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Respiratory Research
Published in: Respiratory Research 1/2023

Open Access 01-12-2023 | Bronchial Asthma | Research

Can we predict who will benefit most from biologics in severe asthma? A post-hoc analysis of two phase 3 trials

Authors: Wenjia Chen, Helen K. Reddel, J Mark FitzGerald, Richard Beasley, Christer Janson, Mohsen Sadatsafavi

Published in: Respiratory Research | Issue 1/2023

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Abstract

Background

Individualized prediction of treatment response may improve the value proposition of advanced treatment options in severe asthma. This study aimed to investigate the combined capacity of patient characteristics in predicting treatment response to mepolizumab in patients with severe asthma.

Methods

Patient-level data were pooled from two multinational phase 3 trials of mepolizumab in severe eosinophilic asthma. We fitted penalized regression models to quantify reductions in the rate of severe exacerbations and the 5-item Asthma Control Questionnaire (ACQ5) score. The capacity of 15 covariates towards predicting treatment response was quantified by the Gini index (measuring disparities in treatment benefit) as well as observed treatment benefit within the quintiles of predicted treatment benefit.

Results

There was marked variability in the ability of patient characteristics to predict treatment response; covariates explained greater heterogeneity in predicting treatment response to asthma control than to exacerbation frequency (Gini index 0.35 v. 0.24). Key predictors for treatment benefit for severe exacerbations included exacerbation history, blood eosinophil count, baseline ACQ5 score and age, and those for symptom control included blood eosinophil count and presence of nasal polyps. Overall, the average reduction in exacerbations was 0.90/year (95%CI, 0.87‒0.92) and average reduction in ACQ5 score was 0.18 (95% CI, 0.02‒0.35). Among the top 20% of patients for predicted treatment benefit, exacerbations were reduced by 2.23/year (95% CI, 2.03‒2.43) and ACQ5 score were reduced by 0.59 (95% CI, 0.19‒0.98). Among the bottom 20% of patients for predicted treatment benefit, exacerbations were reduced by 0.25/year (95% CI, 0.16‒0.34) and ACQ5 by -0.20 (95% CI, -0.51 to 0.11).

Conclusion

A precision medicine approach based on multiple patient characteristics can guide biologic therapy in severe asthma, especially in identifying patients who will not benefit as much from therapy. Patient characteristics had a greater capacity to predict treatment response to asthma control than to exacerbation.

