Comparison of hypothesis- and data-driven asthma phenotypes in NHANES 2007-2012: the importance of comprehensive data availability.
Asthma
Phenotypes
Population-based study
Unsupervised analysis
Journal
Clinical and translational allergy
ISSN: 2045-7022
Titre abrégé: Clin Transl Allergy
Pays: England
ID NLM: 101576043
Informations de publication
Date de publication:
2019
2019
Historique:
received:
04
01
2019
accepted:
01
03
2019
entrez:
29
3
2019
pubmed:
29
3
2019
medline:
29
3
2019
Statut:
epublish
Résumé
Half of the adults with current asthma among the US National Health and Nutrition Examination Survey (NHANES) participants could be classified in more than one hypothesis-driven phenotype. A data-driven approach applied to the same subjects may allow a more useful classification compared to the hypothesis-driven one. To compare previously defined hypothesis-driven with newly derived data-driven asthma phenotypes, identified by latent class analysis (LCA), in adults with current asthma from NHANES 2007-2012. Adults (≥ 18 years) with current asthma from the NHANES were included (n = 1059). LCA included variables commonly used to subdivide asthma. LCA models were derived independently according to age groups: < 40 and ≥ 40 years old. Two data-driven phenotypes were identified among adults with current asthma, for both age groups. The proportions of the hypothesis-driven phenotypes were similar among the two data-driven phenotypes (p > 0.05). Class A < 40 years ( Both data- and hypothesis-driven approaches using clinical and physiological variables commonly used to characterize asthma are suboptimal to identify asthma phenotypes among adults from the general population. Further studies based on more comprehensive disease features are required to identify asthma phenotypes in population-based studies.
Sections du résumé
BACKGROUND
BACKGROUND
Half of the adults with current asthma among the US National Health and Nutrition Examination Survey (NHANES) participants could be classified in more than one hypothesis-driven phenotype. A data-driven approach applied to the same subjects may allow a more useful classification compared to the hypothesis-driven one.
AIM
OBJECTIVE
To compare previously defined hypothesis-driven with newly derived data-driven asthma phenotypes, identified by latent class analysis (LCA), in adults with current asthma from NHANES 2007-2012.
METHODS
METHODS
Adults (≥ 18 years) with current asthma from the NHANES were included (n = 1059). LCA included variables commonly used to subdivide asthma. LCA models were derived independently according to age groups: < 40 and ≥ 40 years old.
RESULTS
RESULTS
Two data-driven phenotypes were identified among adults with current asthma, for both age groups. The proportions of the hypothesis-driven phenotypes were similar among the two data-driven phenotypes (p > 0.05). Class A < 40 years (
CONCLUSION
CONCLUSIONS
Both data- and hypothesis-driven approaches using clinical and physiological variables commonly used to characterize asthma are suboptimal to identify asthma phenotypes among adults from the general population. Further studies based on more comprehensive disease features are required to identify asthma phenotypes in population-based studies.
Identifiants
pubmed: 30918624
doi: 10.1186/s13601-019-0258-7
pii: 258
pmc: PMC6419396
doi:
Types de publication
Journal Article
Langues
eng
Pagination
17Déclaration de conflit d'intérêts
The authors declare that they have no competing interests.
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