Evidence map›Paper›PMID 28559460›Full record

ArticleCancer prevention research (Philadelphia, Pa.)2017

Development of a Cancer Risk Prediction Tool for Use in the UK Primary Care and Community Settings.

Artitaya Lophatananon, Juliet Usher-Smith, Jackie Campbell, Joanne Warcaba, Barbora Silarova, Erika A Waters, Graham A Colditz, Kenneth R Muir

Abstract readComparative Study
In one paragraph

Article in Cancer prevention research (Philadelphia, Pa.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Commentary: 20 years online with "Your Disease Risk".Cancer causes & control : CCC · 2021
    Article
  4. Article
  5. 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

8 authors.

Artitaya LophatananonDivision of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom. artitaya.lophatananon@manchester.ac.uk.
Juliet Usher-SmithThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Jackie CampbellInstitute of Health and Wellbeing, The University of Northampton, Northampton, United Kingdom.
Joanne WarcabaMoulton Surgery, Northampton Lane, Northampton, United Kingdom.
Barbora SilarovaMRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
Erika A WatersDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri.
Graham A ColditzDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri.
Kenneth R MuirDivision of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.

Funding

COMMUNICATING MULTIPLE DISEASE RISKS: A TRANSLATION OF RISK PREDICTION SCIENCER01CA190391 · NCI · WASHINGTON UNIVERSITY · PI WATERS, ERIKA A · 2015 to 2018
$1.4M
Cancer Research UK 19169Cancer Research UK 20818Cancer Research UK A19169Cancer Research UK A20818Medical Research Council MC_QA137853Medical Research Council MC_UU_12015/4NCI NIH HHS R01 CA190391
6 · The paper itself

Abstract

Several multivariable risk prediction models have been developed to asses an individual's risk of developing specific cancers. Such models can be used in a variety of settings for prevention, screening, and guiding investigations and treatments. Models aimed at predicting future disease risk that contains lifestyle factors may be of particular use for targeting health promotion activities at an individual level. This type of cancer risk prediction is not yet available in the UK. We have adopted the approach used by the well-established U.S.-derived "YourCancerRisk" model for use in the UK population, which allow users to quantify their individual risk of developing individual cancers relative to the population average risk. The UK version of "YourCancerRisk" computes 10-year cancer risk estimates for 11 cancers utilizing UK figures for prevalence of risk factors and cancer incidence. Because the prevalence of risk factors and the incidence rates for cancer are different between the U.S. and the UK population, this UK model provides more accurate estimates of risks for a UK population. Using an example of breast cancer and data from UK Biobank cohort, we demonstrate that the individual risk factor estimates are similar for the U.S. and UK populations. Assessment of the performance and validation of the multivariate model predictions based on a binary score confirm the model's applicability. The model can be used to estimate absolute and relative cancer risk for use in Primary Care and community settings and is being used in the community to guide lifestyle change.

Indexed as

Models, StatisticalAdolescentAdultAgedAged, 80 and overBreast NeoplasmsChildCohort StudiesFemaleHealth PromotionHumansIncidenceMaleMiddle AgedNeoplasmsPrevalence

Identifiers

PMID28559460
PMCPMC5501968

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.