Multivariate Analysis As a Support for Diagnostic Flowcharts in Allergic Bronchopulmonary Aspergillosis: A Proof-of-Concept Study - Vitte, Joana; Ranque, Stéphane; Carsin, Ania; Gomez, Carine; Romain, Thomas; Cassagne, Carole; Gouitaa, Marion; Baravalle-Einaudi, Mélisande; Bel, Nathalie Stremler-Le; Reynaud-Gaubert, Martine; Dubus, Jean-Christophe; Mège, Jean-Louis; et al. (Frontiers in Immunology, 2017)
Molecular-based allergy diagnosis yields multiple biomarker datasets. The classical diagnostic score for allergic bronchopulmonary aspergillosis, 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 IgE, anti-Aspergillus fumigatus “precipitins”, and anti-Aspergillus fumigatus IgG. Progress achieved over the last four decades led to multiple IgE and IgG(4) Aspergillus fumigatus 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 allergic bronchopulmonary aspergillosis. 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 Aspergillus fumigatus 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 Aspergillus fumigatus-sensitized patients at risk for allergic bronchopulmonary aspergillosis.