Male sex, n (%) 211 (81.15) Etiology HBV 98 (37.69) HCV 114 (43.85) HBV plus HCV 6 (2.31) NAFLD 14 (5.38) ALD 27 (10.38) AIH 1 (0.38) Comorbid diseases None 193 (74.23) Diabetes 38 (14.62) Hypertension 12 (4.62) Cirrhosis 256 (98.46) Child-Pugh score A 211 (81.15) Child-Pugh score B 36 (13.85) Child-Pugh score C 9 (3.46) AIH = autoimmune hepatitis; ALD = alcoholic liver disease; HBV = hepatitis B virus; HCV = hepatitis C virus; NAFLD = nonalcoholic fatty liver disease. PIVKA-II and AFP in HCC14 © 2023 The Authors. Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb TABLE II - Laboratory results of patients with a high risk for hepato- cellular carcinoma (n = 260) Factors Median (1st-3rd quartile) or number (percentage) Platelet ´103/mm3 145 (102-220) Creatinine (mg/dL) 0.94 (0.80-1.15) Prothrombin time (sec) 12.3 (11.5-13.4) Albumin (g/dL) 3.9 (3.4-4.4) Bilirubin (mg/dL) 1.0 (0.6-1.6) Alanine aminotransferase (U/L) 51 (29-86) Aspartate transaminase (U/L) 74 (40-133) Alkaline phosphatase (U/L) 135 (88-196) Alpha-fetoprotein (ng/mL) 59 (6-1,598) PIVKA-II (mA/mL) 348 (31-10,442) Radiographic findings Number of liver nodules, n (%) 1 156 (90.00) 2 46 (17.69) 3 12 (4.62) ≥4 46 (17.69) Largest size (cm) 3.5 (1.8-7.5) Portal vein invasion, n (%) No invasion 181 (69.62) Main portal vein invasion 56 (21.54) Non-main portal vein invasion 23 (8.85) PIVKA-II = protein induced by vitamin K absence-II or antagonist. TABLE III - Performance characteristics of protein induced by PIVKA-II (mAU/mL) for diagnosing HCC in patients with a high risk for HCC Cutoff Sensitivity Specificity LR+ LR- ≥40 80.80 (75.00-85.80) 75.60 (59.70-87.60) 3.31 (1.93-5.70) 0.25 (0.18-0.35) ≥60 78.50 (72.50-83.80) 80.50 (65.10-91.20) 4.03 (2.15-7.52) 0.27 (0.20-0.36) ≥80 75.30 (69.10-80.90) 82.90 (67.90-92.80) 4.41 (2.24-8.70) 0.30 (0.23-0.39) ≥100 72.10 (65.70-78.00) 87.80 (73.80-95.90) 5.92 (2.59-13.50) 0.32 (0.25-0.40) ≥120 69.40 (62.80-75.40) 87.80 (73.80-95.90) 5.69 (2.49-13.0) 0.35 (0.28-0.44) HCC = hepatocellular carcinoma; LR+ = positive likelihood ratio; LR- = negative likelihood ratio; PIVKA-II = vitamin K absence-II or antagonist. TABLE IV - Performance characteristics of AFP (ng/mL) for diagnos- ing HCC in patients with a high risk for HCC Cutoff Sensitivity Specificity LR+ LR- ≥10 75.80 (69.60-81.30) 65.90 (49.40-79.90) 2.22 (1.44-3.42) 0.37 (0.27-0.51) ≥12 73.10 (66.70-78.80) 70.70 (54.50-83.90) 2.50 (1.54-4.04) 0.38 (0.28-0.51) ≥14 69.40 (62.80-75.40) 73.20 (57.10-85.80) 2.59 (1.55-4.32) 0.42 (0.32-0.55) ≥20 65.30 (58.60-71.60) 78.00 (62.40-89.40) 2.97 (1.66-5.34) 0.45 (0.35-0.57) ≥200 44.70 (38.00-51.60) 90.20 (76.90-97.30) 4.59 (1.79-11.80) 0.61 (0.52-0.72) AFP = alpha-fetoprotein; HCC = hepatocellular carcinoma; LR+ = positive likelihood ratio; LR- = negative likelihood ratio. Fig. 1 - Receiver operating characteristic (ROC) curves and their area under the ROC curves (95% confidence interval) of protein induced by vitamin K absence-II or antagonist (PIVKA-II), alpha-fetoprotein (AFP), and the combination of both biomarkers to predict hepatocel- lular carcinoma (HCC) in patients with a high risk for HCC. Discussion This cohort found that PIVKA-II was more sensitive for HCC diagnosis than AFP and can be used alone without a combination with AFP. The results of this study were comparable with two pre- vious studies to detect HCC in cirrhosis patients with liver nodules of 1 cm or over (26-28). Note that this study had larger study population than the other two studies (260 vs. 128 vs. 90). With larger sample size in this