Childhood asthma clusters and response to therapy in clinical trials

doi:10.1016/j.jaci.2013.09.002

Journal of Allergy and Clinical Immunology

Volume 133, Issue 2, February 2014, Pages 363-369.e3

https://doi.org/10.1016/j.jaci.2013.09.002 Get rights and content

Background

Childhood asthma clusters, or subclasses, have been developed by computational methods without evaluation of clinical utility.

Objective

To replicate and determine whether childhood asthma clusters previously identified computationally in the Severe Asthma Research Program (SARP) are associated with treatment responses in Childhood Asthma Research and Education (CARE) Network clinical trials.

Methods

A cluster assignment model was determined by using SARP participant data. A total of 611 participants 6 to 18 years old from 3 CARE trials were assigned to SARP pediatric clusters. Primary and secondary outcomes were analyzed by cluster in each trial.

Results

CARE participants were assigned to SARP clusters with high accuracy. Baseline characteristics were similar between SARP and CARE children of the same cluster. Treatment response in CARE trials was generally similar across clusters. However, with the caveat of a smaller sample size, children in the early-onset/severe-lung function cluster had best response with fluticasone/salmeterol (64% vs 23% 2.5× fluticasone and 13% fluticasone/montelukast in the Best ADd-on Therapy Giving Effective Responses trial; P = .011) and children in the early-onset/comorbidity cluster had the least clinical efficacy to treatments (eg, −0.076% change in FEV₁ in the Characterizing Response to Leukotriene Receptor Antagonist and Inhaled Corticosteroid trial).

Conclusions

In this study, we replicated SARP pediatric asthma clusters by using a separate, large clinical trials network. Early-onset/severe-lung function and early-onset/comorbidity clusters were associated with differential and limited response to therapy, respectively. Further prospective study of therapeutic response by cluster could provide new insights into childhood asthma treatment.

Section snippets

Methods

The study population consisted of 6- to 18-year-old children with asthma (N = 611) enrolled in 3 CARE Network clinical trials.15, 16, 17 The trials are summarized in Table I. Briefly, the Pediatric Asthma Controller Trial (PACT)¹⁶ was a 3-arm (1× fluticasone, 0.5× fluticasone plus salmeterol, or montelukast) double-blind study of children with mild-moderate asthma and used percentage of asthma control days as the primary outcome. The Characterizing Response to Leukotriene Receptor Antagonist

Classification model and assignment

For early-onset/normal-lung, late-onset/normal-lung, early-onset/comorbidity, and early-onset/severe-lung clusters, cross-validated QDA recall using SARP data with FEV₁ and asthma duration was 96%, 94%, 97%, and 90%, while precision was 96%, 94%, 94%, and 93%, respectively (see Table E1 in this article’s Online Repository at www.jacionline.org). Using SARP data with the same 2 variables, cross-validation LDA recall was 90%, 96%, 94%, and 90% and precision was 98%, 89%, 94%, and 90%,

Discussion

In this study, we replicated SARP pediatric asthma clusters by demonstrating that CARE Network participants assigned to SARP clusters had similar characteristics. Furthermore, overall patterns of treatment response in the PACT, the CLIC trial, and the BADGER trial were similar across clusters when compared with responses in entire study populations. Interestingly, however, the early-onset/severe-lung cluster clearly had a best step 3 response with fluticasone/salmeterol in the BADGER trial,

References (25)

S.E. Wenzel
Asthma: defining of the persistent adult phenotypes
Lancet
(2006)
M.K. Miller et al.
Severity assessment in asthma: an evolving concept
J Allergy Clin Immunol
(2005)
S.J. Szefler et al.
Characterization of within-subject responses to fluticasone and montelukast in childhood asthma
J Allergy Clin Immunol
(2005)
C.A. Sorkness et al.
Long-term comparison of 3 controller regimens for mild-moderate persistent childhood asthma: the Pediatric Asthma Controller Trial
J Allergy Clin Immunol
(2007)
R.L. Sorkness et al.
Sex dependence of airflow limitation and air trapping in children with severe asthma
J Allergy Clin Immunol
(2011)
J. Lötvall et al.
Asthma endotypes: a new approach to classification of disease entities within the asthma syndrome
J Allergy Clin Immunol
(2011)
National Asthma Education and Prevention Program. Expert panel report 3: guidelines for the diagnosis and management of...
Global Initiative for Asthma. Global Strategy for Asthma Management and Prevention (GINA). Available at:...
P. Haldar et al.
Cluster analysis and clinical asthma phenotypes
Am J Respir Crit Care Med
(2008)
W.C. Moore et al.
Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program
Am J Respir Crit Care Med
(2010)

A. Durham et al.

Steroid resistance in severe asthma: current mechanisms and future treatment

Curr Pharm Des

(2011)

T. Sekigawa et al.

Gene-expression profiles in human nasal polyp tissues and identification of genetic susceptibility in aspirin-intolerant asthma

Clin Exp Allergy

(2009)

Cited by (57)

