ArticleClinical and translational allergy2019
Comparison of hypothesis- and data-driven asthma phenotypes in NHANES 2007-2012: the importance of comprehensive data availability.
Article in Clinical and translational allergy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- On the translational potential of atlases in precision oncology.Translational cancer research · 2025Review
- Article
- Risk factors for depression in asthmatic individuals: Findings from NHANES (2005-2018).PloS one · 2023Article
- Comparison of Pulmonary Function and Inflammation in Children/Adolescents with New-Onset Asthma with Different Adiposity Statuses.Nutrients · 2022Article
- A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods.Diagnostics (Basel, Switzerland) · 2021Review
- Highlights and recent developments in allergic diseases in EAACI journals (2019).Clinical and translational allergy · 2020Review
- Longitudinal Asthma Patterns in Italian Adult General Population Samples: Host and Environmental Risk Factors.Journal of clinical medicine · 2020Article
- Comparisons Between Hypothesis- and Data-Driven Approaches for Multimorbidity Frailty Index: A Machine Learning Approach.Journal of medical Internet research · 2020Article
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Authors and funding
7 authors.
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Abstract
backgroundHalf 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.
aimTo 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.
methodsAdults (≥ 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.
resultsTwo 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 (
conclusionBoth 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.
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