study, PIVKA-II was more sensitive to detect HCC than AFP (80.80% vs. 75.80%) by the cutoff point of 40 mAU/L and 10 ng/mL, respectively. Compared with the study from France, the sensitivity of PIVKA-II was comparable (80.80% vs. 77%) as well as the cut- off point (40 vs. 42 mAU/L). However, this study had different results compared with the US study (23), in which AFP had Suttichaimongkol et al J Circ Biomark 2023; 12: 15 © 2023 The Authors. Published by AboutScience - www.aboutscience.eu better sensitivity than PIVKA-II in HCC with a sample size of 208 patients. AFP at 10.9 ng/mL had higher sensitivity at 66% compared with 56% sensitivity of PIVKA-II at 221.5 mAU/mL. These differences may be due to different control. In the pre- vious study, patients with cirrhosis without liver mass served as controls, while non-HCC patients were cirrhotic patients with liver mass in this study. Another possible explanation is the property of PIVKA-II, which is an indicator of microvascu- lar invasion (26). High PIVKA-II of over 90 mAU/mL had higher risk of microvascular invasion by 3.5 times (95% CI 1.08, 11.8; p value 0.043). In this study, 30.38% of patients had portal vein invasion, which may be an indicator of microvascular invasion (Tab. II). In this study, we found that PIVKA-II can be used for HCC diagnosis without a need to combine with AFP. These results were different from the study from Korea (25). The areas under the ROC curve of these combinations were significantly different from PIVKA-II alone (0.912 vs. 0.870) or AFP alone (0.902 vs. 0.812) for those with liver cirrhosis in the previous study. Once again, these differences may be due to different study population. The previous study enrolled patients with HBV infection and categorized into three groups: non-cirrhotic HBV infection, cirrhosis without HCC, and HCC group (no data whether cirrhosis or not). Additionally, the cirrhosis group in the previous study may or may not have liver nodules like in this study. Note that HBV infection was accounted in only 37.69% in this study. Another explanation is different cutoff points for PIVKA-II and AFP. The cutoff points for these two markers in the previous study were 40 mAU/mL and 25 ng/ mL, while the cutoff points in this study were 100 mAU/mL and 11 ng/mL. Note that a combination of these two bio- markers had lower sensitivity but higher specificity. Even though both AFP and PIVKA-II are useful diagnos- tic markers for HCC, a previous report found that they may not be a good marker for small HCC nodules less than 2 cm as they have sensitivity of approximately 50% (29). However, they may be used for HCC detection particularly in hepatitis virus-related HCC (22,30). A study from China found similar findings as this study but different cutoff for both AFP and PIVKA-II (31). A combination of AFP and PIVKA-II model is better than AFP alone but comparable with PIVKA-II alone. Therefore, PIVKA-II may be used alone without a combina- tion with AFP to diagnose HCC. Compared with benign liver disease, this study had PIVKA-II and AFP cutoff points at 40 mAU/mL and 10 ng/mL while the Chinese study had cut- off points of 43.47 mAU/mL and 21.47 ng/mL for PIVKA-II and AFP. The different cutoff points may be from different study population and sample size. This study had larger sample size and most patients (80%) had HBV or HCV as a cause, while the Chinese study did not show causes of HCC. Another study conducted with liver cirrhosis as a control group also found that similar findings of PIVKA-II alone were