ArticleBMC research notes2023
The diagnostic performance of AFP and PIVKA-II models for non-B non-C hepatocellular carcinoma.
Article in BMC research notes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- Circulating Cell-Free DNA Analysis for Diagnostic and Prognostic Assessment of Hepatocellular Carcinoma in Cirrhosis.International journal of molecular sciences · 2026Article
- Hepatocellular Carcinoma Over Three Decades: from Screening Evolution to Integrated Therapeutic Strategies.Journal of cancer prevention · 2026Review
- Combined DeRitis ratio and alkaline phosphatase on the prediction of portal vein tumor thrombosis in patients with hepatocellular carcinoma.Scientific reports · 2024Article
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Authors and funding
18 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis 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).
resultsA 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.
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