Pediatric obesity and severe asthma: Targeting pathways driving inflammation
2023, Pharmacological Research
Asthma affects more than 300 million people of all ages worldwide, including about 10–15% of school-aged children, and its prevalence is increasing. Severe asthma (SA) is a particular and rare phenotype requiring treatment with high-dose inhaled corticosteroids plus a second controller and/or systemic glucocorticoid courses to achieve symptom control or remaining “uncontrolled” despite this therapy. In SA, other diagnoses have been excluded, and potential exacerbating factors have been addressed. Notably, obese asthmatics are at higher risk of developing SA. Obesity is both a major risk factor and a disease modifier of asthma in children and adults: two main “obese asthma” phenotypes have been described in childhood with high or low levels of Type 2 inflammation biomarkers, respectively, the former characterized by early onset and eosinophilic inflammation and the latter by neutrophilic inflammation and late-onset. Nevertheless, the interplay between obesity and asthma is far more complex and includes obese tissue-driven inflammatory pathways, mechanical factors, comorbidities, and poor response to corticosteroids. This review outlines the most recent findings on SA in obese children, particularly focusing on inflammatory pathways, which are becoming of pivotal importance in order to identify selective targets for specific treatments, such as biological agents.
Diagnosing, Monitoring and Treating Asthma
2021, Encyclopedia of Respiratory Medicine, Second Edition
Asthma is the most common long term condition in childhood, yet the frequency with which it is diagnosed belies the complexity and heterogeneity of asthma and the challenges in management. Although most children respond well to low levels of inhaled steroids a significant proportion experience frequent attacks and symptoms which impact on their quality of life. Advances have been made in recent years in understanding the underlying pathobiology of childhood asthma, particularly in those with severe asthma, affording the opportunity for more effective targeted treatments. This article will discuss the important considerations in diagnosing childhood asthma, explore the underlying pathophysiology, describe phenotypes of asthma and how they can be used to direct treatment and finally discuss the key components of asthma monitoring.
Advances in understanding and reducing the burden of severe asthma in children
2020, The Lancet Respiratory Medicine
Severe asthma in children is rare, accounting for only a small proportion of childhood asthma. After addressing modifiable factors such as adherence to treatment, comorbidities, and adverse exposures, children whose disease is not well controlled on high doses of medication form a heterogeneous group of severe asthma phenotypes. Over the past decade, considerable advances have been made in understanding the pathophysiology of severe therapy-resistant asthma in children. However, asthma attacks and hospital admissions are frequent and mortality is still unacceptably high. Strategies to modify the natural history of asthma, prevent severe exacerbations, and prevent lung function decline are needed. Mechanistic studies have led to the development of several biologics targeting type 2 inflammation. This growing pipeline has the potential to reduce the burden of severe asthma; however, detailed assessment and characterisation of each child with seemingly severe asthma is necessary so that the most effective and appropriate management strategy can be implemented. Risk stratification, remote monitoring, and the integration of multiple data sources could help to tailor management for the individual child with severe asthma.
T2-“Low” Asthma: Overview and Management Strategies
2020, Journal of Allergy and Clinical Immunology: In Practice
Although the term “asthma” has been applied to all patients with airway lability and variable chest symptoms for centuries, phenotypes of asthma with distinct clinical and molecular features that may warrant different treatment approaches are well recognized. Patients with type 2 (T2)-“high” asthma are characterized by upregulation of T2 immune pathways (ie, IL-4 and IL-13 gene sets) and eosinophilic airway inflammation, whereas these features are absent in patients with T2-“low” asthma and may contribute to poor responsiveness to corticosteroid treatment. This review details definitions and clinical features of T2-“low” asthma, potential mechanisms and metabolic aspects, pediatric considerations, and potential treatment approaches. Priority research questions for T2-“low” asthma are also discussed.
Asthma-COPD Overlap and Chronic Airflow Obstruction: Definitions, Management, and Unanswered Questions
2020, Journal of Allergy and Clinical Immunology: In Practice
Citation Excerpt :
Data on the effect of FAO on the frequency of acute exacerbations are conflicting.5,14,16 Asthmatic patients with FAO may also respond differently to inhaled medications.17,18 Multiple reports have shown that asthmatic patients with FAO are prescribed higher doses of inhaled corticosteroids and use reliever medications more frequently17-19; this may reflect greater steroid resistance, or the prescribing habits of physicians attempting to normalize lung function by escalating steroid doses.
Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) is a common clinical presentation of chronic airways disease in which patients show some features usually associated with asthma, and some usually associated with COPD. There is ongoing debate over whether ACO is a discrete clinical entity, or if it is part of a continuum of airways disease. Furthermore, there is considerable variation among current definitions of ACO, which makes diagnosis potentially challenging for clinicians. Treating ACO may be equally challenging because ACO is an understudied population, and the evidence base for its management comes largely from asthma and COPD studies, the relevance of which deserves careful consideration. In this review, we synthesize the various approaches to ACO diagnosis and evaluate the role of currently available diagnostic tests. We describe the potential benefits of existing asthma and COPD therapies in treating patients with ACO, and the value of a “treatable traits” approach to ACO management. Throughout the review, we highlight some of the pressing, unanswered questions surrounding ACO that are relevant to the clinical community. Ultimately, addressing these questions is necessary if we are to improve clinical outcomes for this complex and heterogeneous patient population.
It's Time to Start Phenotyping Our Patients with Asthma
2019, Immunology and Allergy Clinics of North America
Citation Excerpt :
This finding led to several studies that examined children with asthma and attempted to better define underlying phenotypes (Table 1). Similar to the adult studies, children were grouped into clusters with phenotypic characteristics focused primarily on atopy, airway physiology, symptom onset, and asthma symptom days and exacerbations.15–18 In a study by Fitzpatrick and colleagues,15 cluster analysis similar to that used in the adult Severe Asthma Research Program identified four clusters of patients.

