Evidence map›Paper›PMID 27547696›Full record

ArticleCurrent epidemiology reports2016

Population Attributable and Preventable Fractions: Cancer Risk Factor Surveillance, and Cancer Policy Projection.

Kevin D Shield, D Maxwell Parkin, David C Whiteman, Jürgen Rehm, Vivian Viallon, Claire Marant Micallef, Paolo Vineis, Lesley Rushton, Freddie Bray, Isabelle Soerjomataram

Abstract read
In one paragraph

Article in Current epidemiology reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 4 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

34 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

10 authors.

Kevin D ShieldSection of Cancer Surveillance, International Agency for Research on Cancer, Lyon, France.
D Maxwell ParkinCentre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, United Kingdom.
David C WhitemanPopulation Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Jürgen RehmSocial and Epidemiological Research Department, Centre for Addiction and Mental Health, Toronto, Canada.
Vivian ViallonUniversité de Lyon, Université Lyon 1, UMRESTTE IFSTTAR, UMRESTTE, Lyon, France.
Claire Marant MicallefSection of Cancer Surveillance, International Agency for Research on Cancer, Lyon, France.
Paolo VineisHuGeF Foundation, Torino, Italy; MRC-PHE Center for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
Lesley RushtonFaculty of Medicine, School of Public Health, Imperial College of London, London, United Kingdom.
Freddie BraySection of Cancer Surveillance, International Agency for Research on Cancer, Lyon, France.
Isabelle SoerjomataramSection of Cancer Surveillance, International Agency for Research on Cancer, Lyon, France.

Funding

ENHANCING GLOBAL CANCER SURVEILLANCE THROUGH REGIONAL HUBS FOR CANCER REGISTRATIOU58DP004954 · DP · INTERNATIONAL AGENCY FOR RES ON CANCER · PI BRAY, FREDDIE · 2013 to 2015
$528k
NCCDPHP CDC HHS U58 DP004954World Health Organization 001
6 · The paper itself

Abstract

The proportions of new cancer cases and deaths that are caused by exposure to risk factors and that could be prevented are key statistics for public health policy and planning. This paper summarizes the methodologies for estimating, challenges in the analysis of, and utility of, population attributable and preventable fractions for cancers caused by major risk factors such as tobacco smoking, dietary factors, high body fat, physical inactivity, alcohol consumption, infectious agents, occupational exposure, air pollution, sun exposure, and insufficient breastfeeding. For population attributable and preventable fractions, evidence of a causal relationship between a risk factor and cancer, outcome (such as incidence and mortality), exposure distribution, relative risk, theoretical-minimum-risk, and counterfactual scenarios need to be clearly defined and congruent. Despite limitations of the methodology and the data used for estimations, the population attributable and preventable fractions are a useful tool for public health policy and planning.

Indexed as

EtiologyIncidenceMortalityNeoplasmsPopulation Attributable FractionPrevention and controlRisk

Identifiers

PMID27547696
PMCPMC4990141

What OpenQuestion holds

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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.