Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

345
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
345

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Predicting preoperative lymph node metastasis of hilar cholangiocarcinoma based on deep learning radiomics.

The ultrasound journal·2026
Same author

A risk-based post ablation follow-up strategy for hepatocellular carcinoma.

JHEP reports : innovation in hepatology·2026
Same author

Development of a Scoring System For Severe Acute Pancreatitis And Utility of US-guided Catheter Drainage in High-risk Patients.

Academic radiology·2026
Same author

FUGEA: Fused unified gradient ensemble for cross-architecture transferable attacks.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Doxorubicin-loaded perfluoropentane nanodroplets enhance radiofrequency ablation efficacy by relieving tumor hypoxia.

Nanomedicine (London, England)·2026
Same author

Ultrasound-guided percutaneous ablation outcomes in patients with HBcAb positivity non-B non-C hepatocellular carcinoma: a multicenter long-term follow-up study.

International journal of surgery (London, England)·2025

Related Experiment Video

Updated: Jul 1, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K

Cox model risk score to predict survival of intrahepatic cholangiocarcinoma after ultrasound-guided ablation.

Yueting Sun1, Baoxian Liu1, Hui Shen1

  • 1Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, No. 58 Zhong Shan Road, Guangzhou, 510000, Guangdong Province, China.

Abdominal Radiology (New York)
|March 5, 2024
PubMed
Summary

This study developed a predictive model for intrahepatic cholangiocarcinoma (iCCA) survival after ablation. Key factors include age, tumor size, and CA199 levels, aiding in risk assessment for patients.

Keywords:
Intrahepatic cholangiocarcinomaOverall survivalRisk regression modelThermal ablationUltrasound

More Related Videos

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

265
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
07:32

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis

Published on: April 12, 2024

1.3K

Related Experiment Videos

Last Updated: Jul 1, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

265
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
07:32

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis

Published on: April 12, 2024

1.3K

Area of Science:

  • Hepatobiliary Surgery
  • Oncology
  • Medical Imaging

Background:

  • Intrahepatic cholangiocarcinoma (iCCA) is a challenging liver cancer.
  • Ultrasound-guided ablation offers a minimally invasive treatment option for iCCA.
  • Predicting survival outcomes after ablation is crucial for patient management.

Purpose of the Study:

  • To identify factors influencing overall survival (OS) and progression-free survival (PFS) in iCCA patients post-ablation.
  • To develop and validate a predictive model for survival risk in iCCA patients undergoing ablation.

Main Methods:

  • Retrospective analysis of 54 patients with 86 iCCAs treated between 2008 and 2022.
  • Cox regression analysis to determine predictors of OS and PFS.
  • Development and validation of a survival prediction model using time-dependent ROC and decision curve analysis.

Main Results:

  • Pre-ablation CA199 > 140 U/ml predicted poor PFS.
  • Age > 70, early recurrence, tumor size > 1.5 cm, and high CA199 predicted poor OS.
  • The developed model demonstrated good predictive performance with AUCs ranging from 0.767 to 0.854.

Conclusions:

  • A novel model effectively predicts survival outcomes for iCCA patients after thermal ablation.
  • The model incorporates age, tumor size, recurrence status, and CA199 levels.
  • Further validation studies are recommended to confirm the model's utility.