65
IRUS Total
Downloads
  Altmetric

Does understanding endotypes translate to better asthma management options for all?

File Description SizeFormat 
JACI Rostrum clean Endnote removed.docxAccepted version52.14 kBMicrosoft WordView/Open
Fig_01.pdfSupporting information71.2 kBAdobe PDFView/Open
Fig_02.pngSupporting information94.62 kBimage/pngView/Open
Fig_03.pdfSupporting information134.92 kBAdobe PDFView/Open
Fig_04.pdfSupporting information108.13 kBAdobe PDFView/Open
Fig_05.pdfSupporting information131.02 kBAdobe PDFView/Open
Title: Does understanding endotypes translate to better asthma management options for all?
Authors: Custovic, A
Henderson, J
Simpson, A
Item Type: Journal Article
Abstract: Despite the development of novel treatments, improvement in the design of delivery devices, and new technologies for monitoring and improving adherence, the burden of asthma is not decreasing. Predicting an individual patient's response to asthma drugs remains challenging, and the provision of personalized treatment remains elusive. Although biomarkers, such as allergic sensitization and blood eosinophilia, might be important predictors of response to inhaled corticosteroids in preschool children, these relatively cheap and available investigations are seldom used in clinical practice to select patients for corticosteroid prescription. However, for the majority of patients, response to different treatments cannot be accurately predicted. One of the key factors preventing further advances is the reductionist view of asthma as a single disease, which is forcing patients with different asthma subtypes into a single group for empiric treatment. This inevitably results in treatment failures and, for some, an unacceptable risk/benefit ratio. The approach to asthma today is an example of the traditional symptom (diagnosis)-based, one-size-fits-all approach rather than a stratified approach, and our guidelines-driven management based on a unitary diagnosis might not be the optimal way to deliver care. The only way to deliver stratified medicine and find a cure is through the understanding of asthma endotypes. We propose that the way to discover endotypes, biomarkers, and personalized treatments is through the iterative process based on interpretation of big data analytics from birth and patient cohorts, responses to treatments in randomized controlled trials, and in vitro mechanistic studies using human samples and experimental animal models, with technological and methodological advances at its core.
Issue Date: 1-Jul-2019
Date of Acceptance: 21-May-2019
URI: http://hdl.handle.net/10044/1/72261
DOI: https://dx.doi.org/10.1016/j.jaci.2019.05.016
ISSN: 0091-6749
Publisher: Elsevier
Start Page: 25
End Page: 33
Journal / Book Title: Journal of Allergy and Clinical Immunology
Volume: 144
Issue: 1
Copyright Statement: © 2019 American Academy of Allergy, Asthma & Immunology. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor/Funder: Medical Research Council (MRC)
Funder's Grant Number: MR/K002449/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Allergy
Immunology
Asthma
childhood
endotypes
data driven
cohorts
integration
team science
IGE RESPONSES
DOUBLE-BLIND
CHILDREN
THERAPY
CLASSIFICATION
FLUTICASONE
MONTELUKAST
SYMPTOMS
INFANTS
Asthma
childhood
cohorts
data driven
endotypes
integration
team science
Asthma
childhood
cohorts
data driven
endotypes
integration
team science
Allergy
1107 Immunology
Publication Status: Published
Conference Place: United States
Online Publication Date: 2019-05-27
Appears in Collections:National Heart and Lung Institute