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A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study

Overview of attention for article published in Lancet Oncology, December 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
13 news outlets
blogs
3 blogs
twitter
166 X users
patent
8 patents
facebook
1 Facebook page
wikipedia
3 Wikipedia pages

Citations

dimensions_citation
370 Dimensions

Readers on

mendeley
340 Mendeley
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Title
A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study
Published in
Lancet Oncology, December 2016
DOI 10.1016/s1470-2045(16)30648-9
Pubmed ID
Authors

Jacob G Scott, Anders Berglund, Michael J Schell, Ivaylo Mihaylov, William J Fulp, Binglin Yue, Eric Welsh, Jimmy J Caudell, Kamran Ahmed, Tobin S Strom, Eric Mellon, Puja Venkat, Peter Johnstone, John Foekens, Jae Lee, Eduardo Moros, William S Dalton, Steven A Eschrich, Howard McLeod, Louis B Harrison, Javier F Torres-Roca

Abstract

Despite its common use in cancer treatment, radiotherapy has not yet entered the era of precision medicine, and there have been no approaches to adjust dose based on biological differences between or within tumours. We aimed to assess whether a patient-specific molecular signature of radiation sensitivity could be used to identify the optimum radiotherapy dose. We used the gene expression-based radiation-sensitivity index and the linear quadratic model to derive the genomic-adjusted radiation dose (GARD). A high GARD value predicts for high therapeutic effect for radiotherapy; which we postulate would relate to clinical outcome. Using data from the prospective, observational Total Cancer Care (TCC) protocol, we calculated GARD for primary tumours from 20 disease sites treated using standard radiotherapy doses for each disease type. We also used multivariable Cox modelling to assess whether GARD was independently associated with clinical outcome in five clinical cohorts: Erasmus Breast Cancer Cohort (n=263); Karolinska Breast Cancer Cohort (n=77); Moffitt Lung Cancer Cohort (n=60); Moffitt Pancreas Cancer Cohort (n=40); and The Cancer Genome Atlas Glioblastoma Patient Cohort (n=98). We calculated GARD for 8271 tissue samples from the TCC cohort. There was a wide range of GARD values (range 1·66-172·4) across the TCC cohort despite assignment of uniform radiotherapy doses within disease types. Median GARD values were lowest for gliomas and sarcomas and highest for cervical cancer and oropharyngeal head and neck cancer. There was a wide range of GARD values within tumour type groups. GARD independently predicted clinical outcome in breast cancer, lung cancer, glioblastoma, and pancreatic cancer. In the Erasmus Breast Cancer Cohort, 5-year distant-metastasis-free survival was longer in patients with high GARD values than in those with low GARD values (hazard ratio 2·11, 95% 1·13-3·94, p=0·018). A GARD-based clinical model could allow the individualisation of radiotherapy dose to tumour radiosensitivity and could provide a framework to design genomically-guided clinical trials in radiation oncology. None.

X Demographics

X Demographics

The data shown below were collected from the profiles of 166 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 340 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Canada 1 <1%
Unknown 337 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 58 17%
Researcher 54 16%
Other 34 10%
Student > Master 33 10%
Student > Doctoral Student 18 5%
Other 70 21%
Unknown 73 21%
Readers by discipline Count As %
Medicine and Dentistry 131 39%
Biochemistry, Genetics and Molecular Biology 27 8%
Physics and Astronomy 21 6%
Agricultural and Biological Sciences 15 4%
Engineering 11 3%
Other 36 11%
Unknown 99 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 217. 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 13 February 2024.
All research outputs
#181,068
of 25,724,500 outputs
Outputs from Lancet Oncology
#199
of 6,937 outputs
Outputs of similar age
#3,765
of 424,720 outputs
Outputs of similar age from Lancet Oncology
#6
of 128 outputs
Altmetric has tracked 25,724,500 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,937 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.2. This one has done particularly well, scoring higher than 97% 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 424,720 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 128 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 95% of its contemporaries.