ArticleAnnals of surgical oncology2023
The Prognostic Value of Preoperative Serum Markers and Risk Classification in Patients with Hepatocellular Carcinoma.
Article in Annals of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 8 citations in OpenAlex.
- Early recurrence prediction and risk stratification of hepatocellular carcinoma after transarterial chemoembolization achieving imaging complete response based on contrast-enhanced CT machine learning.Abdominal radiology (New York) · 2026Article
- Review
- Concordance Index-Based Comparison of Inflammatory and Classical Prognostic Markers in Untreated Hepatocellular Carcinoma.Journal of clinical medicine · 2025Article
- 3D synergistic tumor-liver analysis further improves the efficacy prediction in hepatocellular carcinoma: a multi-center study.BMC cancer · 2025Article
- Prognostic Value of Des-Gamma-Carboxy Prothrombin in AFP-Negative Hepatocellular Carcinoma Patients Following Liver Resection:Journal of Cancer · 2025Article
- The Prognostic Value of Preoperative Serum Markers and Risk Classification in Patients with Hepatocellular Carcinoma.Annals of surgical oncology · 2024Article
- PIVKA-II combined with tumor burden score to predict long-term outcomes of AFP-negative hepatocellular carcinoma patients after liver resection.Cancer medicine · 2024Article
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14 authors at 8 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundComplex hepatocellular carcinoma (HCC) prognostic biomarkers have been reported in various studies. We aimed to establish biomarkers that could predict prognosis, and formulate a simple classification using non-invasive preoperative blood test data.
methodsWe retrospectively identified 305 patients for a discovery cohort who had undergone HCC-related hepatectomy at four Japanese university hospitals between January 1, 2011 and December 31, 2013. Preoperative blood test parameter optimal cut-off values were determined using receiver operating characteristic curve analysis. Cox uni- and multivariate analyses were used to determine independent prognostic factors. Risk classifications were established using classification and regression tree (CART) analysis. Validation was performed with 267 patients from three other hospitals.
resultsIn multivariate analysis, α-fetoprotein (AFP, p < 0.001), protein induced by vitamin K absence or antagonist-II (PIVKA-II, p = 0.006), and C-reactive protein (CRP, p < 0.001) were independent prognostic factors for overall survival (OS). AFP (p = 0.007), total bilirubin (p = 0.001), and CRP (p = 0.003) were independent recurrent risk factors for recurrence-free survival (RFS). CART analysis results formed OS (CRP, AFP, and albumin) and RFS (PIVKA-II, CRP, and total bilirubin) decision trees, based on machine learning using preoperative serum markers, with three risk classifications. Five-year OS (low risk, 80.0%; moderate risk, 56.3%; high risk, 25.2%; p < 0.001) and RFS (low risk, 43.4%; moderate risk, 30.8%; high risk, 16.6%; p < 0.001) risks differed significantly. These classifications also stratified OS and RFS risk in the validation cohort.
conclusionThree simple risk classifications using preoperative non-invasive prognostic factors could predict prognosis.
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