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 Experiment Video

Updated: May 12, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison 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

Prediction models in Lynch syndrome.

Fay Kastrinos1, Judith Balmaña, Sapna Syngal

  • 1Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.

Familial Cancer
|April 5, 2013
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Detecting and Preventing Fraudulent Participation in Qualitative Research: Content Analysis of Two Multisite Studies.

Journal of medical Internet research·2026
Same author

Nationwide Trends in Colorectal Cancer Screening by the End of the COVID-19 Pandemic: Racial/Ethnic Differences and Opportunities.

Journal of the National Comprehensive Cancer Network : JNCCN·2026
Same author

RecQ DNA helicases germline variants in Lynch-like syndrome.

Genetics in medicine open·2026
Same author

Fraudulent and Imposter Participants in Qualitative Research: Experiences from Two Multi-Site Studies.

Journal of medical Internet research·2026
Same author

Optimising rare tumour risk syndromes care: clinical insights and the PREVENTABLE socioeconomic framework.

European journal of human genetics : EJHG·2026
Same author

Lynch syndrome integrative epidemiology and genetics (LINEAGE): rationale for cohort design.

Familial cancer·2026

Prediction models help identify individuals at risk for Lynch syndrome (hereditary non-polyposis colorectal cancer). These tools aid clinicians in determining the need for genetic testing and risk assessment.

Area of Science:

  • Genetics
  • Oncology
  • Clinical Decision Support

Background:

  • Lynch syndrome is an inherited condition increasing cancer risk.
  • Accurate identification of individuals with Lynch syndrome is crucial for timely intervention.
  • Current diagnostic strategies can be complex for healthcare providers.

Purpose of the Study:

  • To review and compare existing prediction models for Lynch syndrome identification.
  • To assess the performance and clinical utility of these models.
  • To discuss the integration of prediction models into routine clinical practice.

Main Methods:

  • Systematic review of developed Lynch syndrome prediction models.
  • Analysis of model performance based on validation studies.

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Predictive Immune Modeling of Solid Tumors
08:50

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

Related Experiment Videos

Last Updated: May 12, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison 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

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Predictive Immune Modeling of Solid Tumors
08:50

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

  • Comparison with alternative diagnostic approaches (clinical and molecular).

    • Main Results:

    • Various prediction models exist to estimate Lynch syndrome risk.
    • Model performance varies, necessitating careful selection and validation.
    • Prediction models offer a complementary tool to existing diagnostic strategies.

    Conclusions:

    • Prediction models are valuable aids for clinicians in identifying individuals at risk for Lynch syndrome.
    • Systematic implementation of these models can enhance cancer risk assessment and prevention efforts.
    • Further research and validation are important for optimizing their clinical use.