↓ Skip to main content

Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers

Overview of attention for article published in Cancer Epidemiology, Biomarkers & Prevention, September 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
4 tweeters

Readers on

mendeley
17 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers
Published in
Cancer Epidemiology, Biomarkers & Prevention, September 2018
DOI 10.1158/1055-9965.epi-18-0400
Pubmed ID
Authors

Juliet A. Usher-Smith, Stephen J. Sharp, Robert Luben, Simon J. Griffin

Abstract

Most risk models for cancer are either specific to individual cancers or include complex or predominantly non-modifiable risk factors. We developed lifestyle-based models for the five cancers for which the most cases are potentially preventable through lifestyle change in the UK (lung, colorectal, bladder, kidney and oesophageal for men and breast, lung, colorectal, endometrial and kidney for women). We selected lifestyle risk factors from the European Code against Cancer and obtained estimates of relative risks from meta-analyses of observational studies. We used mean values for risk factors from nationally representative samples and mean 10-year estimated absolute risks from routinely available sources. We then assessed the performance of the models in 23,768 participants in the EPIC-Norfolk cohort who had no history of the five selected cancers at baseline. In men the combined risk model showed good discrimination (AUC: 0.71, 95% CI 0.69-0.73) and calibration. Discrimination was lower in women (AUC: 0.59 95% CI 0.57 - 0.61) but calibration was good. In both sexes the individual models for lung cancer had the highest AUCs (0.83, 95%CI 0.80-0.85 for men and 0.82, 95%CI 0.76-0.87 for women). The lowest AUCs were for breast cancer in women and kidney cancer in men. The discrimination and calibration of the models are both reasonable, with the discrimination for individual cancers comparable or better than many other published risk models. These models could be used to demonstrate the potential impact of lifestyle change on risk of cancer to promote behaviour change.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 29%
Unspecified 4 24%
Student > Doctoral Student 2 12%
Student > Ph. D. Student 1 6%
Student > Postgraduate 1 6%
Other 4 24%
Readers by discipline Count As %
Medicine and Dentistry 9 53%
Unspecified 6 35%
Nursing and Health Professions 1 6%
Materials Science 1 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 July 2019.
All research outputs
#7,649,453
of 13,576,937 outputs
Outputs from Cancer Epidemiology, Biomarkers & Prevention
#1,919
of 3,254 outputs
Outputs of similar age
#130,230
of 262,237 outputs
Outputs of similar age from Cancer Epidemiology, Biomarkers & Prevention
#22
of 49 outputs
Altmetric has tracked 13,576,937 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,254 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 262,237 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.