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.
Highlights
Emerging knowledge in breast cancer control has put pressure on the health system for the adoption of new technologies and policies
Randomized trials are the gold standard of evidence to introduce new interventions in clinical practice and public health; such evidence is not always relevant for informing policy decisions because the context of the interventions evolves quickly, compared with the time that elapses between the design of a trial and the availability of its results
Most breast cancer screening randomized trials were from the era before breast cancer adjuvant treatment was available and used film-screen mammography [1,2]; breast cancer survival has since vastly improved [3], and digital mammography has superseded film-screen mammography
Summary
Emerging knowledge in breast cancer control has put pressure on the health system for the adoption of new technologies and policies. An example includes breast cancer models developed by the CISNET breast cancer working group, where the models have been used extensively knowledge from experts in different areas [4]. An example includes breast cancer models developed by the CISNET breast cancer working group, where the models have been used extensively to investigate emerging issues in breast cancer control and to inform debates on topics such as breast density legislation in the US [4]. OncoSim-Breast is an example of such a model but developed for the Canadian population using Canadian data, whenever applicable It is the only breast cancer model of this nature, i.e., a microsimulation model developed foremerging informing various breast questions, When to investigate issues in breast cancercancer control control and to inform debatesinonCanada
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