RT Journal Article
SR Electronic
T1 Clinical response to benralizumab can be predicted by combining clinical outcomes at 3 months with baseline characteristics
JF ERJ Open Research
JO erjor
FD European Respiratory Society
SP 00559-2022
DO 10.1183/23120541.00559-2022
A1 Johannes A. Kroes
A1 Kim de Jong
A1 Simone Hashimoto
A1 Sander W. Zielhuis
A1 Eric N van Roon
A1 Jacob K. Sont
A1 Anneke ten Brinke
A1 ,
YR 2023
UL http://openres.ersjournals.com/content/early/2023/01/05/23120541.00559-2022.abstract
AB Background Benralizumab is highly effective in many, but not all, patients with severe asthma. Baseline characteristics alone are insufficient to predict an individual's probability of long-term benralizumab response.Objectives To (1) study whether parameters at 3 months –in addition to baseline characteristics– contribute to the prediction of benralizumab response at 1 year and to (2) develop an easy-to-use prediction tool to assess an individual's probability of long-term response.Methods We assessed the effect of benralizumab treatment in 192 patients from the Dutch severe asthma registry (RAPSODI). To investigate predictors of long-term benralizumab response (≥50% reduction in maintenance oral corticosteroid (OCS) dose or annual exacerbation frequency) we used logistic regression, including baseline characteristics and 3-month Asthma Control Questionnaire (ACQ-6) score and maintenance OCS dose.Results Benralizumab treatment significantly improved several clinical outcomes and 144 (75%) patients were classified as long-term responders. Response prediction improved significantly when 3-month outcomes were added to a predictive model with baseline characteristics only (AUROC 0.85 versus 0.72, p=0.001). Based on this model, a prediction tool using gender, prior biologic use, baseline blood eosinophils, FEV1 and at 3 months OCS dose and ACQ-6 was developed which classified patients into 3 categories with increasing probability of long-term response (95%CI): 25%(3–65), 67%(57–77) and 97%(91–99) respectively.Conclusion In addition to baseline characteristics, treatment outcomes at 3 months contribute to the prediction of benralizumab response at 1 year in patients with severe eosinophilic asthma. Prediction tools as proposed in this study may help physicians optimize the use of costly biologics.FootnotesThis manuscript has recently been accepted for publication in the ERJ Open Research. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJOR online. Please open or download the PDF to view this article.Conflict of interest: Mr. Johannes A Kroes reports a grant from AstraZeneca.Conflict of interest: Dr. Kim De Jong has nothing to disclose.Conflict of interest: Dr. Simone Hashimoto has nothing to disclose.Conflict of interest: Dr. Sander W Zielhuis reports a grant from AstraZeneca and personal fees from Novartis, GlaxoSmithKline, Sanofi-Genzyme Regeneron, Eli-Lilly and Merck Sharp & Dohme. Prof.Conflict of interest: Dr. Eric N Van Roon has nothing to disclose.Conflict of interest: Dr. Jacob K Sont reports a grant from AstraZeneca.Conflict of interest: Dr. Anneke Ten Brinke reports grants from AstraZeneca, GlaxoSmithKline, TEVA and Sanofi-Genzyme Regeneron and personal fees from GlaxoSmithKline, TEVA, AstraZeneca and Sanofi-Genzyme Regeneron, unrelated to this work.