Multivariate Analysis As a Support for Diagnostic Flowcharts in Allergic Bronchopulmonary Aspergillosis: A Proof-of-Concept Study
Résumé
Molecular-based allergy diagnosis yields multiple biomarker datasets. The classical diagnostic score for allergic bronchopulmonary aspergillosis (ABPA), a severe disease usually occurring in asthmatic patients and people with cystic fibrosis, comprises succinct immunological criteria formulated in 1977: total IgE, anti-Aspergillus fumigatus (Af) IgE, anti-Af ``precipitins,'' and anti-Af IgG. Progress achieved over the last four decades led to multiple IgE and IgG(4) Af biomarkers available with quantitative, standardized, molecular-level reports. These newly available biomarkers have not been included in the current diagnostic criteria, either individually or in algorithms, despite persistent underdiagnosis of ABPA. Large numbers of individual biomarkers may hinder their use in clinical practice. Conversely, multivariate analysis using new tools may bring about a better chance of less diagnostic mistakes. We report here a proof-of-concept work consisting of a three-step multivariate analysis of Af IgE, IgG, and IgG4 biomarkers through a combination of principal component analysis, hierarchical ascendant classification, and classification and regression tree multivariate analysis. The resulting diagnostic algorithms might show the way for novel criteria and improved diagnostic efficiency in Af-sensitized patients at risk for ABPA.
Mots clés
allergic bronchopulmonary aspergillosis
Aspergillus fumigatus
immunoglobulin
molecular allergens
multivariate analysis Abbreviations: ABPA
allergic bronchopulmonary aspergillosis
Af
CART
classification and regression tree
CF
cystic fibrosis
HAC
hierarchical ascendant classification
Ig
PCA
principal component analysis
s
specific
Domaines
Médecine humaine et pathologie| Origine | Publication financée par une institution |
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