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

  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. A Nomogram For Predicting Colorectal Cancer Liver Metastasis Using Circulating Tumor Cells From The First Drainage Vein.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. A Nomogram For Predicting Colorectal Cancer Liver Metastasis Using Circulating Tumor Cells From The First Drainage Vein.

Related Experiment Video

Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones
11:43

Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones

Published on: November 30, 2016

12.6K

A nomogram for predicting colorectal cancer liver metastasis using circulating tumor cells from the first drainage vein.

Xiaoyu Yang1, Zhongguo Zhang1, Xue Bi1

  • 1Liaoning Cancer Hospital & Institute, Cancer Hospital of Dalian University of Technology, Cancer Hospital of China Medical University, PR China.

European Journal of Surgical Oncology : the Journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
|August 9, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

A new nomogram model combining circulating tumor cells (CTC) from the first drainage vein (FDV) and clinical factors effectively predicts liver metastasis in colorectal cancer (CRC) patients, aiding clinical decisions.

Keywords:
CRCCTCFDVLiver metastases

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

239
Portal Vein Injection of Colorectal Cancer Organoids to Study the Liver Metastasis Stroma
07:59

Portal Vein Injection of Colorectal Cancer Organoids to Study the Liver Metastasis Stroma

Published on: September 3, 2021

6.3K

Related Experiment Videos

Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones
11:43

Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones

Published on: November 30, 2016

12.6K
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

239
Portal Vein Injection of Colorectal Cancer Organoids to Study the Liver Metastasis Stroma
07:59

Portal Vein Injection of Colorectal Cancer Organoids to Study the Liver Metastasis Stroma

Published on: September 3, 2021

6.3K

Area of Science:

  • Oncology
  • Medical Diagnostics
  • Cancer Research

Background:

  • Colorectal cancer (CRC) liver metastasis (mCRC) is a significant challenge in patient outcomes.
  • Accurate prediction of mCRC is crucial for timely and effective clinical intervention.

Purpose of the Study:

  • To develop and validate a predictive nomogram for liver metastasis in CRC patients.
  • To integrate circulating tumor cells (CTC) from the first drainage vein (FDV) with clinical parameters for enhanced prediction.
  • To provide a tool for improved clinical diagnosis and treatment strategies.

Main Methods:

  • A cohort of 343 CRC patients was analyzed.
  • Multivariate logistic regression identified independent predictors for mCRC.
  • Nomograms were constructed and validated using ROC curves, calibration plots, and decision curve analysis (DCA).

Main Results:

  • CTC levels in FDV were significantly higher in patients with liver metastasis.
  • Vascular invasion, T stage, CEA, CA19-9, and CTC were identified as key predictors.
  • The nomogram demonstrated strong discriminatory ability (AUC 0.871 training, 0.891 validation) and good clinical utility.

Conclusions:

  • A validated nomogram integrating CTC from FDV and clinical factors accurately predicts mCRC.
  • This model offers a valuable tool for assessing the risk of liver metastasis in CRC patients.
  • The findings support enhanced clinical decision-making for CRC management.