Evidence map›Paper›PMID 28615275›Full record

ArticleBMJ open2017

The burden of cancer attributable to modifiable risk factors: the Australian cancer-PAF cohort consortium.

Maria E Arriaga, Claire M Vajdic, Karen Canfell, Robert MacInnis, Peter Hull, Dianna J Magliano, Emily Banks, Graham G Giles, Robert G Cumming, Julie E Byles and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Psycho-oncology · 2020
    Pooled it
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  9. A review of harmonization methods for studying dietary patterns.Smart health (Amsterdam, Netherlands) · 2022
    Article
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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

17 authors.

Maria E ArriagaCentre for Big Data Research in Health, University of New South Wales, Sydney, Australia.
Claire M VajdicCentre for Big Data Research in Health, University of New South Wales, Sydney, Australia.
Karen CanfellCancer Research Division, Cancer Council New South Wales, Sydney, Australia.
Robert MacInnisCancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
Peter HullCentre for Big Data Research in Health, University of New South Wales, Sydney, Australia.
Dianna J MaglianoDiabetes and Population Health Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, Australia.
Emily BanksANU College of Medicine, Biology and Environment, Australian National University, Canberra, Australia.
Graham G GilesCancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
Robert G CummingSchool of Public Health, University of Sydney, Sydney, Australia.
Julie E BylesResearch Centre for Gender, Health and Ageing, University of Newcastle, Newcastle, Australia.
Anne W TaylorSchool of Medicine, University of Adelaide, Adelaide, Australia.
Jonathan E ShawClinical Diabetes Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, Australia.
Kay PriceSchool of Nursing and Midwifery, University of South Australia, Adelaide, Australia.
Vasant HiraniSchool of Public Health, University of Sydney, Sydney, Australia.
Paul MitchellCentre for Vision Research, University of Sydney, Sydney, Australia.
Barbara-Ann AdelsteinPrince of Wales Clinical School, University of New South Wales, Sydney, Australia.
Maarit A LaaksonenCentre for Big Data Research in Health, University of New South Wales, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo estimate the Australian cancer burden attributable to lifestyle-related risk factors and their combinations using a novel population attributable fraction (PAF) method that accounts for competing risk of death, risk factor interdependence and statistical uncertainty.

participants365 173 adults from seven Australian cohort studies. We linked pooled harmonised individual participant cohort data with population-based cancer and death registries to estimate exposure-cancer and exposure-death associations. Current Australian exposure prevalence was estimated from representative external sources. To illustrate the utility of the new PAF method, we calculated fractions of cancers causally related to body fatness or both tobacco and alcohol consumption avoidable in the next 10 years by risk factor modifications, comparing them with fractions produced by traditional PAF methods. FINDINGS TO DATE: Over 10 years of follow-up, we observed 27 483 incident cancers and 22 078 deaths. Of cancers related to body fatness (n=9258), 13% (95% CI 11% to 16%) could be avoided if those currently overweight or obese had body mass index of 18.5-24.9 kg/m FUTURE PLANS: We will rank the most important causal factors and their combinations for a spectrum of cancers and inform cancer control activities.

Indexed as

AdolescentAdultAgedAged, 80 and overAlcohol DrinkingAustraliaBody Mass IndexCost of IllnessFemaleHumansLife StyleMaleMiddle AgedNeoplasmsOverweightProspective Studiesburden of diseasecancercohortmodifiable risk factorspoolingpopulation attributable fraction

Identifiers

PMID28615275
PMCPMC5726120

What OpenQuestion holds

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LicenceCC BY-NC
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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.