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

472
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...
472

You might also read

Related Articles

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

Sort by
Same author

Adherence to the Mediterranean diet and risk of pancreatic cancer: an analysis of 2.3 million participants in the Pooling Project of Prospective Studies of Diet and Cancer (DCPP).

European journal of epidemiology·2026
Same author

Geographic variation in female breast cancer incidence and mortality in Canada.

Health reports·2026
Same author

Enhancing the OncoSim-Breast model using Canadian breast density information.

Health reports·2026
Same author

Associations of Job Strain and Health: Differences Among Nurses and Personal Support Workers in Residential Care Homes During the COVID-19 Pandemic.

Workplace health & safety·2026
Same author

Projected estimates of cancer in Canada in 2026.

CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne·2026
Same author

CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne·2026
Same journal

Predicting Post-Radiotherapy Lymphocyte Recovery for Individualized Risk Stratification in Locally Advanced Esophageal Squamous Cell Carcinoma.

Current oncology (Toronto, Ont.)·2026
Same journal

From Adjunct to Essential: Integrating Supportive Care into Oncology.

Current oncology (Toronto, Ont.)·2026
Same journal

Next-Generation Sequencing in Differentiated Thyroid Cancer Patients Treated with Lenvatinib: Results and Challenges in Real-Life Practice.

Current oncology (Toronto, Ont.)·2026
Same journal

The Route of Administration Determines the Efficacy of Zinc in Preventing Radiation-Induced Oral Mucositis: A Systematic Review and Meta-Analysis.

Current oncology (Toronto, Ont.)·2026
Same journal

Mechanisms of Progression and Challenges for Intervention in the Natural History of Early Prostate Cancer: A Narrative Review.

Current oncology (Toronto, Ont.)·2026
Same journal

Maintenance Therapy in Acute Myeloid Leukemia: Current Perspectives and Future Directions.

Current oncology (Toronto, Ont.)·2026
See all related articles

Related Experiment Video

Updated: Sep 29, 2025

Modeling Breast Cancer in Human Breast Tissue using a Microphysiological System
10:51

Modeling Breast Cancer in Human Breast Tissue using a Microphysiological System

Published on: April 23, 2021

4.3K

The OncoSim-Breast Cancer Microsimulation Model.

Jean H E Yong1, Claude Nadeau2, William M Flanagan2

  • 1Canadian Partnership Against Cancer, Toronto, ON M5H 1J8, Canada.

Current Oncology (Toronto, Ont.)
|March 24, 2022
PubMed
Summary
This summary is machine-generated.

The OncoSim-Breast model accurately reproduces Canadian breast cancer trends and screening trial outcomes. This validation enhances confidence in using the simulation for breast cancer intervention policy decisions.

Keywords:
breast cancercostsdisease progressioneffectivenessincidencenatural historyscreeningsimulation model

More Related Videos

Modeling Ovarian Cancer Multicellular Spheroid Behavior in a Dynamic 3D Peritoneal Microdevice
11:34

Modeling Ovarian Cancer Multicellular Spheroid Behavior in a Dynamic 3D Peritoneal Microdevice

Published on: February 18, 2017

8.8K
Live Imaging of Drug Responses in the Tumor Microenvironment in Mouse Models of Breast Cancer
08:26

Live Imaging of Drug Responses in the Tumor Microenvironment in Mouse Models of Breast Cancer

Published on: March 24, 2013

25.1K

Related Experiment Videos

Last Updated: Sep 29, 2025

Modeling Breast Cancer in Human Breast Tissue using a Microphysiological System
10:51

Modeling Breast Cancer in Human Breast Tissue using a Microphysiological System

Published on: April 23, 2021

4.3K
Modeling Ovarian Cancer Multicellular Spheroid Behavior in a Dynamic 3D Peritoneal Microdevice
11:34

Modeling Ovarian Cancer Multicellular Spheroid Behavior in a Dynamic 3D Peritoneal Microdevice

Published on: February 18, 2017

8.8K
Live Imaging of Drug Responses in the Tumor Microenvironment in Mouse Models of Breast Cancer
08:26

Live Imaging of Drug Responses in the Tumor Microenvironment in Mouse Models of Breast Cancer

Published on: March 24, 2013

25.1K

Area of Science:

  • Oncology
  • Biostatistics
  • Health Economics

Background:

  • OncoSim-Breast is a Canadian simulation model designed for evaluating breast cancer interventions.
  • The model simulates tumor development, progression, and metastasis.

Purpose of the Study:

  • To describe the OncoSim-Breast model.
  • To validate the model's accuracy by comparing its projections with observed breast cancer trends and screening trial data.

Main Methods:

  • The OncoSim-Breast model integrates Canadian data on cancer incidence, mortality, screening programs, and costs.
  • Model projections were compared against data from the Canadian Cancer Registry, Vital Statistics, and a randomized screening trial (UK Age trial).

Main Results:

  • OncoSim-Breast projections for breast cancer incidence, mortality, and stage distribution closely matched observed Canadian data.
  • The model successfully replicated the screening effects observed in the UK Age trial.

Conclusions:

  • The OncoSim-Breast model demonstrates a high degree of accuracy in reproducing population-level breast cancer trends.
  • The model's validated performance supports its use in informing policy decisions for early breast cancer detection and intervention strategies.