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External validation of risk prediction models for incident colorectal cancer using UK Biobank

Overview of attention for article published in British Journal of Cancer, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
24 tweeters

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
36 Mendeley
Title
External validation of risk prediction models for incident colorectal cancer using UK Biobank
Published in
British Journal of Cancer, January 2018
DOI 10.1038/bjc.2017.463
Pubmed ID
Authors

J A Usher-Smith, A Harshfield, C L Saunders, S J Sharp, J Emery, F M Walter, K Muir, S J Griffin

Abstract

This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries. There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals. Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.British Journal of Cancer advance online publication, 30 January 2018; doi:10.1038/bjc.2017.463 www.bjcancer.com.

Twitter Demographics

The data shown below were collected from the profiles of 24 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 22%
Unspecified 7 19%
Researcher 7 19%
Student > Master 6 17%
Student > Bachelor 5 14%
Other 3 8%
Readers by discipline Count As %
Medicine and Dentistry 12 33%
Unspecified 10 28%
Engineering 2 6%
Biochemistry, Genetics and Molecular Biology 2 6%
Neuroscience 2 6%
Other 8 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 May 2018.
All research outputs
#1,081,126
of 13,324,694 outputs
Outputs from British Journal of Cancer
#718
of 8,098 outputs
Outputs of similar age
#43,764
of 348,131 outputs
Outputs of similar age from British Journal of Cancer
#12
of 131 outputs
Altmetric has tracked 13,324,694 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,098 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 348,131 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 131 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.