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Treatable traits in the European U‐ BIOPRED adult asthma cohorts
Author(s) -
Simpson Andrew J.,
Hekking PieterPaul,
Shaw Dominick E.,
Fleming Louise J.,
Roberts Graham,
Riley John H.,
Bates Stewart,
Sousa Ana R.,
Bansal Aruna T.,
Pandis Ioannis,
Sun Kai,
Bakke Per S.,
Caruso Massimo,
Dahlén Barbro,
Dahlén SvenErik,
Horvath Ildiko,
Krug Norbert,
Montuschi Paolo,
Sandstrom Thomas,
Singer Florian,
Adcock Ian M.,
Wagers Scott S.,
Djukanovic Ratko,
Chung Kian Fan,
Sterk Peter J.,
Fowler Stephen J.
Publication year - 2019
Publication title -
allergy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.363
H-Index - 173
eISSN - 1398-9995
pISSN - 0105-4538
DOI - 10.1111/all.13629
Subject(s) - asthma , medicine , immunology , demography , environmental health , sociology
To the Editor, Improvements in asthma outcomes have stalled over the past decade, which may be attributed to treating patients on the basis of a generic diagnostic label. The taxonomy “Treatable Traits” was proposed by Agusti et al (2016) as a precision medicine approach for the diagnosis and management of chronic airway diseases that is based on the identification of genetic, phenotypic and psychosocial characteristics for which therapeutic interventions are known to improve respiratory health. The Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U‐BIOPRED) project was set up to identify multidimensional phenotypes and endotypes in severe asthma. Here, we aim to identify and quantify treatable traits within the severe and mild/moderate U‐BIOPRED adult asthma cohorts and across previously identified phenotypes. We hypothesize that treatable traits will be more common in severe asthma and vary significantly across asthma phenotypes. Data from the severe asthma and mild/moderate asthma cohorts of the U‐BIOPRED project were included in this study. Full details of the study population and methodology have been presented elsewhere. Criteria for treatable traits were based on Agusti et al and presented in Table 1. Chi‐squared tests were used to examine differences in the prevalence of each treatable trait between groups and independent sample t tests used to determine differences in the total number of traits between cohorts. No adjustment for multiple testing was applied as the analyses were considered exploratory; as this may inflate the type‐1 error rate, individual P values are presented for each comparison. A post hoc power calculation shows our sample of 421 (severe smoking/ex‐smoking vs severe nonsmoking) and 399 (severe nonsmoking vs mild/moderate) is sufficient to identify a difference in treatable trait prevalence between cohorts with a medium effect size (0.3) and a power close to 1.00. Data analysis was supported by IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY, USA, with significance set at P < 0.05, unless otherwise stated.