The OncoSim model: development and use for better decision-making in Canadian cancer control

C.L. Gauvreau, N.R. Fitzgerald, S. Memon, W.M. Flanagan, C. Nadeau, K. Asakawa, R. Garner, A.B. Miller, W.K. Evans, C.M. Popadiuk, M. Wolfson, A.J. Coldman

Abstract


The Canadian Partnership Against Cancer was created in 2007 by the federal government to accelerate cancer control across Canada. Its OncoSim microsimulation model platform, which consists of a suite of specific cancer models, was conceived as a tool to augment conventional resources for population-level policy- and decision-making. The Canadian Partnership Against Cancer manages the OncoSim program, with funding from Health Canada and model development by Statistics Canada.

Microsimulation modelling allows for the detailed capture of population heterogeneity and health and demographic history over time. Extensive data from multiple Canadian sources were used as inputs or to validate the model. OncoSim has been validated through expert consultation; assessments of face validity, internal validity, and external validity; and model fit against observed data. The platform comprises three in-depth cancer models (lung, colorectal, cervical), with another in-depth model (breast) and a generalized model (25 cancers) being in development. Unique among models of its class, OncoSim is available online for public sector use free of charge. Users can customize input values and output display, and extensive user support is provided.

OncoSim has been used to support decision-making at the national and jurisdictional levels. Although simulation studies are generally not included in hierarchies of evidence, they are integral to informing cancer control policy when clinical studies are not feasible. OncoSim can evaluate complex intervention scenarios for multiple cancers.

Canadian decision-makers thus have a powerful tool to assess the costs, benefits, cost-effectiveness, and budgetary effects of cancer control interventions when faced with difficult choices for improvements in population health and resource allocation.

Keywords


OncoSim; cancer modelling; cancer outcome projections; cancer control; cancer system resource allocation

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DOI: http://dx.doi.org/10.3747/co.24.3850






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ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)