Evidence map›Paper›PMID 24019751›Full record

ReviewPharmacogenomics and personalized medicine2013

Role of biomarkers in understanding and treating children with asthma: towards personalized care.

Jason E Lang, Kathryn V Blake

Open access · goldAbstract readReview
In one paragraph

Review in Pharmacogenomics and personalized medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. Genetic variants and risk of asthma in an American Indian population.Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology · 2017
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Jason E LangDivision of Pulmonary and Sleep Medicine, Nemours Children's Hospital, Orlando, FL, USA.
Kathryn V Blake
Nemours Children's Clinic · USNemours Children’s Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Asthma is one of the most common chronic diseases affecting children. Despite publicized expert panels on asthma management and the availability of high-potency inhaled corticosteroids, asthma continues to pose an enormous burden on quality of life for children. Research into the genetic and molecular origins of asthma are starting to show how distinct disease entities exist within the syndrome of "asthma". Biomarkers can be used to diagnose underlying molecular mechanisms that can predict the natural course of disease or likely response to drug treatment. The progress of personalized medicine in the care of children with asthma is still in its infancy. We are not yet able to apply stratified asthma treatments based on molecular phenotypes, although that time may be fast approaching. This review discusses some of the recent advances in asthma genetics and the use of current biomarkers that can help guide improved treatment. For example, the fraction of expired nitric oxide and serum Immunoglobulin E (IgE) (including allergen-specific IgE), when evaluated in the context of recurrent asthma symptoms, are general predictors of allergic airway inflammation. Biomarker assays for secondhand tobacco smoke exposure and cysteinyl leukotrienes are both promising areas of study that can help personalize management, not just for pharmacologic management, but also education and prevention efforts.

Indexed as

asthmabiomarkerschildrenmanagement

Identifiers

PMID24019751
PMCPMC3760446
OpenAlexW2067845893

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.