View all citing articles on Scopus

: This study was supported by the Clinical and Translational Science Award (CTSA) program through the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS) UL1TR000427 and National Heart, Lung, and Blood Institute (NHLBI) Fellowship F30HL112491. The study was also supported by grants (5U10HL064287, 5U10HL064288, 5U10HL064295, 5U10HL064307, 5U10HL064305, and 5U10HL064313) from the NHLBI; a grant (5UL1RR02499204) from the Washington University School of Medicine CTSA Infrastructure for Pediatric Research; a grant (1UL1RR025011) from the Madison CTSA; a grant (UL1RR025780) to the Colorado CTSA from the National Center for Research Resources; and grants to the General Clinical Research Centers at Washington University School of Medicine (M01 RR00036), National Jewish Health (M01 RR00051), and the University of New Mexico (5M01 RR00997).

: Disclosure of potential conflict of interest: T. S. Chang has received research support from the National Institutes of Health (NIH)/National Center for Research Resources, NIH/National Heart, Lung, and Blood Institute (NHLBI), and NIH/Medical Scientist Training Program. R. F. Lemanske, Jr has received research support, travel support, and fees for participation in review activities from the NIH; has received consultancy fees from Merck, Sepracor, SA Boney and Associates Ltd, GlaxoSmithKline (GSK), American Institute of Research, Genentech, Inc, Double Helix Development, Inc, and Boehringer Ingelheim; is employed by the University of Wisconsin School of Medicine and Public Health; has received research support from the NHLBI and Pharmaxis; has received lecture fees from Michigan Public Health Institute, Allegheny General Hospital, the American Academy of Pediatrics, West Allegheny Health Systems, California Chapter 4 AAP, the Colorado Allergy Society, Pennsylvania Allergy and Asthma Association, Harvard Pilgrim Health, California Society of Allergy, the NYC Allergy Society, the World Allergy Organization, the American College of Chest Physicians, Asia Pacific Association of Pediatric Allergy, Respirology and Immunology, and the Western Society of Allergy, Asthma, and Immunology; has received payment for manuscript preparation from the American Academy of Allergy, Asthma & Immunology (AAAAI); and receives royalties from Elsevier and UpToDate. D. T. Mauger has received research support from the NIH/NHLBI; has received provision of a study drug from GSK and Merck; and has received consultancy fees from GSK, Merck, Boehringer Ingelheim, and Biocryst. A. M. Fitzpatrick has received consultancy fees from MedImmune, Inc, Consulting, Merck Scientific Advisory Board, GSK Scientific Advisory Board, and Genentech Consulting. C. A. Sorkness has received research support from the NHLBI Care Network. S. J. Szefler has received research support, travel support, fees for participation in review activities, and payment for writing/reviewing the manuscript from the NHLBI; has received consultancy fees from Merck, Genentech, Boehringer Ingelheim, and GSK; has received research support from GSK; has received lecture fees from Merck; has received payment for manuscript preparation from Genentech; and has a previously submitted patent with the NHLBI. C. D. Page has received research support from the NIH and has received consultancy fees from MedSeek. D. J. Jackson has received research support from the NIH and Pharmaxis and has received consultancy fees from Gilead and GSK. R. E. Gangnon declares that he has no relevant conflicts of interest.

View full text

Asthma and lower airway diseaseChildhood asthma clusters and response to therapy in clinical trials

Background

Objective

Methods

Results

Conclusions

Section snippets

Methods

Classification model and assignment

Discussion

Lancet

J Allergy Clin Immunol

J Allergy Clin Immunol

J Allergy Clin Immunol

J Allergy Clin Immunol

J Allergy Clin Immunol

Cluster analysis and clinical asthma phenotypes

Am J Respir Crit Care Med

Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program

Am J Respir Crit Care Med

Steroid resistance in severe asthma: current mechanisms and future treatment

Curr Pharm Des

Gene-expression profiles in human nasal polyp tissues and identification of genetic susceptibility in aspirin-intolerant asthma

Clin Exp Allergy

Asthma and lower airway disease
Childhood asthma clusters and response to therapy in clinical trials