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Cell-free circulating tumor DNA in cancer

Overview of attention for article published in Ai zheng Aizheng Chinese journal of cancer, April 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#33 of 248)
  • Good Attention Score compared to outputs of the same age (78th percentile)

Mentioned by

twitter
3 tweeters
patent
1 patent
wikipedia
3 Wikipedia pages

Citations

dimensions_citation
118 Dimensions

Readers on

mendeley
281 Mendeley
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Title
Cell-free circulating tumor DNA in cancer
Published in
Ai zheng Aizheng Chinese journal of cancer, April 2016
DOI 10.1186/s40880-016-0092-4
Pubmed ID
Authors

Zhen Qin, Vladimir A. Ljubimov, Cuiqi Zhou, Yunguang Tong, Jimin Liang

Abstract

Cancer is a common cause of death worldwide. Despite significant advances in cancer treatments, the morbidity and mortality are still enormous. Tumor heterogeneity, especially intratumoral heterogeneity, is a significant reason underlying difficulties in tumor treatment and failure of a number of current therapeutic modalities, even of molecularly targeted therapies. The development of a virtually noninvasive "liquid biopsy" from the blood has been attempted to characterize tumor heterogeneity. This review focuses on cell-free circulating tumor DNA (ctDNA) in the bloodstream as a versatile biomarker. ctDNA analysis is an evolving field with many new methods being developed and optimized to be able to successfully extract and analyze ctDNA, which has vast clinical applications. ctDNA has the potential to accurately genotype the tumor and identify personalized genetic and epigenetic alterations of the entire tumor. In addition, ctDNA has the potential to accurately monitor tumor burden and treatment response, while also being able to monitor minimal residual disease, reducing the need for harmful adjuvant chemotherapy and allowing more rapid detection of relapse. There are still many challenges that need to be overcome prior to this biomarker getting wide adoption in the clinical world, including optimization, standardization, and large multicenter trials.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 281 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Turkey 1 <1%
Sweden 1 <1%
Russia 1 <1%
Ireland 1 <1%
Unknown 277 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 52 19%
Student > Bachelor 49 17%
Student > Ph. D. Student 41 15%
Student > Master 38 14%
Other 25 9%
Other 35 12%
Unknown 41 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 78 28%
Medicine and Dentistry 52 19%
Agricultural and Biological Sciences 46 16%
Engineering 12 4%
Pharmacology, Toxicology and Pharmaceutical Science 10 4%
Other 30 11%
Unknown 53 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 17 February 2021.
All research outputs
#3,603,782
of 20,303,071 outputs
Outputs from Ai zheng Aizheng Chinese journal of cancer
#33
of 248 outputs
Outputs of similar age
#59,321
of 277,711 outputs
Outputs of similar age from Ai zheng Aizheng Chinese journal of cancer
#1
of 1 outputs
Altmetric has tracked 20,303,071 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 248 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 86% 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 277,711 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 78% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them