Evidence map›Paper›PMID 34036521›Full record

ArticleCanadian journal of public health = Revue canadienne de sante publique2021

Estimating the future cancer management costs attributable to modifiable risk factors in Canada.

Yibing Ruan, Abbey E Poirier, Joy Pader, Keiko Asakawa, Chaohui Lu, Saima Memon, Anthony B Miller, Stephen D Walter, Paul J Villeneuve, Will D King and 5 more

Abstract read
In one paragraph

Article in Canadian journal of public health = Revue canadienne de sante publique, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Shooting for the Moon: Can We Cut Cancer Mortality in Canada By 50% By 2050?Cancer control : journal of the Moffitt Cancer Center
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Yibing RuanDepartment of Cancer Epidemiology and Prevention Research, CancerControl Alberta, Alberta Health Services, Calgary, Alberta, T2S 3C3, Canada.
Abbey E PoirierDepartment of Cancer Epidemiology and Prevention Research, CancerControl Alberta, Alberta Health Services, Calgary, Alberta, T2S 3C3, Canada.
Joy PaderDepartment of Cancer Epidemiology and Prevention Research, CancerControl Alberta, Alberta Health Services, Calgary, Alberta, T2S 3C3, Canada.
Keiko AsakawaStatistics Canada, Ottawa, Ontario, Canada.
Chaohui LuStatistics Canada, Ottawa, Ontario, Canada.
Saima MemonCanadian Partnership Against Cancer, Toronto, Ontario, Canada.
Anthony B MillerCanadian Partnership Against Cancer, Toronto, Ontario, Canada.
Stephen D WalterDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.
Paul J VilleneuveDepartment of Health Sciences, Carleton University, Ottawa, Ontario, Canada.
Will D KingDepartment of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.
Karena D VoleskyGerald Bronfman Department of Oncology, Division of Cancer Epidemiology and Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.
Leah SmithCanadian Cancer Society, Toronto, Ontario, Canada.
Prithwish DeCancer Care Ontario, Toronto, Ontario, Canada.
Christine M FriedenreichDepartment of Cancer Epidemiology and Prevention Research, CancerControl Alberta, Alberta Health Services, Calgary, Alberta, T2S 3C3, Canada.
Darren R BrennerDepartment of Cancer Epidemiology and Prevention Research, CancerControl Alberta, Alberta Health Services, Calgary, Alberta, T2S 3C3, Canada. Darren.Brenner@ucalgary.ca.ORCID http://orcid.org/0000-0002-3027-290X

Funding

Canadian Cancer Society Partner Prevention Research Grant 703106
6 · The paper itself

Abstract

objectivesAn estimated 33-37% of incident cancers in Canada are attributable to modifiable risk factors. Interventions targeting these risk factors would minimize the substantial health and economic burdens Canadians face due to cancer. We estimate the future health and economic burden of cancer in Canada by incorporating data from the Canadian Population Attributable Risk of Cancer (ComPARe) study into OncoSim, a web-based microsimulation tool.

methodsUsing the integrated OncoSim population attributable risk and population impact measures, we evaluated risk factor-targeted intervention scenarios implemented in 2020, assuming the targeted risk factor prevalence reduction would be achieved by 2032 with a 12-year latency period.

resultsWe estimate that smoking will be the largest contributor to cancer-related costs, with a cost of CAD $44.4 billion between 2032 and 2044. An estimated CAD $3.3 billion of the cost could be avoided with a 30% reduction in smoking prevalence by 2022. Following smoking, the next highest cancer management costs are associated with inadequate physical activity and excess body weight, accounting for CAD $10.7 billion ($2.7 billion avoidable) and CAD $9.8 billion ($3.2 billion avoidable), respectively. Avoidable costs for other risk factors range from CAD $90 million to CAD $2.5 billion.

conclusionInterventions targeting modifiable cancer risk factors could prevent a substantial number of incident cancer cases and billions of dollars in cancer management costs. With limited budgets and rising costs in cancer care in Canada, these simulation models and results are valuable for researchers and policymakers to inform decisions and prioritize and evaluate intervention programs.

Indexed as

Health Care CostsNeoplasmsCanadaCost of IllnessForecastingHumansRisk FactorsSmokingCancer costCancer managementCancer preventionEconomic burden

Identifiers

PMID34036521
PMCPMC8651827

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.