Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications

Judie A. Howrylak, Anne L. Fuhlbrigge, Robert C. Strunk, Robert S. Zeiger, Scott T. Weiss, Benjamin A. Raby

Research output: Contribution to journalArticle

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Abstract

Background Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been explored. Objective Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. Methods We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. Results We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone (P <.0001) or additional controller medications (P =.001), as well as longitudinal differences in pulmonary function (P <.0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide (P =.02) and nedocromil (P =.01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide (P =.12) and nedocromil (P =.56) compared with placebo. Conclusion Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design.

Original languageEnglish (US)
Pages (from-to)1289-1300.e12
JournalJournal of Allergy and Clinical Immunology
Volume133
Issue number5
DOIs
StatePublished - May 2014

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Anti-Inflammatory Agents
Asthma
Nedocromil
Phenotype
Budesonide
Cluster Analysis
Placebos
Lung
Airway Obstruction
Random Allocation
Prednisone
Adrenal Cortex Hormones
Clinical Trials
Therapeutics

All Science Journal Classification (ASJC) codes

  • Immunology and Allergy
  • Immunology

Cite this

Howrylak, Judie A. ; Fuhlbrigge, Anne L. ; Strunk, Robert C. ; Zeiger, Robert S. ; Weiss, Scott T. ; Raby, Benjamin A. / Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications. In: Journal of Allergy and Clinical Immunology. 2014 ; Vol. 133, No. 5. pp. 1289-1300.e12.
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Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications. / Howrylak, Judie A.; Fuhlbrigge, Anne L.; Strunk, Robert C.; Zeiger, Robert S.; Weiss, Scott T.; Raby, Benjamin A.

In: Journal of Allergy and Clinical Immunology, Vol. 133, No. 5, 05.2014, p. 1289-1300.e12.

Research output: Contribution to journalArticle

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AU - Howrylak, Judie A.

AU - Fuhlbrigge, Anne L.

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AU - Weiss, Scott T.

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N2 - Background Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been explored. Objective Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. Methods We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. Results We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone (P <.0001) or additional controller medications (P =.001), as well as longitudinal differences in pulmonary function (P <.0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide (P =.02) and nedocromil (P =.01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide (P =.12) and nedocromil (P =.56) compared with placebo. Conclusion Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design.

AB - Background Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been explored. Objective Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. Methods We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. Results We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone (P <.0001) or additional controller medications (P =.001), as well as longitudinal differences in pulmonary function (P <.0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide (P =.02) and nedocromil (P =.01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide (P =.12) and nedocromil (P =.56) compared with placebo. Conclusion Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design.

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