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Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink)
BACKGROUND: Distinct asthma phenotypes have previously been suggested, including benign asthma, atopic asthma and obese non-eosinophilic asthma. This study aims to establish if these phenotypes can be identified using data recorded in primary care clinical records and reports on patient characterist...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329349/ https://www.ncbi.nlm.nih.gov/pubmed/30662273 http://dx.doi.org/10.2147/JAA.S182013 |
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author | Nissen, Francis Douglas, Ian J Müllerová, Hana Pearce, Neil Bloom, Chloe I Smeeth, Liam Quint, Jennifer K |
author_facet | Nissen, Francis Douglas, Ian J Müllerová, Hana Pearce, Neil Bloom, Chloe I Smeeth, Liam Quint, Jennifer K |
author_sort | Nissen, Francis |
collection | PubMed |
description | BACKGROUND: Distinct asthma phenotypes have previously been suggested, including benign asthma, atopic asthma and obese non-eosinophilic asthma. This study aims to establish if these phenotypes can be identified using data recorded in primary care clinical records and reports on patient characteristics and exacerbation frequency. METHODS: A population-based cohort study identified 193,999 asthma patients in UK primary care from 2007 to 2017. We used linked primary and secondary care data from the Clinical Practice Research Datalink, Hospital Episode Statistics and Office for National Statistics. Patients were classified into predefined phenotypes or included in an asthma “not otherwise specified” (NOS) group. We used negative binomial regression to calculate the exacerbation rates and adjusted rate ratios. Rate ratios were further stratified by asthma treatment step. RESULTS: In our cohort, 3.9% of patients were categorized as benign asthma, 28.6% atopic asthma and 4.8% obese non-eosinophilic asthma. About 62.7% of patients were asthma NOS, including asthma NOS without treatment (10.4%), only on short-acting beta agonist (6.1%) and on maintenance treatment (46.2%). Crude severe exacerbation rates per 1,000 person-years were lowest for benign asthma (106.8 [95% CI: 101.2–112.3]) and highest for obese non-eosinophilic asthma (469.0 [451.7–486.2]). Incidence rate ratios for all phenotype groups decreased when stratified by treatment step but remained raised compared to benign asthma. CONCLUSION: Established phenotypes can be identified in a general asthma population, although many patients did not fit into the specific phenotypes which we studied. Phenotyping patients and knowledge of asthma treatment step could help anticipate clinical course and therefore could aid clinical management but is only possible in a minority of primary care patients based on current phenotypes and electronic health records (EHRs). |
format | Online Article Text |
id | pubmed-6329349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63293492019-01-18 Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink) Nissen, Francis Douglas, Ian J Müllerová, Hana Pearce, Neil Bloom, Chloe I Smeeth, Liam Quint, Jennifer K J Asthma Allergy Original Research BACKGROUND: Distinct asthma phenotypes have previously been suggested, including benign asthma, atopic asthma and obese non-eosinophilic asthma. This study aims to establish if these phenotypes can be identified using data recorded in primary care clinical records and reports on patient characteristics and exacerbation frequency. METHODS: A population-based cohort study identified 193,999 asthma patients in UK primary care from 2007 to 2017. We used linked primary and secondary care data from the Clinical Practice Research Datalink, Hospital Episode Statistics and Office for National Statistics. Patients were classified into predefined phenotypes or included in an asthma “not otherwise specified” (NOS) group. We used negative binomial regression to calculate the exacerbation rates and adjusted rate ratios. Rate ratios were further stratified by asthma treatment step. RESULTS: In our cohort, 3.9% of patients were categorized as benign asthma, 28.6% atopic asthma and 4.8% obese non-eosinophilic asthma. About 62.7% of patients were asthma NOS, including asthma NOS without treatment (10.4%), only on short-acting beta agonist (6.1%) and on maintenance treatment (46.2%). Crude severe exacerbation rates per 1,000 person-years were lowest for benign asthma (106.8 [95% CI: 101.2–112.3]) and highest for obese non-eosinophilic asthma (469.0 [451.7–486.2]). Incidence rate ratios for all phenotype groups decreased when stratified by treatment step but remained raised compared to benign asthma. CONCLUSION: Established phenotypes can be identified in a general asthma population, although many patients did not fit into the specific phenotypes which we studied. Phenotyping patients and knowledge of asthma treatment step could help anticipate clinical course and therefore could aid clinical management but is only possible in a minority of primary care patients based on current phenotypes and electronic health records (EHRs). Dove Medical Press 2019-01-08 /pmc/articles/PMC6329349/ /pubmed/30662273 http://dx.doi.org/10.2147/JAA.S182013 Text en © 2019 Nissen et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Nissen, Francis Douglas, Ian J Müllerová, Hana Pearce, Neil Bloom, Chloe I Smeeth, Liam Quint, Jennifer K Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink) |
title | Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink) |
title_full | Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink) |
title_fullStr | Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink) |
title_full_unstemmed | Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink) |
title_short | Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink) |
title_sort | clinical profile of predefined asthma phenotypes in a large cohort of uk primary care patients (clinical practice research datalink) |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329349/ https://www.ncbi.nlm.nih.gov/pubmed/30662273 http://dx.doi.org/10.2147/JAA.S182013 |
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