Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Mar 3;29(3):1619-1633.
doi: 10.3390/curroncol29030136.

The OncoSim-Breast Cancer Microsimulation Model

Jean H E Yong  1 , Claude Nadeau  2 , William M Flanagan  2 , Andrew J Coldman  3 , Keiko Asakawa  2 , Rochelle Garner  2 , Natalie Fitzgerald  1 , Martin J Yaffe  4 , Anthony B Miller  5
Affiliations

The OncoSim-Breast Cancer Microsimulation Model

Jean H E Yong et al. Curr Oncol. .

Abstract

Background: OncoSim-Breast is a Canadian breast cancer simulation model to evaluate breast cancer interventions. This paper aims to describe the OncoSim-Breast model and how well it reproduces observed breast cancer trends.

Methods: The OncoSim-Breast model simulates the onset, growth, and spread of invasive and ductal carcinoma in situ tumours. It combines Canadian cancer incidence, mortality, screening program, and cost data to project population-level outcomes. Users can change the model input to answer specific questions. Here, we compared its projections with observed data. First, we compared the model's projected breast cancer trends with the observed data in the Canadian Cancer Registry and from Vital Statistics. Next, we replicated a screening trial to compare the model's projections with the trial's observed screening effects.

Results: OncoSim-Breast's projected incidence, mortality, and stage distribution of breast cancer were close to the observed data in the Canadian Cancer Registry and from Vital Statistics. OncoSim-Breast also reproduced the breast cancer screening effects observed in the UK Age trial.

Conclusions: OncoSim-Breast's ability to reproduce the observed population-level breast cancer trends and the screening effects in a randomized trial increases the confidence of using its results to inform policy decisions related to early detection of breast cancer.

Keywords: breast cancer; costs; disease progression; effectiveness; incidence; natural history; screening; simulation model.

PubMed Disclaimer

Conflict of interest statement

The authors declared no conflict of interest.

Figures

Figure 1
Figure 1
Schematic diagram of the OncoSim-Breast model.
Figure 2
Figure 2
Model inputs and outputs.
Figure 3
Figure 3
Incidence of invasive breast cancer (per 100,000 women), average per year (2008–2017), by province, OncoSim-Breast vs. Canadian Cancer Registry (CCR). * Data from Quebec were available only in 2008–2010 in the Canadian Cancer Registry because Quebec switched to a different cancer reporting system after 2010. Error bars represent the 95% confidence intervals.
Figure 4
Figure 4
(A) Incidence of invasive breast cancer (per 100,000 women) by age group in 1992–2013, OncoSim-Breast vs. Canadian Cancer Registry (CCR); (B) incidence of ductal carcinoma in situ (per 100,000 women) by age group in 1992–2013, OncoSim-Breast vs. Canadian Cancer Registry (CCR). Error bars represent the 95% confidence intervals.
Figure 4
Figure 4
(A) Incidence of invasive breast cancer (per 100,000 women) by age group in 1992–2013, OncoSim-Breast vs. Canadian Cancer Registry (CCR); (B) incidence of ductal carcinoma in situ (per 100,000 women) by age group in 1992–2013, OncoSim-Breast vs. Canadian Cancer Registry (CCR). Error bars represent the 95% confidence intervals.
Figure 5
Figure 5
Distribution of breast cancer by stage at diagnosis, females, Canada, 2011–2015, OncoSim-Breast vs. Canadian Cancer Registry. * The Canadian Cancer Registry did not include data from Quebec in 2011–2015 because Quebec switched to a different cancer reporting system after 2010.
See this image and copyright information in PMC

References

    1. Miller A.B., To T., Baines C.J., Wall C. The Canadian National Breast Screening Study-1: Breast cancer mortality after 11 to 16 years of follow-up: A randomized screening trial of mammography in women age 40 to 49 years. Ann. Intern. Med. 2002;137:305–312. doi: 10.7326/0003-4819-137-5_Part_1-200209030-00005. - DOI - PubMed
    1. Nyström L., Bjurstam N., Jonsson H., Zackrisson S., Frisell J. Reduced breast cancer mortality after 20+ years of follow-up in the Swedish randomized controlled mammography trials in Malmö, Stockholm, and Göteborg. J. Med. Screen. 2017;24:34–42. doi: 10.1177/0969141316648987. - DOI - PubMed
    1. Saadatmand S., Bretveld R., Siesling S., Tilanus-Linthorst M.M.A. Influence of tumour stage at breast cancer detection on survival in modern times: Population based study in 173,797 patients. BMJ. 2015;351:h4901. doi: 10.1136/bmj.h4901. - DOI - PMC - PubMed
    1. Alagoz O., Berry D.A., de Koning H.J., Feuer E.J., Lee S.J., Plevritis S.K., Schechter C.B., Stout N.K., Trentham-Dietz A., Mandelblatt J.S. Introduction to the Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer models. Med. Decis. Mak. 2018;38:3S–8S. doi: 10.1177/0272989X17737507. - DOI - PMC - PubMed
    1. Coldman A., Flanagan W., Nadeau C., Wolfson M., Fitzgerald N., Memon S., Gauvreau C., Miller A., Earle C. Projected effect of fecal immunochemical test threshold for colorectal cancer screening on outcomes and costs for Canada using the OncoSim microsimulation model. J. Cancer Policy. 2017;13:38–46. doi: 10.1016/j.jcpo.2017.07.004. - DOI

Publication types