ArticleBMC cancer2025
Diagnostic and prognostic performance of serum GPC3 and PIVKA-II in AFP-negative hepatocellular carcinoma and establishment of nomogram prediction models.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Identification of novel circulating protein biomarkers for hepatocellular carcinoma superior to alpha-fetoprotein through a stemness index and secretome analysis.World journal of surgical oncology · 2026Article
- Serum Outperforms Plasma for Glypican-3 Quantification in Hepatocellular Carcinoma-A Prospective Comparative Study.Journal of clinical medicine · 2026Article
- Tumour-host divergence: a hypothesis for personalised blood-based early detection of hepatocellular carcinoma.Frontiers in oncology · 2026Article
- Protein Induced by Vitamin K Absence or Antagonist II in Primary Liver Cancer: Basic Research Insights and Clinical Applications.Journal of clinical and translational hepatology · 2025Review
- Utility of Alpha-Fetoprotein and Protein Induced by Vitamin K Absence or Antagonist-II Kinetics in Predicting Radiologic Response and Survival in Unresectable Hepatocellular Carcinoma Undergoing Immunotherapy.World journal of oncology · 2025Article
- CRAFITY and AFP/PIVKA-II Kinetics Predict Prognosis in Hepatocellular Carcinoma on Immunotherapy.Cancers · 2025Article
- Article
- Targeting Glypican-3 for Liver Cancer Therapy: Clinical Applications and Detection Methods.Journal of clinical and translational hepatology · 2025Review
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Authors and funding
7 authors.
Funding
Abstract
objectiveA significant proportion, ranging from 20 to 40%, of individuals with hepatocellular carcinoma (HCC) do not exhibit elevated Alpha-fetoprotein (AFP) levels. This study aimed to evaluate the utility of serum glypican-3 (GPC3) and protein induced by vitamin K absence or antagonist II (PIVKA-II) in an AFP-negative HCC (N-HCC) population, and to develop nomogram diagnostic and prognostic prediction models utilizing GPC3 and PIVKA-II.
methodsSerum GPC3 and PIVKA-II levels were measured in this case-control study, followed by the establishment of a receiver operating characteristic (ROC) curve, restricted cubic spline (RCS), and Kaplan-Meier survival curve. Additionally, a diagnostic prediction nomogram was constructed using univariate and multivariate logistic regression. Furthermore, we utilized least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression to develop a prognostic prediction nomogram. The performance of these models was evaluated using ROC curve analysis and decision curve analysis (DCA).
resultsSerum GPC3 and PIVKA-II expression levels were significantly elevated in untreated patients with N-HCC (especially stageI and tumor size < 3 cm) compared to those with AFP-negative benign liver disease (N-BLD). Derived from ROC analysis, the diagnostic cutoff points for GPC3 and PIVKA-II were set at 0.100 ng/mL and 40.00 mAU/mL, respectively. PIVKA-II demonstrated sensitivity and specificity of 84.62% and 90.38%, surpassing GPC3's 76.92% and 73.08%. The area under the ROC curve (AUC) for a diagnostic prediction nomogram incorporating GPC3, PIVKA-II, and gamma-glutamyltransferase (GGT) was 0.943 (95% CI: 0.912-0.974), superior to models using GPC3 or PIVKA-II alone. This model showed 95.20% sensitivity and 81.70% specificity in differentiating N-HCC from N-BLD. Stratifying patients into high-risk and low-risk groups using cutoff values established by RCS for GPC3 (0.124 ng/mL) and PIVKA-II (274 mAU/mL) revealed significant associations between these risk stratifications and patient survival. Finally, the use of GPC3-highrisk, cirrhosis, albumin (ALB), portal venous thrombosis (PVT), and surgical treatment as five parameters in the nomogram prognostic prediction model effectively differentiated between high- and low-risk prognostic patients with N-HCC with relatively high accuracy.
conclusionsSerum GPC3 and PIVKA-II demonstrate clinical significance in the timely detection and prognosis assessment of N-HCC. The application of nomogram prediction models based on GPC3 and PIVKA-II stands as an important adjunctive tool for diagnosing and prognosticating N-HCC.
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