ArticleTechnology in cancer research & treatment
A Clinical Tool to Predict the Microvascular Invasion Risk in Patients with Hepatocellular Carcinoma.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Model Construction for Predicting Preoperative Microvascular Invasion of Hepatocellular Carcinoma by Gadoxetic Acid Disodium-Enhanced Magnetic Resonance Imaging Combined with Serology.Medical science monitor : international medical journal of experimental and clinical research · 2025Article
- Chinese expert consensus on the diagnosis and treatment of hepatocellular carcinoma with microvascular invasion (2024 edition).Hepatobiliary surgery and nutrition · 2025Review
- Predictive model based on blood cell analysis and coagulation function indicators for neuroblastic tumors staging diagnosis.Frontiers in oncology · 2025Article
- Clinical Nomogram Model for Pre-Operative Prediction of Microvascular Invasion of Hepatocellular Carcinoma before Hepatectomy.Medicina (Kaunas, Lithuania) · 2024Article
- Enhancing preoperative diagnosis of microvascular invasion in hepatocellular carcinoma: domain-adaptation fusion of multi-phase CT images.Frontiers in oncology · 2024Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundMicrovascular invasion (MVI) plays an important role in tumor progression. The aim of this study is to establish and validate an effective hematological nomogram for MVI prediction in hepatocellular carcinoma (HCC).
methodsA retrospective study was performed in a primary cohort that includes 1306 patients clinicopathologically diagnosed with HCC, and a validation cohort contained 563 continuous patients. Univariate logistic regression was used to assess the association between variables included both clinicopathologic factors and coagulation parameters (prothrombin time, activated partial thromboplastin time, fibrinogen, and thrombin time [TT]) and MVI. Multiple logistic regression was used to construct a prediction nomogram. We tested the accuracy of the nomogram by discrimination and calibration, and then plotted decision curves to assess the benefits of the nomogram-assisted decisions in a clinical context.
resultsIn the two cohorts, patients without MVI had the longest overall survival (OS), compared the OS with MVI. The multivariate analysis indicated that age, sex, tumor node metastasis (TNM) stage, aspartate aminotransferase, alpha fetoprotein, C-reactive protein, and TT were identified as significant independent predictors of MVI of HCC patients. The Hosmer-Lemeshow test showed good point estimate associated
conclusionsA noninvasive and easy-to-use nomogram was established and may be used to predict preoperative MVI in HCC.
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