Trial registration

ClinicalTrials.gov number, NCT01691521 (registered September 24, 2012) and NCT01000506 (registered October 23, 2009).
Appendix
Available only for authorised users
Literature
1.
Chung KF, Wenzel SE, Brozek JL, Bush A, Castro M, Sterk PJ, et al. International ERS/ATS guidelines on definition, evaluation and treatment of severe asthma. Eur Respir J. 2014 Feb;43(2):343–73.
2.
Hekking PPW, Wener RR, Amelink M, Zwinderman AH, Bouvy ML, Bel EH. The prevalence of severe refractory asthma. J Allergy Clin Immunol. 2015 Apr;135(4):896–902.
3.
von Bülow A, Kriegbaum M, Backer V, Porsbjerg C. The prevalence of severe asthma and low asthma control among danish adults. J Allergy Clin Immunol Pract. 2014 Dec;2(6):759–67.
4.
Custovic A, Johnston SL, Pavord I, Gaga M, Fabbri L, Bel EH, et al. EAACI position statement on asthma exacerbations and severe asthma. Allergy. 2013 Dec;68(12):1520–31.
5.
Chen W, Safari A, FitzGerald JM, Sin DD, Tavakoli H, Sadatsafavi M. Economic burden of multimorbidity in patients with severe asthma: a 20-year population-based study. Thorax. 2019 Dec;74(12):1113–9.
6.
Antonicelli L, Bucca C, Neri M, De Benedetto F, Sabbatani P, Bonifazi F, et al. Asthma severity and medical resource utilisation. Eur Respir J. 2004 May;23(5):723–9.
7.
“Real-life”. Effectiveness Studies of Omalizumab in Adult Patients with Severe Allergic Asthma: Meta-analysis. J Allergy Clin Immunol Pract. 2017 Sep 1;5(5):1362–1370.e2.
8.
Nair P, Pizzichini MMM, Kjarsgaard M, Inman MD, Efthimiadis A, Pizzichini E, et al. Mepolizumab for prednisone-dependent asthma with sputum eosinophilia. N Engl J Med. 2009 Mar;5(10):985–93.
9.
Pavord ID, Korn S, Howarth P, Bleecker ER, Buhl R, Keene ON et al. Mepolizumab for severe eosinophilic asthma (DREAM): a multicentre, double-blind, placebo-controlled trial.Lancet Lond Engl. 2012 Aug18;380(9842):651–9.
10.
Ortega HG, Liu MC, Pavord ID, Brusselle GG, FitzGerald JM, Chetta A, et al. Mepolizumab Treatment in patients with severe eosinophilic asthma. N Engl J Med. 2014 Sep;25(13):1198–207.
11.
Bel EH, Wenzel SE, Thompson PJ, Prazma CM, Keene ON, Yancey SW, et al. Oral glucocorticoid-sparing effect of Mepolizumab in Eosinophilic Asthma. N Engl J Med. 2014 Sep;25(13):1189–97.
12.
Corren J, Parnes JR, Wang L, Mo M, Roseti SL, Griffiths JM, et al. Tezepelumab in adults with uncontrolled asthma. N Engl J Med. 2017 Sep;7(10):936–46.
13.
Nair P, Wenzel S, Rabe KF, Bourdin A, Lugogo NL, Kuna P, et al. Oral glucocorticoid–sparing effect of Benralizumab in severe asthma. N Engl J Med. 2017 Jun;22(25):2448–58.
14.
Rabe KF, Nair P, Brusselle G, Maspero JF, Castro M, Sher L, et al. Efficacy and safety of Dupilumab in glucocorticoid-dependent severe asthma. N Engl J Med. 2018 Jun;28(26):2475–85.
15.
Kim H, Ellis AK, Fischer D, Noseworthy M, Olivenstein R, Chapman KR, et al. Asthma biomarkers in the age of biologics. Allergy Asthma Clin Immunol. 2017 Nov;17(1):48.
16.
Haldar P, Brightling CE, Hargadon B, Gupta S, Monteiro W, Sousa A, et al. Mepolizumab and Exacerbations of Refractory Eosinophilic Asthma. N Engl J Med. 2009 Mar;5(10):973–84.
17.
Niven RM, Saralaya D, Chaudhuri R, Masoli M, Clifton I, Mansur AH et al. Impact of omalizumab on treatment of severe allergic asthma in UK clinical practice: a UK multicentre observational study (the APEX II study). BMJ Open. 2016 Aug 1;6(8):e011857.
18.
19.
Eger K, Kroes JA, Ten Brinke A, Bel EH. Long-term therapy response to Anti-IL-5 biologics in severe Asthma-A real-life evaluation. J Allergy Clin Immunol Pract. 2021 Mar;9(3):1194–200.
20.
Mukherjee M, Forero DF, Tran S, Boulay ME, Bertrand M, Bhalla A et al. Suboptimal treatment response to anti-IL-5 monoclonal antibodies in severe eosinophilic asthmatics with airway autoimmune phenomena. Eur Respir J [Internet]. 2020 Oct 1 [cited 2021 Oct 27];56(4). Available from: https://​erj.​ersjournals.​com/​content/​56/​4/​2000117
21.
Chen BK, Yang YT, Bennett CL. Why Biologics and Biosimilars remain so expensive: despite two wins for Biosimilars, the Supreme Court’s recent rulings do not solve fundamental barriers to competition. Drugs. 2018 Nov;78(17):1777–81.