comparable with a combination of PIVKA-II and AFP for HCC diagnosis (32). There are some limitations in this study. First, etiologies of cirrhosis in this study are varied; HCV was the most com- mon cause (43.85%) followed by HBV infection (37.69%). The results of this study may not be applicable for other coun- tries with different causes of cirrhosis or HCC. Second, we used different cutoff points for a combination of PIVKA-II and AFP as discussed earlier. Third, some associated factors with hepatitis virus or fatty liver such as sleep apnea were not studied (33-38). No predictor for HCC was studied as well as systematic review (39-42). Finally, note that control group in this study were those with high risk for HCC: presence of liver mass of 1 cm or more in size. As this study enrolled high- risk patients for HCC with various causes, various Child-Pugh score classification, various liver nodule sizes, these may lead to possible selection biases. Further studies are necessary before considering these biomarkers even for a general eval- uation of the HCC diagnosis. In conclusion, PIVKA-II may have more diagnostic yield for HCC compared with AFP. It can be used alone without a com- bination with AFP. Acknowledgments The authors would like to thank the Division of Research and Graduate Studies, and the Fundamental Fund of Khon Kaen University, Khon Kaen, Thailand. Disclosures Conflict of interest: The authors declare no conflict of interest. Financial support: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors contribution: All authors contributed equally to this manu- script. References 1. Akinyemiju T, Abera S, Ahmed M, et al; Global Burden of Disease Liver Cancer Collaboration. The burden of primary liver cancer and underlying etiologies from 1990 to 2015 at the global, regional, and national level: results from the Global Burden of Disease Study 2015. JAMA Oncol. 2017;3(12):1683- 1691. CrossRef PubMed 2. Lee S, Kim Y-Y, Shin J, et al. CT and MRI liver imaging reporting and data system version 2018 for hepatocellular carcinoma: a systematic review with meta-analysis. J Am Coll Radiol. 2020;17(10):1199-1206. CrossRef PubMed 3. Si Y-Q, Wang X-Q, Pan C-C, Wang Y, Lu ZM. An efficient nomo- gram for discriminating intrahepatic cholangiocarcinoma from hepatocellular carcinoma: a retrospective study. Front Oncol. 2022;12:833999. CrossRef PubMed 4. Cho IJ, Jeong J-U, Nam T-K, et al. PIVKA-II as a surrogate marker for prognosis in patients with localized hepatocellular carci- noma receiving stereotactic body radiotherapy. Radiat Oncol J. 2022;40(1):20-28. CrossRef PubMed 5. Wang S-Y, Su T-H, Chen B-B, et al. Prothrombin induced by vita- min K absence or antagonist-II (PIVKA-II) predicts complete responses of transarterial chemoembolization for hepatocel- lular carcinoma. J Formos Med Assoc. 2022;121(6):1579-1587. CrossRef 6. Yanagaki M, Shirai Y, Hamura R, et al. Novel combined fibrosis- based index predicts the long-term outcomes of hepato- cellular carcinoma after hepatic resection. Int J Clin Oncol. 2022;27(4):717-728. CrossRef PubMed 7. Yang Y, Li G, Lu Z, Liu Y, Kong J, Liu J. Progression of prothrombin induced by vitamin K absence-II in hepatocellular carcinoma. Front Oncol. 2021;11:726213. CrossRef PubMed 8. Sagar VM, Herring K, Curbishley S, et al. The potential of PIVKA-II as a treatment response biomarker in hepatocel- lular carcinoma: a prospective United Kingdom cohort study. Oncotarget. 