ArticleClinical and translational allergy2022
How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers?
Article in Clinical and translational allergy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06163807 (Follow-up of Spanish Prospective Asthma and Nasal Polyposis Registry), which is not on this map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Follow-up of Spanish Prospective Asthma and Nasal Polyposis Registry
Who cites it
4 citing papers in PubMed.
- Beyond biomarkers: the role of clinical factors associated with biologic therapy response in severe asthma.Annals of medicine · 2026Observational
- Green Light for Response: Clinical Stratification of Response to Biologic Therapy in Severe Asthma.Journal of asthma and allergy · 2026Article
- Asthma Inflammatory Phenotypes: How Can We Distinguish Them?Journal of clinical medicine · 2024Article
- How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers?Clinical and translational allergy · 2022Article
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Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: Asthma is a heterogeneous respiratory disease that encompasses different inflammatory and functional endophenotypes. Many non-invasive biomarkers has been investigated to its pathobiology. Heany et al proposed a clinical algorithm that classifies severe asthmatic patients into likely-eosinophilic phenotypes, based on accessible biomarkers: PBE, current treatment, FeNO, presence of nasal polyps (NP) and age of onset. Materials and Methods: We assessed the concordance between the algorithm proposed by Heany et al. with sputum examination, the gold standard, in 145 asthmatic patients of the MEGA cohort with varying grades of severity. Results: No correlation was found between both classifications 0.025 (CI = 0.013-0.037). Moreover, no relationship was found between sputum eosinophilia and peripheral blood eosinophilia count in the total studied population. Discussion and Conclusion: In conclusion, our results suggest that grouping the biomarkers proposed by Heany et al. are insufficient to diagnose eosinophilic phenotypes in asthmatic patients. Sputum analysis remains the gold standard to assess airway inflammation.
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