ReviewPrediction of response to biological treatment with monoclonal antibodies in severe asthma
Graphical abstract
Introduction
Patients with severe asthma require high-dose inhalation therapy to control their disease. These patients experience frequent exacerbations, and they often depend on the chronic use of oral corticosteroids (OCS) with associated serious adverse effects.[1] In recent years, major developments occurred in severe asthma management. Different asthma phenotypes and subgroups were identified [2] and new treatment options have become available in the form of monoclonal antibodies (MABs).[3] Although these novel biological agents have shown promising results in many patients with asthma, it is evident that not all patients respond equally well. This difference in treatment response may be multifactorial and related to the heterogeneity of the severe asthma population or the different underlying molecular pathways, but also drug and treatment strategy related factors may play a role. Optimal use of biologics, both in terms of costs and prevention of unnecessary patient exposure, is of the utmost importance. A Dutch cost estimation indicates the drug costs per patient per year in the Netherlands at €15.000,-.[4] Unfortunately, it is not yet clear which patients will respond to which biologic. Therefore, biologic response prediction has become a major point of interest in severe asthma management.
The present article shortly describes asthma phenotypes, and inflammatory mechanisms and pathobiologic features leading to severe asthma. Furthermore, the pharmacological mechanism of action and clinical outcomes of the currently available biologics for severe asthma are summarized. Then, we thoroughly review predictors of response to the currently registered biologics and, finally, discuss recent developments and future perspectives in response prediction.
Section snippets
Asthma subtypes and pathobiology
Asthma is a heterogeneous, inflammatory airway disease in which different phenotypes have been identified based on clinical, functional or inflammatory parameters.[2] Late-onset eosinophilic asthma is currently one of the most well-defined asthma phenotypes with a clearly different clinical profile from that seen in classic childhood-onset allergic asthma.[5] Patients with late-onset eosinophilic asthma show eosinophilic inflammation in blood as well as sputum and frequently report absence of
Predictors of response
The main objective of phase I-III clinical trials is the assessment of efficacy and safety. Knowing which patient will respond in real-life is a different objective and usually not established at the moment of market approval of the biologic. Prediction of treatment responses is not easy and has to deal with various problems: e.g. how to define a response or responder, what are clinically relevant outcome measures [51], and what should be the timing of the evaluation of response. Since
Future perspectives
New perspectives in response prediction of the MABs used in severe asthma may present themselves in the near future. Four possible aspects will be highlighted below.
Conclusion
This article summarizes the current state of knowledge on response prediction of biological treatment in severe asthma. Studies that explore the predictability of biologic efficacy are mainly based on post-hoc analyses of the large registration trials or small exploratory studies with a limited number of patients. Although these studies provide some insight, there are still several issues that require further evidence. For example, what is the best timing to assess biologic response or when can
CRediT authorship contribution statement
J.A. Kroes: Investigation, Formal analysis, Writing - original draft, Writing - review & editing. S.W. Zielhuis: Conceptualization, Writing - review & editing, Supervision, Funding acquisition. E.N. van Roon: Writing - review & editing, Supervision. A. ten Brinke: Conceptualization, Writing - review & editing, Supervision.
Declaration of Competing Interest
JA Kroes: No conflicts of interest to disclose.
A ten Brinke: Unrestricted research grants GSK, TEVA. Research advisory boards GSK, Novartis, AstraZeneca, Boehringer Ingelheim, Chiesi, Sanofi. Honoraria lectures GSK, Novartis, Teva, Boehringer Ingelheim.
SW Zielhuis: Advisory boards Novartis, AstraZeneca, Sanofi. Honoraria lectures MSD. Until 2007 employed at Teva NL, but no involvement since then.
EN van Roon: No conflicts of interest to disclose.
Acknowledgements
This article was supported by funding of the Medical Centre Leeuwarden Science Fund, the Netherlands.
The authors would like to thank Olga van Dijk and colleagues from the MCL Academy for the reference acquisition for this study.
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