2021;12(24):2338-2350. CrossRef PubMed https://doi.org/10.1001/jamaoncol.2017.3055 https://www.ncbi.nlm.nih.gov/pubmed/28983565 https://doi.org/10.1016/j.jacr.2020.06.005 https://www.ncbi.nlm.nih.gov/pubmed/32640250 https://doi.org/10.3389/fonc.2022.833999 https://www.ncbi.nlm.nih.gov/pubmed/35480111 https://doi.org/10.3857/roj.2021.00934 https://www.ncbi.nlm.nih.gov/pubmed/35368197 http://dx.doi.org/10.1016/j.jfma.2022.01.005 https://doi.org/10.1007/s10147-021-02111-7 https://www.ncbi.nlm.nih.gov/pubmed/35015195 https://doi.org/10.3389/fonc.2021.726213 https://www.ncbi.nlm.nih.gov/pubmed/34900676https://www.ncbi.nlm.nih.gov/pubmed/34900676 https://doi.org/10.18632/oncotarget.28136 https://www.ncbi.nlm.nih.gov/pubmed/34853657 PIVKA-II and AFP in HCC16 © 2023 The Authors. Journal of Circulating Biomarkers - ISSN 1849-4544 - www.aboutscience.eu/jcb 9. Hayashi M, Yamada S, Takano N, et al. Different characteris- tics of serum alfa fetoprotein and serum des-gamma-carboxy prothrombin in resected hepatocellular carcinoma. In Vivo. 2021;35(3):1749-1760. CrossRef PubMed 10. Mukund A, Vats P, Jindal A, Patidar Y, Sarin SK. Early hepatocel- lular carcinoma treated by radiofrequency ablation-mid- and long-term outcomes. J Clin Exp Hepatol. 2020;10(6):563-573. CrossRef PubMed 11. Lee Q, Yu X, Yu W. The value of PIVKA-II versus AFP for the diag- nosis and detection of postoperative changes in hepatocellular carcinoma. J Interv Med. 2021;4(2):77-81. CrossRef PubMed 12. Kysela P, Kala Z, Zatloukal M, Raudenská M, Brančíková D. Hepatocellular carcinoma – prognostic criteria of individu- alized treatment. Klin Onkol. 2022;35(2):100-113. CrossRef PubMed 13. Si Y-Q, Wang X-Q, Fan G, et al. Value of AFP and PIVKA-II in diagnosis of HBV-related hepatocellular carcinoma and pre- diction of vascular invasion and tumor differentiation. Infect Agent Cancer. 2020;15(1):70. CrossRef PubMed 14. Basile U, Miele L, Napodano C, et al. The diagnostic performance of PIVKA-II in metabolic and viral hepatocellular carcinoma: a pilot study. Eur Rev Med Pharmacol Sci. 2020;24(24):12675- 12685. PubMed 15. Degasperi E, Perbellini R, D’Ambrosio R, et al. Prothrombin induced by vitamin K absence or antagonist-II and alpha foe- toprotein to predict development of hepatocellular carcinoma in Caucasian patients with hepatitis C-related cirrhosis treated with direct-acting antiviral agents. Aliment Pharmacol Ther. 2022;55(3):350-359. CrossRef PubMed 16. Su T-H, Peng C-Y, Chang S-H, et al. Serum PIVKA-II and alpha- fetoprotein at virological remission predicts hepatocellular car- cinoma in chronic hepatitis B related cirrhosis. J Formos Med Assoc. 2022;121(3):703-711. CrossRef PubMed 17. Bruix J, Sherman M; American Association for the Study of Liver Diseases. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53(3):1020-1022. CrossRef PubMed 18. de Lope CR, Tremosini S, Forner A, Reig M, Bruix J. Management of HCC. J Hepatol. 2012;56(suppl 1):S75-S87. CrossRef PubMed 19. Singal A, Volk ML, Waljee A, et al. Meta-analysis: surveillance with ultrasound for early-stage hepatocellular carcinoma in patients with cirrhosis. Aliment Pharmacol Ther. 2009;30(1): 37-47. CrossRef PubMed 20. Chi X, Jiang L, Yuan Y, et al. A comparison of clinical patho- logic characteristics between alpha-fetoprotein negative and positive hepatocellular carcinoma patients from Eastern and Southern China. BMC Gastroenterol. 