Phenotypic subtypes of fibrotic hypersensitivity pneumonitis identified by machine learning consensus clustering analysis
Issued Date
2024-12-01
Resource Type
ISSN
14659921
eISSN
1465993X
Scopus ID
2-s2.0-85182646261
Pubmed ID
38238763
Journal Title
Respiratory Research
Volume
25
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Respiratory Research Vol.25 No.1 (2024)
Suggested Citation
Petnak T., Cheungpasitporn W., Thongprayoon C., Sodsri T., Tangpanithandee S., Moua T. Phenotypic subtypes of fibrotic hypersensitivity pneumonitis identified by machine learning consensus clustering analysis. Respiratory Research Vol.25 No.1 (2024). doi:10.1186/s12931-024-02664-x Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/95529
Title
Phenotypic subtypes of fibrotic hypersensitivity pneumonitis identified by machine learning consensus clustering analysis
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Corresponding Author(s)
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Abstract
Background: Patients with fibrotic hypersensitivity pneumonitis (f-HP) have varied clinical and radiologic presentations whose associated phenotypic outcomes have not been previously described. We conducted a study to evaluate mortality and lung transplant (LT) outcomes among clinical clusters of f-HP as characterized by an unsupervised machine learning approach. Methods: Consensus cluster analysis was performed on a retrospective cohort of f-HP patients diagnosed according to recent international guideline. Demographics, antigen exposure, radiologic, histopathologic, and pulmonary function findings along with comorbidities were included in the cluster analysis. Cox proportional-hazards regression was used to assess mortality or LT risk as a combined outcome for each cluster. Results: Three distinct clusters were identified among 336 f-HP patients. Cluster 1 (n = 158, 47%) was characterized by mild restriction on pulmonary function testing (PFT). Cluster 2 (n = 46, 14%) was characterized by younger age, lower BMI, and a higher proportion of identifiable causative antigens with baseline obstructive physiology. Cluster 3 (n = 132, 39%) was characterized by moderate to severe restriction. When compared to cluster 1, mortality or LT risk was lower in cluster 2 (hazard ratio (HR) of 0.42; 95% CI, 0.21–0.82; P = 0.01) and higher in cluster 3 (HR of 1.76; 95% CI, 1.24–2.48; P = 0.001). Conclusions: Three distinct phenotypes of f-HP with unique mortality or transplant outcomes were found using unsupervised cluster analysis, highlighting improved mortality in fibrotic patients with obstructive physiology and identifiable antigens.