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Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study
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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6074628/ https://www.ncbi.nlm.nih.gov/pubmed/30068623 http://dx.doi.org/10.1136/bmjopen-2018-022378 |
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author | Brenner, Darren R Poirier, Abbey E Walter, Stephen D King, Will D Franco, Eduardo L Demers, Paul A Villeneuve, Paul J Ruan, Yibing Khandwala, Farah Grevers, Xin Nuttall, Robert Smith, Leah De, Prithwish Volesky, Karena O’Sullivan, Dylan Hystad, Perry Friedenreich, Christine M |
author_facet | Brenner, Darren R Poirier, Abbey E Walter, Stephen D King, Will D Franco, Eduardo L Demers, Paul A Villeneuve, Paul J Ruan, Yibing Khandwala, Farah Grevers, Xin Nuttall, Robert Smith, Leah De, Prithwish Volesky, Karena O’Sullivan, Dylan Hystad, Perry Friedenreich, Christine M |
author_sort | Brenner, Darren R |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6074628 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-60746282018-08-09 Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study Brenner, Darren R Poirier, Abbey E Walter, Stephen D King, Will D Franco, Eduardo L Demers, Paul A Villeneuve, Paul J Ruan, Yibing Khandwala, Farah Grevers, Xin Nuttall, Robert Smith, Leah De, Prithwish Volesky, Karena O’Sullivan, Dylan Hystad, Perry Friedenreich, Christine M BMJ Open Epidemiology 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. BMJ Publishing Group 2018-08-01 /pmc/articles/PMC6074628/ /pubmed/30068623 http://dx.doi.org/10.1136/bmjopen-2018-022378 Text en © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Epidemiology Brenner, Darren R Poirier, Abbey E Walter, Stephen D King, Will D Franco, Eduardo L Demers, Paul A Villeneuve, Paul J Ruan, Yibing Khandwala, Farah Grevers, Xin Nuttall, Robert Smith, Leah De, Prithwish Volesky, Karena O’Sullivan, Dylan Hystad, Perry Friedenreich, Christine M Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study |
title | Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study |
title_full | Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study |
title_fullStr | Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study |
title_full_unstemmed | Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study |
title_short | Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study |
title_sort | estimating the current and future cancer burden in canada: methodological framework of the canadian population attributable risk of cancer (compare) study |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6074628/ https://www.ncbi.nlm.nih.gov/pubmed/30068623 http://dx.doi.org/10.1136/bmjopen-2018-022378 |
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