Dataset Information

Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study.

ABSTRACT:

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.

SUBMITTER: Brenner DR

PROVIDER: S-EPMC6074628 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study.

Brenner Darren R DR Poirier Abbey E AE Walter Stephen D SD King Will D WD Franco Eduardo L EL Demers Paul A PA Villeneuve Paul J PJ Ruan Yibing Y Khandwala Farah F Grevers Xin X Nuttall Robert R Smith Leah L De Prithwish P Volesky Karena K O'Sullivan Dylan D Hystad Perry P Friedenreich Christine M CM

BMJ open 20180801 7

<h4>Introduction</h4>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.<h4>Methods ...[more]

PMID: 30068623

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Project description:BackgroundThe Global Burden of Disease (GBD) studies have transformed global understanding of health risks by producing comprehensive estimates of attributable disease burden, or the current disease that would be eliminated if a risk factor did not exist. Yet many have noted the greater policy significance of avoidable burden, or the future disease that could actually be eliminated if a risk factor were eliminated today. Avoidable risk may be considerably lower than attributable risk if baseline levels of exposure or disease are declining, or if a risk factor carries lagged effects on disease. As global efforts to deliver clean cookstoves accelerate, a temporal estimation of avoidable risk due to household air pollution (HAP) becomes increasingly important, particularly in light of the rapid uptake of modern stoves and ongoing epidemiologic transitions in regions like South and Southeast Asia.Methods and findingsWe estimate the avoidable burden associated with HAP using International Futures (IFs), an integrated forecasting system that has been used to model future global disease burdens and risk factors. Building on GBD and other estimates, we integrated a detailed HAP exposure estimation and exposure-response model into IFs. We then conducted a counterfactual experiment in which HAP exposure is reduced to theoretical minimum levels in 2015. We evaluated avoidable mortality and DALY reductions for the years 2015 to 2024 relative to a Base Case scenario in which only endogenous changes occurred. We present results by cause and region, looking at impacts on acute lower respiratory infection (ALRI) and four noncommunicable diseases (NCDs). We found that just 2.6% of global DALYs would be averted between 2015 and 2024, compared to 4.5% of global DALYs attributed to HAP in the 2010 GBD study, due in large part to the endogenous tendency towards declining traditional stove usage in the IFs base case forecast. The extent of diminished impact was comparable for ALRI and affected NCDs, though for different reasons. ALRI impacts diminish due to the declining burden of ALRI in the base case forecast, particularly apparent in South Asia and Southeast Asia. Although NCD burdens are rising in regions affected by HAP, the avoidable risk of NCD nonetheless diminishes due to lagged effects. Because the stove transition and the decline of ALRI are proceeding more slowly in Sub-Saharan Africa, avoidable impacts would also be more persistent (3.9% of total DALY due to HAP) compared to South Asia (3.6%) or Southeast Asia (2.5%).ConclusionsOur results illustrate how a temporal dynamic calculation of avoidable risk may yield different estimates, compared to a static attributable risk estimate, of the global and regional burden of disease. Our results suggest a window of rising and falling opportunity for HAP interventions that may have already closed in Southeast Asia and may be closing quickly in South Asia, but may remain open longer in Sub-Saharan Africa. A proper accounting of global health priorities should apply an avoidable risk framework that considers the role of ongoing social, economic and health transitions in constantly altering the disease and risk factor landscape.

Dataset Information

Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study.

Introduction

Methods and analysis

Dissemination

Publications

Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study.

Similar Datasets

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