Benralizumab Effectiveness in Severe Asthma Is Independent of Previous Biologic Use

Jackson, David J.; Burhan, Hassan; Menzies‐Gow, Andrew; Pfeffer, Paul; Nanzer, AM; Gil, Esther Garcia; Morris, Tamsin; Tran, Trung; Hirsch, Ian; Dube, Sabada

doi:10.1016/j.jaip.2022.02.014

Cited by 31 publications

(29 citation statements)

References 28 publications

(33 reference statements)

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“… 32 A slightly greater reduction in exacerbations was seen in patients with BEC higher than 400 cells/mm 3 when compared with patients showing BEC between 300 and 400 cells/mm 3 in the Benralizumab Patient Access Programme (BPAP) study. 33 With regard to lung function, benralizumab was found to be more effective in improving FEV 1 in patients with BEC greater than 500 cells/mm 3 , in line with the results from this post hoc analysis. 30 Potential differences between the results of this and other studies could be due to discrepancies in the number of patients enrolled as well as the baseline characteristics shown by the BEC cohorts in the various RWE.…”

Section: Discussionsupporting

confidence: 84%

Clinical Features and Efficacy of Benralizumab in Patients with Blood Eosinophil Count Between 300 and 450 Cells/mm3: A Post Hoc Analysis from the ANANKE Study

Senna¹,

Aliani²,

Altieri³

et al. 2022

JAA

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Benralizumab effectively reduces severe eosinophilic asthma (SEA) exacerbations in patients with a wide range of baseline blood eosinophil count (BEC). Patients included in real-world studies are often characterized by high mean/median BEC, while patients with BEC close to 300 cells/mm 3 are poorly represented. This post hoc analysis from the Italian study ANANKE aims to define the clinical features and corroborate the efficacy of benralizumab in real world in the BEC 300-450 cells/mm 3 subset of patients. Patients and Methods: Post hoc analysis of the Italian, multicenter, observational, retrospective real-life study ANANKE (NCT04272463). Baseline clinical and laboratory characteristics were collected in the 12 months prior to benralizumab treatment and presented for a BEC 300-450 cells/mm 3 subgroup of patients. Change over time of BEC, annualized exacerbation rate (AER), asthma control (ACT), lung function and oral corticosteroid (OCS) use at 16, 24 and 48 weeks after benralizumab introduction were collected. Results: A total of 164 patients were analyzed, 34 of whom with a BEC of 300-450 cells/mm 3 . This subgroup was more likely to be female (64.7%), with lower rates of severe exacerbations at baseline when compared to the total population (0.69 vs 1.01). After 48 weeks of benralizumab treatment, the BEC 300-450 subset showed similar reductions in AER (−94.8% vs −92.2%) and OCS use

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Section: Discussionsupporting

confidence: 84%

Clinical Features and Efficacy of Benralizumab in Patients with Blood Eosinophil Count Between 300 and 450 Cells/mm3: A Post Hoc Analysis from the ANANKE Study

Senna¹,

Aliani²,

Altieri³

et al. 2022

JAA

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“…[12,13,16,28] Early treatment outcomes as a parameter in predicting future response to benralizumab was studied in a single study in which an ACQ-6-improvement of ≥0.5 units 4 weeks after initiating benralizumab predicted response at 48 weeks. [19] Our study confirms and extends these findings, as we showed that a combination of baseline characteristics and early treatment outcomes was most successful in identifying patients that are most likely to respond to benralizumab.…”

Section: Discussionsupporting

confidence: 86%

“…In a recent study it was stated that benralizumab is effective in severe asthma independent of previous biologic use. [19] Also in the present population, patients with or without previous treatment with a biologic for severe asthma significantly benefited from benralizumab treatment (data not shown). However, the individual probability of responding to benralizumab treatment was significantly higher in patients without previous biologic use, justifying its inclusion in the predictive model.…”

Section: Discussionmentioning

confidence: 62%

“…[13,16] Next to baseline characteristics, early treatment effects may contribute to the prediction of long-term outcomes, as shown by a few studies that focused on predicting future asthma exacerbations or therapy response. [17][18][19] Whether the prediction of long-term response to benralizumab improves with the addition of early treatment outcomes to baseline characteristics is not yet known. Therefore, we assessed the effects of benralizumab treatment using real-world patient data from the Dutch Severe Asthma Registry RAPSODI.…”

Section: Introductionmentioning

confidence: 99%

“…Certain baseline characteristics, such as higher exacerbation frequency or higher blood eosinophil counts, are associated with more favourable benralizumab-induced outcomes, but it remains difficult to predict an individuals’ probability of being a responder [ 13 , 16 ]. Next to baseline characteristics, early treatment effects may contribute to the prediction of long-term outcomes, as shown by a few studies that focused on predicting future asthma exacerbations or therapy response [ 17 – 19 ]. Whether the prediction of long-term response to benralizumab improves with the addition of early treatment outcomes to baseline characteristics is not yet known.…”

Section: Introductionmentioning

confidence: 99%

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Clinical response to benralizumab can be predicted by combining clinical outcomes at 3 months with baseline characteristics

et al. 2023

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BackgroundBenralizumab 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.ObjectivesTo (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.MethodsWe 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.ResultsBenralizumab 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 0.85versus0.72, p=0.001). Based on this model, a prediction tool using gender, prior biologic use, baseline blood eosinophils, FEV1and 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.ConclusionIn 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.

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Probabilistic precision calculations for the planning of studies assessing negative binomial rates

Hedberg,

Franzén

2024

Pharmacoepidemiology and Drug

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PurposeOutcome variables that are assumed to follow a negative binomial distribution are frequently used in both clinical and epidemiological studies. Epidemiological studies, particularly those performed by pharmaceutical companies often aim to describe a population rather than compare treatments. Such descriptive studies are often analysed using confidence intervals. While precision calculations and sample size calculations are not always performed in these settings, they have the important role of setting expectations of what results the study may generate. Current methods for precision calculations for the negative binomial rate are based on plugging in parameter values into the confidence interval formulae. This method has the downside of ignoring the randomness of the confidence interval limits. To enable better practice for precision calculations, methods are needed that address the randomness.MethodsUsing the well‐known delta‐method we develop a method for calculating the precision probability, that is, the probability of achieving a certain width. We assess the performance of the method in smaller samples through simulations.ResultsThe method for the precision probability performs well in small to medium sample sizes, and the usefulness of the method is demonstrated through an example.ConclusionsWe have developed a simple method for calculating the precision probability for negative binomial rates. This method can be used when planning epidemiological studies in for example, asthma, while correctly taking the randomness of confidence intervals into account.

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Benralizumab Effectiveness in Severe Asthma Is Independent of Previous Biologic Use

Cited by 31 publications

References 28 publications

Clinical Features and Efficacy of Benralizumab in Patients with Blood Eosinophil Count Between 300 and 450 Cells/mm3: A Post Hoc Analysis from the ANANKE Study

Clinical Features and Efficacy of Benralizumab in Patients with Blood Eosinophil Count Between 300 and 450 Cells/mm3: A Post Hoc Analysis from the ANANKE Study

Clinical response to benralizumab can be predicted by combining clinical outcomes at 3 months with baseline characteristics

Probabilistic precision calculations for the planning of studies assessing negative binomial rates

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