Show simple item record

dc.contributor.authorUsher-Smith, Julieten
dc.contributor.authorEmery, Jonen
dc.contributor.authorHamilton, Willieen
dc.contributor.authorGriffin, Simonen
dc.contributor.authorWalter, Fionaen
dc.date.accessioned2015-10-28T15:28:38Z
dc.date.available2015-10-28T15:28:38Z
dc.date.issued2015-12-03en
dc.identifier.citationBritish Journal of Cancer 2015, 113: 1645–1650. doi:10.1038/bjc.2015.409en
dc.identifier.issn0007-0920
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/252443
dc.description.abstractNumerous risk tools are now available which predict either current or future risk of a cancer diagnosis. In theory these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an “area of extraordinary opportunity” and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalization, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the under lying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed.
dc.languageEnglishen
dc.language.isoenen
dc.publisherNature Publishing Group
dc.rightsCreative Commons Attribution 4.0 International License
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectprimary careen
dc.subjectcanceren
dc.subjectrisken
dc.subjectpredictionen
dc.subjectmodelen
dc.subjectdiagnosisen
dc.subjectscreeningen
dc.titleRisk Prediction Tools for Cancer in Primary Careen
dc.typeArticle
dc.description.versionThis is the final version of the article. It was first available from NPG via http://dx.doi.org/10.1038/bjc.2015.409en
prism.endingPage1650
prism.publicationDate2015en
prism.publicationNameBritish Journal of Canceren
prism.startingPage1645
prism.volume113en
dcterms.dateAccepted2015-10-26en
rioxxterms.versionofrecord10.1038/bjc.2015.409en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2015-12-03en
dc.contributor.orcidUsher-Smith, Juliet [0000-0002-8501-2531]
dc.contributor.orcidGriffin, Simon [0000-0002-2157-4797]
dc.contributor.orcidWalter, Fiona [0000-0002-7191-6476]
dc.identifier.eissn1532-1827
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idMRC (MC_UU_12015/4)
pubs.funder-project-idMedical Research Council (MC_U106179474)


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Creative Commons Attribution 4.0 International License
Except where otherwise noted, this item's licence is described as Creative Commons Attribution 4.0 International License