Estimating the current and future cancer burden in Canada: Methodological framework of the Canadian population attributable risk of cancer (ComPARe) study
BMJ Open , Volume 8 - Issue 7
Introduction The Canadian Population Attributable Risk of Cancer project aims to quantify the number and proportion of cancer cases incident in Canada, now and projected to 2042, that could be prevented through changes in the prevalence of modifiable exposures associated with cancer. The broad risk factor categories of interest include tobacco, diet, energy imbalance, infectious diseases, hormonal therapies and environmental factors such as air pollution and residential radon. Methods and analysis Using a national network, we will use population-attributable risks (PAR) and potential impact fractions (PIF) to model both attributable (current) and avoidable (future) cancers. The latency periods and the temporal relationships between exposures and cancer diagnoses will be accounted for in the analyses. For PAR estimates, historical exposure prevalence data and the most recent provincial and national cancer incidence data will be used. For PIF estimates, we will model alternative or counterfactual' distributions of cancer risk factor exposures to assess how cancer incidence could be reduced under different scenarios of population exposure, projecting incidence to 2042. Dissemination The framework provided can be readily extended and applied to other populations or jurisdictions outside of Canada. An embedded knowledge translation and exchange component of this study with our Canadian Cancer Society partners will ensure that these findings are translated to cancer programmes and policies aimed at population-based cancer risk reduction strategies.
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Brenner, D.R. (Darren R.), Poirier, A.E. (Abbey E.), Walter, S.D. (Stephen D.), King, W.D. (Will D.), Franco, E.L. (Eduardo L.), Demers, P.A. (Paul A.), … Friedenreich, C.M. (Christine M.). (2018). Estimating the current and future cancer burden in Canada: Methodological framework of the Canadian population attributable risk of cancer (ComPARe) study. BMJ Open, 8(7). doi:10.1136/bmjopen-2018-022378