22.
Tan LE, Tan WHG, Aziz MIA, Koh MS, Tay TR, Pearce F, et al. Assessing the cost-effectiveness of mepolizumab as add-on therapy to standard of care for severe eosinophilic asthma in Singapore. J Asthma. 2020 Oct;15(0):1–11.
23.
Kent DM, Steyerberg E, van Klaveren D. Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects. BMJ. 2018 Dec;10:363:k4245.
24.
Pavord ID, Korn S, Howarth P, Bleecker ER, Buhl R, Keene ON et al. Mepolizumab for severe eosinophilic asthma (DREAM): a multicentre, double-blind, placebo-controlled trial.Lancet. 2012 Aug18;380(9842):651–9.
25.
Riley RD, Ensor J, Snell KIE, Harrell FE, Martin GP, Reitsma JB, et al. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020 Mar;18:368:m441.
26.
Reddel HK, Taylor DR, Bateman ED, Boulet LP, Boushey HA, Busse WW, et al. An official american thoracic Society/European respiratory society statement: asthma control and exacerbations: standardizing endpoints for clinical asthma trials and clinical practice. Am J Respir Crit Care Med. 2009 Jul;180(1):59–99.
27.
28.
29.
van Klaveren D, Balan TA, Steyerberg EW, Kent DM. Models with interactions overestimated heterogeneity of treatment effects and were prone to treatment mistargeting. J Clin Epidemiol. 2019 Oct;114:72–83.
30.
Austin PC, Urbach DR. Using G-computation to estimate the effect of regionalization of surgical services on the absolute reduction in the occurrence of adverse patient outcomes. Med Care. 2013 Sep;51(9):797–805.
31.
Gastwirth JL. The estimation of the Lorenz curve and Gini Index. Rev Econ Stat. 1972;54(3):306–16.CrossRef
32.
33.
Asada Y, Hurley J, Norheim OF, Johri M. A three-stage approach to measuring health inequalities and inequities. Int J Equity Health. 2014 Nov;13(1):98.
34.
Steinbeis F, Gotham D, von Philipsborn P, Stratil JM. Quantifying changes in global health inequality: the Gini and Slope Inequality Indices applied to the Global Burden of Disease data, 1990–2017.BMJ Glob Health. 2019 Sep24;4(5):e001500.
35.
Tao Y, Henry K, Zou Q, Zhong X. Methods for measuring horizontal equity in health resource allocation: a comparative study.Health Econ Rev. 2014 Aug10;4(1):10.
36.
Juniper EF, Svensson K, Mörk AC, Ståhl E. Measurement properties and interpretation of three shortened versions of the asthma control questionnaire. Respir Med. 2005 May;99(5):553–8.
37.
Anderson WC, Szefler SJ. Cost-effectiveness and comparative effectiveness of biologic therapy for asthma: To biologic or not to biologic? Ann Allergy Asthma Immunol. 2019 Apr 1;122(4):367–72.
38.
Porsbjerg CM, Menzies-Gow AN, Tran TN, Murray RB, Unni B, Audrey Ang SL et al. Global Variability in Administrative Approval Prescription Criteria for Biologic Therapy in Severe Asthma.J Allergy Clin Immunol Pract. 2022 Jan 3;S2213-2198(21)01454-9.
39.
Luc F, Prieur E, Whitmore GA, Gibson PG, Vandemheen KL, Aaron SD. Placebo Effects in clinical trials evaluating patients with uncontrolled persistent asthma. Ann Am Thorac Soc. 2019 Sep;16(9):1124–30.
40.
Bender B, Oppenheimer J, George M, Brown R, Patel A, Hill T et al. Assessment of Real-World Escalation to Biologics in US Patients With Asthma. J Allergy Clin Immunol Pract. 2022 Nov 1;10(11):2941–8.
41.
Chen W, Sadatsafavi M, Tran TN, Murray RB, Wong CBN, Ali N, et al. Characterization of patients in the international severe Asthma Registry with high steroid exposure who did or did not initiate biologic therapy. J Asthma Allergy. 2022;15:1491–510.CrossRefPubMedPubMedCentral
Metadata
Title
Can we predict who will benefit most from biologics in severe asthma? A post-hoc analysis of two phase 3 trials
Authors
Wenjia Chen
Helen K. Reddel
J Mark FitzGerald
Richard Beasley
Christer Janson
Mohsen Sadatsafavi
Publication date
01-12-2023
Publisher
BioMed Central
Published in
Respiratory Research / Issue 1/2023
Electronic ISSN: 1465-993X
DOI
https://doi.org/10.1186/s12931-023-02409-2

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WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

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