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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, August 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 (88th percentile)

Mentioned by

news
6 news outlets
twitter
37 tweeters

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
11 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, August 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

Twitter Demographics

The data shown below were collected from the profiles of 37 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 18%
Researcher 2 18%
Student > Master 1 9%
Other 1 9%
Librarian 1 9%
Other 1 9%
Unknown 3 27%
Readers by discipline Count As %
Medicine and Dentistry 5 45%
Nursing and Health Professions 1 9%
Biochemistry, Genetics and Molecular Biology 1 9%
Unknown 4 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 61. 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 05 December 2019.
All research outputs
#301,804
of 13,995,463 outputs
Outputs from Journal of Clinical Oncology
#772
of 13,790 outputs
Outputs of similar age
#10,056
of 255,072 outputs
Outputs of similar age from Journal of Clinical Oncology
#34
of 307 outputs
Altmetric has tracked 13,995,463 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 13,790 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.5. 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 255,072 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 307 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.