Related Experiment Video
Updated: Jan 28, 2026

A "Patient-Like" Orthotopic Syngeneic Mouse Model of Hepatocellular Carcinoma Metastasis
Published on: October 24, 2015
Nomogram predicting extrahepatic metastasis of hepatocellular carcinoma based on commonly available clinical data
Chern-Horng Lee1, Chee-Jen Chang2, Yu-Jr Lin2
1Division of General Internal Medicine and Geriatrics Chang Gung Memorial Hospital Taoyuan Taiwan.
Background And Aim:
Extrahepatic metastasis (EHM) of hepatocellular carcinoma (HCC) leads to a worse prognosis. We aimed to develop a nomogram based on noninvasive pretreatment clinical data to predict EHM of HCC sooner.
Methods:
Three cohorts containing 1820, 479, and 988 HCC patients were enrolled from three hospitals in different regions in Taiwan and served as the training and validation cohorts. Pretreatment clinical data were analyzed by Cox regression modeling for independent risk factors of EHM.
Results:
Platelet count ≥ 200 × 103/μL, serum alfa-fetoprotein ≥ 100 ng/dL, tumor size ≥ 3 cm, tumor number > 1, and macrovascular invasion were independent risk factors for EHM and were used to develop a nomogram. This nomogram had concordance indices of 0.733 (95% confidence interval [CI]: 0.688-0.778) and 0.739 (95% CI: 0.692-0.787) for the prediction of EHM during a 5-year follow-up duration in the training and validation cohorts, respectively. A nomogram score > 61 implied a high risk of EHM (hazard ratio [HR] = 3.83; 95% CI: 2.77-5.31, P < 0.001).
Conclusion:
We have developed a nomogram that could accurately predict EHM of HCC and be readily available for formulating individualized treatment for all individual HCC patients to improve therapeutic efficacy.
More Related Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
Related Concept Videos
Common Ion Effect
Statistical Software for Data Analysis and Clinical Trials
Dosage Regimen Designs: Nomograms and Tabulations
Metastasis
Epithelial-to-Mesenchymal Transition
The epithelial-to-mesenchymal transition or EMT is a developmental process commonly observed in wound healing, embryogenesis, and cancer metastasis. EMT is induced by transforming growth factor-beta (TGF-β) or receptor tyrosine kinase (RTK) ligands, which further...
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.