Résumé
Asthma is defined as severe when it is uncontrolled despite the high intensity of treatment, or that loses control when a therapeutic step down is tried.
These patients, for years, have been "uniformly" treated with massive doses of inhaled and oral corticosteroids regardless of their inflammatory state.
Initially, asthma was considered of genesis "exclusively allergic." Subsequently, thanks to the development of noninvasive tools and of human monoclonal antibodies targeting interleukin 5, a pathogenetic role has been given to eosinophils. Management of steroids based on sputum eosinophil counts has been suggested according to clinical phenotypes identified through cluster analysis.
The algorithms obtained from the cluster analysis have proved later to be poorly predictive of the inflammatory phenotype and difficult to apply in clinical practice.
In the new era of precision medicine, the greatest challenge is finding clinical or biological elements predictive of response to therapies such as biologics. Cluster analyses performed on omics data or on cohorts of patients treated with biologics are more promising in this sense.
In this article, starting from the current definition of severe asthma, we review the phenotypes proposed over time to date, showing the difficulty underlying the process of "phenotyping" due to the scarcity of available biomarkers.