2022;22(1):202. CrossRef PubMed 21. Ji J, Liu L, Jiang F, et al. The clinical application of PIVKA-II in hepatocellular carcinoma and chronic liver diseases: a multi- center study in China. J Clin Lab Anal. 2021;35(11):e24013. CrossRef PubMed 22. Sun T, Li R, Qiu Y, Shen S, Wang W. New thresholds for AFP and des-γ-carboxy prothrombin in chronic liver disease depending on the use of nucleoside analogs and an integrated nomogram. Int J Gen Med. 2021;14:6149-6165. CrossRef PubMed 23. Marrero JA, Kulik LM, Sirlin CB, et al. Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases. Hepatology. 2018;68(2):723-750. CrossRef PubMed 24. Ette AI, Ndububa DA, Adekanle O, Ekrikpo U. Utility of serum des-gamma-carboxyprothrombin in the diagnosis of hepato- cellular carcinoma among Nigerians, a case-control study. BMC Gastroenterol. 2015;15(1):113. CrossRef PubMed 25. Seo SI, Kim HS, Kim WJ, et al. Diagnostic value of PIVKA-II and alpha-fetoprotein in hepatitis B virus-associated hepatocellu- lar carcinoma. World J Gastroenterol. 2015;21(13):3928-3935. CrossRef PubMed 26. Poté N, Cauchy F, Albuquerque M, et al. Performance of PIVKA-II for early hepatocellular carcinoma diagnosis and pre- diction of microvascular invasion. J Hepatol. 2015;62(4):848- 854. CrossRef PubMed 27. Saitta C, Raffa G, Alibrandi A, et al. PIVKA-II is a useful tool for diagnostic characterization of ultrasound-detected liver nod- ules in cirrhotic patients. Medicine (Baltimore). 2017;96(26): e7266. CrossRef PubMed 28. Durazo FA, Blatt LM, Corey WG, et al. Des-gamma-carboxyprot- hrombin, alpha-fetoprotein and AFP-L3 in patients with chronic hepatitis, cirrhosis and hepatocellular carcinoma. J Gastroen- terol Hepatol. 2008;23(10):1541-1548. CrossRef PubMed 29. Tarao K, Nozaki A, Komatsu H, et al. Real impact of tumor marker AFP and PIVKA-II in detecting very small hepatocellular carcinoma (≤2 cm, Barcelona stage 0) – assessment with large number of cases. World J Hepatol. 2020;12(11):1046-1054. CrossRef PubMed 30. Chen Y, Yang Y, Li S, et al. Changes and clinical significance of PIVKA-II in hepatitis E patients. Front Public Health. 2022;9:784718. CrossRef PubMed 31. Feng H, Li B, Li Z, Wei Q, Ren L. PIVKA-II serves as a potential bio- marker that complements AFP for the diagnosis of hepatocel- lular carcinoma. BMC Cancer. 2021;21(1):401. CrossRef PubMed 32. Xu F, Zhang L, He W, Song D, Ji X, Shao J. The diagnostic value of serum PIVKA-II alone or in combination with AFP in Chinese hepatocellular carcinoma patients. Dis Markers. 2021;2021:8868370. CrossRef PubMed 33. Khamsai S, Chootrakool A, Limpawattana P, et al. Hypertensive crisis in patients with obstructive sleep apnea-induced hyper- tension. BMC Cardiovasc Disord. 2021;21(1):310. CrossRef PubMed 34. Jeerasuwannakul B, Sawunyavisuth B, Khamsai S, et al. Prevalence and risk factors of proteinuria in patients with type 2 diabetes mellitus. Asia Pac J Sci Technol. 2021 [cited 2022 Jan 19];26(4):APST-26-04-02. Available from: Online 35. Soontornrungsun B, Khamsai S, Sawunyavisuth B, et al. Obstructive sleep apnea in patients with diabetes less than 40 years of age. Diabetes Metab Syndr. 2020;14(6):1859-1863. CrossRef PubMed 36. Sawunyavisuth B. What are predictors for a continuous positive airway pressure machine purchasing in obstructive sleep apnea patients? Asia Pac J Sci Technol. 2018:23(3):APST- 23-03-10. CrossRef 37. Manasirisuk P, Chainirun N, Tiamkao S, et al. Efficacy of generic atorvastatin in a real-world setting. Clin Pharmacol. 2021;13:45-51. CrossRef PubMed 38. Tomar A, Bhardwaj A, Choudhary A, Bhattacharyya D. Association of obstructive sleep apnea with nocturnal hypox- emia in metabolic-associated fatty liver disease patients: a cross-sectional analysis of record-based data. J Family Med Prim Care. 2021;10(8):3105-3110. CrossRef PubMed 39. Tongdee S, Sawunyavisuth B, Sukeepaisarnjaroen W, Boonsawat W, Khamsai S, Sawanyawisuth K. Clinical factors predictive of appropriate treatment in COPD: a community hospital setting. Drug Target Insights. 