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Tran, Vinh Thanh; Phan, Thang Thanh; Nguyen, Tran Bao; Le, Thao Thi; Tran, Thanh-Tram Thi; Nguyen, Anh-Thu Thi; Nguyen, Hang Thuy; Nguyen, Ngoc-Diep Bui; Ho, Toan Trong; Pho, Suong Phuoc; Nguyen, Thuy-An Thi; Nguyen, Hue Thi; Mai, Huyen Thi; Pham, Bich-Tuyen Thi; Nguyen, Khoa Dinh; Le, Binh Thanh; Nguyen, Thuc Tri; Nguyen, Son Truong

The diagnostic performance of AFP and PIVKA-II models for non-B non-C hepatocellular carcinoma

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  • Media type: E-Article
  • Title: The diagnostic performance of AFP and PIVKA-II models for non-B non-C hepatocellular carcinoma
  • Contributor: Tran, Vinh Thanh; Phan, Thang Thanh; Nguyen, Tran Bao; Le, Thao Thi; Tran, Thanh-Tram Thi; Nguyen, Anh-Thu Thi; Nguyen, Hang Thuy; Nguyen, Ngoc-Diep Bui; Ho, Toan Trong; Pho, Suong Phuoc; Nguyen, Thuy-An Thi; Nguyen, Hue Thi; Mai, Huyen Thi; Pham, Bich-Tuyen Thi; Nguyen, Khoa Dinh; Le, Binh Thanh; Nguyen, Thuc Tri; Nguyen, Son Truong
  • Published: Springer Science and Business Media LLC, 2023
  • Published in: BMC Research Notes, 16 (2023) 1
  • Language: English
  • DOI: 10.1186/s13104-023-06600-y
  • ISSN: 1756-0500
  • Keywords: General Biochemistry, Genetics and Molecular Biology ; General Medicine
  • Origination:
  • Footnote:
  • Description: Abstract Objective This study aims to describe the diagnostic performance of alpha-fetoprotein (AFP), alpha-fetoprotein L3 isoform (AFP-L3), protein induced by vitamin K absence II (PIVKA-II), and combined biomarkers for non-B non-C hepatocellular carcinoma (NBNC-HCC). Results A total of 681 newly-diagnosed primary liver disease subjects (385 non-HCC, 296 HCC) who tested negativity for the hepatitis B surface antigen (HBsAg) and hepatitis C antibody (anti-HCV) enrolled in this study. At the cut-off point of 3.8 ng/mL, AFP helps to discriminate HCC from non-HCC with an area under the curve (AUC) value of 0.817 (95% confidence interval [CI]: 0.785–0.849). These values of AFP-L3 (cut-off 0.9%) and PIVKA-II (cut-off 57.7 mAU/mL) were 0.758 (95%CI: 0.725–0.791) and 0.866 (95%CI: 0.836–0.896), respectively. The Bayesian Model Averaging (BMA) statistic identified the optimal model, including patients’ age, aspartate aminotransferase, AFP, and PIVKA-II combination, which helps to classify HCC with better performance (AUC = 0.896, 95%CI: 0.872–0.920, P < 0.001). The sensitivity and specificity of the optimal model reached 81.1% (95%CI: 76.1–85.4) and 83.2% (95%CI: 78.9–86.9), respectively. Further analyses indicated that AFP and PIVKA-II markers and combined models have good-to-excellent performance detecting curative resected HCC, separating HCC from chronic hepatitis, dysplastic, and hyperplasia nodules.
  • Access State: Open Access