| Title |
Predictive Biomarkers for Asthma Therapy
|
|---|---|
| Published in |
Current Allergy and Asthma Reports, September 2017
|
| DOI | 10.1007/s11882-017-0739-5 |
| Pubmed ID | |
| Authors |
Sarah K. Medrek, Amit D. Parulekar, Nicola A. Hanania |
| Abstract |
Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 68 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 10 | 15% |
| Researcher | 7 | 10% |
| Other | 6 | 9% |
| Student > Doctoral Student | 5 | 7% |
| Student > Ph. D. Student | 5 | 7% |
| Other | 14 | 21% |
| Unknown | 21 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 29 | 43% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Agricultural and Biological Sciences | 2 | 3% |
| Computer Science | 2 | 3% |
| Other | 7 | 10% |
| Unknown | 21 | 31% |
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 16 November 2018.
All research outputs
#15,492,327
of 23,023,224 outputs
Outputs from Current Allergy and Asthma Reports
#566
of 808 outputs
Outputs of similar age
#199,649
of 318,256 outputs
Outputs of similar age from Current Allergy and Asthma Reports
#9
of 13 outputs
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