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Treatment Algorithms for Patients with Metastatic Non-Small Cell, Non-Squamous Lung Cancer

Overview of attention for article published in Frontiers in oncology, September 2014
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Title
Treatment Algorithms for Patients with Metastatic Non-Small Cell, Non-Squamous Lung Cancer
Published in
Frontiers in oncology, September 2014
DOI 10.3389/fonc.2014.00256
Pubmed ID
Authors

Barbara Melosky

Abstract

A number of developments have altered the treatment paradigm for metastatic non-small cell, non-squamous lung cancer. These include increasing knowledge of molecular signal pathways, as well as the outcomes of several large-scale trials. As a result, treatments are becoming more efficacious and more personalized, and are changing the management and prognosis of non-small cell lung cancer patients. This is resulting in increased survival in select patient groups. In this paper, a simplified algorithm for treating patients with metastatic non-small cell, non-squamous lung cancer is presented.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

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 %
Germany 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Other 5 29%
Researcher 5 29%
Student > Postgraduate 2 12%
Student > Ph. D. Student 1 6%
Student > Master 1 6%
Other 1 6%
Unknown 2 12%
Readers by discipline Count As %
Medicine and Dentistry 7 41%
Biochemistry, Genetics and Molecular Biology 3 18%
Agricultural and Biological Sciences 2 12%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Social Sciences 1 6%
Other 1 6%
Unknown 2 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 September 2014.
All research outputs
#20,656,161
of 25,374,647 outputs
Outputs from Frontiers in oncology
#11,313
of 22,416 outputs
Outputs of similar age
#193,481
of 264,231 outputs
Outputs of similar age from Frontiers in oncology
#48
of 89 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 28th percentile – i.e., 28% 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 264,231 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.