2021;15:21-25. CrossRef PubMed 40. Charoentanyarak S, Sawunyavisuth B, Deepai S, Sawanyawisuth K. A point-of-care serum lactate level and mortality in adult sepsis patients: a community hospital setting. J Prim Care Community Health. 2021;12:21501327211000233. CrossRef PubMed 41. Boonwang T, Namwaing P, Srisaphonphusitti L, et al. Esports may improve cognitive skills in soccer players: a systematic review. Asia Pac J Sci Technol. 2022;27:APST-27-03-03. 42. Namwaing P, Ngamjarus C, Sakaew W, et al. Chest physical therapy and outcomes in primary spontaneous pneumotho- rax: a systematic review. J Med Assoc Thai. 2021;104(S4): S165-168. CrossRef https://doi.org/10.21873/invivo.12434 https://www.ncbi.nlm.nih.gov/pubmed/33910859 https://doi.org/10.1016/j.jceh.2020.04.016 https://www.ncbi.nlm.nih.gov/pubmed/33311893 https://doi.org/10.1016/j.jimed.2021.02.004 https://www.ncbi.nlm.nih.gov/pubmed/34805952 https://doi.org/10.48095/ccko2022100 https://www.ncbi.nlm.nih.gov/pubmed/35459334 https://doi.org/10.1186/s13027-020-00337-0 https://www.ncbi.nlm.nih.gov/pubmed/33292429 https://www.ncbi.nlm.nih.gov/pubmed/33378014 https://doi.org/10.1111/apt.16685 https://www.ncbi.nlm.nih.gov/pubmed/34738664 https://doi.org/10.1016/j.jfma.2021.08.003 https://www.ncbi.nlm.nih.gov/pubmed/34452785 https://doi.org/10.1002/hep.24199 https://www.ncbi.nlm.nih.gov/pubmed/21374666 https://doi.org/10.1016/S0168-8278(12)60009-9 https://www.ncbi.nlm.nih.gov/pubmed/22300468 https://doi.org/10.1111/j.1365-2036.2009.04014.x https://www.ncbi.nlm.nih.gov/pubmed/19392863 https://doi.org/10.1186/s12876-022-02279-w https://www.ncbi.nlm.nih.gov/pubmed/35461226 https://doi.org/10.1002/jcla.24013 https://www.ncbi.nlm.nih.gov/pubmed/34590755 https://doi.org/10.2147/IJGM.S335400 https://www.ncbi.nlm.nih.gov/pubmed/34611429 https://doi.org/10.1002/hep.29913 https://www.ncbi.nlm.nih.gov/pubmed/29624699 https://doi.org/10.1186/s12876-015-0344-9 https://www.ncbi.nlm.nih.gov/pubmed/26341083 https://doi.org/10.3748/wjg.v21.i13.3928 https://www.ncbi.nlm.nih.gov/pubmed/25852278 https://doi.org/10.1016/j.jhep.2014.11.005 https://www.ncbi.nlm.nih.gov/pubmed/25450201 https://doi.org/10.1097/MD.0000000000007266 https://www.ncbi.nlm.nih.gov/pubmed/28658121 https://doi.org/10.1111/j.1440-1746.2008.05395.x https://www.ncbi.nlm.nih.gov/pubmed/18422961 https://doi.org/10.4254/wjh.v12.i11.1046 https://www.ncbi.nlm.nih.gov/pubmed/33312428 https://doi.org/10.3389/fpubh.2021.784718 https://www.ncbi.nlm.nih.gov/pubmed/35145947 https://doi.org/10.1186/s12885-021-08138-3 https://www.ncbi.nlm.nih.gov/pubmed/33849479 https://doi.org/10.1155/2021/8868370 https://www.ncbi.nlm.nih.gov/pubmed/33628341 https://doi.org/10.1186/s12872-021-02119-x https://www.ncbi.nlm.nih.gov/pubmed/34162333 https://so01.tci-thaijo.org/index.php/APST/article/view/248718 https://doi.org/10.1016/j.dsx.2020.09.008 https://www.ncbi.nlm.nih.gov/pubmed/32992217 https://doi.org/10.14456/apst.2018.10 https://doi.org/10.2147/CPAA.S285750 https://www.ncbi.nlm.nih.gov/pubmed/33707972 https://doi.org/10.4103/jfmpc.jfmpc_412_21 https://www.ncbi.nlm.nih.gov/pubmed/34660454 https://doi.org/10.33393/dti.2021.2291 https://www.ncbi.nlm.nih.gov/pubmed/34803374 https://doi.org/10.1177/21501327211000233 https://www.ncbi.nlm.nih.gov/pubmed/33733925 https://doi.org/10.35755/jmedassocthai.2021.S04.00059