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Current concepts in targeting chronic obstructive pulmonary disease pharmacotherapy: making progress towards personalised management

Overview of attention for article published in The Lancet, May 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

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29 X users
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6 Facebook pages

Citations

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218 Dimensions

Readers on

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227 Mendeley
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1 CiteULike
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Title
Current concepts in targeting chronic obstructive pulmonary disease pharmacotherapy: making progress towards personalised management
Published in
The Lancet, May 2015
DOI 10.1016/s0140-6736(15)60693-6
Pubmed ID
Authors

Prescott G Woodruff, Alvar Agusti, Nicolas Roche, Dave Singh, Fernando J Martinez

Abstract

Chronic obstructive pulmonary disease (COPD) is a common, complex, and heterogeneous disorder that is responsible for substantial and growing morbidity, mortality, and health-care expense worldwide. Of imperative importance to decipher the complexity of COPD is to identify groups of patients with similar clinical characteristics, prognosis, or therapeutic needs, the so-called clinical phenotypes. This strategy is logical for research but might be of little clinical value because clinical phenotypes can overlap in the same patient and the same clinical phenotype could result from different biological mechanisms. With the goal to match assessment with treatment choices, the latest iteration of guidelines from the Global Initiative for Chronic Obstructive Lung Disease reorganised treatment objectives into two categories: to improve symptoms (ie, dyspnoea and health status) and to decrease future risk (as predicted by forced expiratory volume in 1 s level and exacerbations history). This change thus moves treatment closer to individualised medicine with available bronchodilators and anti-inflammatory drugs. Yet, future treatment options are likely to include targeting endotypes that represent subtypes of patients defined by a distinct pathophysiological mechanism. Specific biomarkers of these endotypes would be particularly useful in clinical practice, especially in patients in which clinical phenotype alone is insufficient to identify the underlying endotype. A few series of potential COPD endotypes and biomarkers have been suggested. Empirical knowledge will be gained from proof-of-concept trials in COPD with emerging drugs that target specific inflammatory pathways. In every instance, specific endotype and biomarker efforts will probably be needed for the success of these trials, because the pathways are likely to be operative in only a subset of patients. Network analysis of human diseases offers the possibility to improve understanding of disease pathobiological complexity and to help with the development of new treatment alternatives and, importantly, a reclassification of complex diseases. All these developments should pave the way towards personalised treatment of patients with COPD in the clinic.

X Demographics

X Demographics

The data shown below were collected from the profiles of 29 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 227 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 1%
United States 2 <1%
South Africa 1 <1%
Spain 1 <1%
Denmark 1 <1%
Unknown 219 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 15%
Other 30 13%
Student > Master 27 12%
Student > Bachelor 20 9%
Student > Ph. D. Student 18 8%
Other 59 26%
Unknown 40 18%
Readers by discipline Count As %
Medicine and Dentistry 97 43%
Agricultural and Biological Sciences 17 7%
Biochemistry, Genetics and Molecular Biology 11 5%
Pharmacology, Toxicology and Pharmaceutical Science 11 5%
Nursing and Health Professions 9 4%
Other 27 12%
Unknown 55 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 12 July 2016.
All research outputs
#1,964,708
of 25,641,627 outputs
Outputs from The Lancet
#12,342
of 42,873 outputs
Outputs of similar age
#24,234
of 279,507 outputs
Outputs of similar age from The Lancet
#200
of 454 outputs
Altmetric has tracked 25,641,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 42,873 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 68.0. This one has gotten more attention than average, scoring higher than 71% 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 279,507 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 91% of its contemporaries.
We're also able to compare this research output to 454 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.