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Predicting Renal Cancer Recurrence: Defining Limitations of Existing Prognostic Models With Prospective Trial-Based Validation.

Overview of attention for article published in Journal of Clinical Oncology, June 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
9 news outlets
twitter
36 X users

Citations

dimensions_citation
84 Dimensions

Readers on

mendeley
52 Mendeley
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Title
Predicting Renal Cancer Recurrence: Defining Limitations of Existing Prognostic Models With Prospective Trial-Based Validation.
Published in
Journal of Clinical Oncology, June 2019
DOI 10.1200/jco.19.00107
Pubmed ID
Authors

Andres F Correa, Opeyemi Jegede, Naomi B Haas, Keith T Flaherty, Michael R Pins, Edward M Messing, Judith Manola, Christopher G Wood, Christopher J Kane, Michael A S Jewett, Janice P Dutcher, Robert S DiPaola, Michael A Carducci, Robert G Uzzo

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 21%
Other 4 8%
Student > Doctoral Student 4 8%
Student > Bachelor 3 6%
Student > Ph. D. Student 3 6%
Other 9 17%
Unknown 18 35%
Readers by discipline Count As %
Medicine and Dentistry 22 42%
Agricultural and Biological Sciences 2 4%
Nursing and Health Professions 2 4%
Computer Science 2 4%
Mathematics 1 2%
Other 5 10%
Unknown 18 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 79. 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 28 April 2022.
All research outputs
#542,346
of 25,385,509 outputs
Outputs from Journal of Clinical Oncology
#1,145
of 22,054 outputs
Outputs of similar age
#11,629
of 367,362 outputs
Outputs of similar age from Journal of Clinical Oncology
#31
of 598 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,054 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.0. This one has done particularly well, scoring higher than 94% 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 367,362 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 96% of its contemporaries.
We're also able to compare this research output to 598 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 94% of its contemporaries.