Open Access
RESEARCH ARTICLE
Application of the Asthma Phenotype Algorithm from the Severe Asthma Research Program to an Urban Population
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1 Division of Pulmonary and Critical Care Medicine, Department of Medicine, New York University School of Medicine, New York, New York, United States of America,2 Environmental Medicine, New York University School of Medicine, New York, New York, United States of America
Abstract Top
Rationale
Identification and characterization of asthma phenotypes are challenging due to disease complexity and heterogeneity. The Severe Asthma Research Program (SARP) used unsupervised cluster analysis to define 5 phenotypically distinct asthma clusters that they replicated using 3 variables in a simplified algorithm. We evaluated whether this simplified SARP algorithm could be used in a separate and diverse urban asthma population to recreate these 5 phenotypic clusters.
Methods
The SARP simplified algorithm was applied to adults with asthma recruited to the New York University/Bellevue Asthma Registry (NYUBAR) to classify patients into five groups. The clinical phenotypes were summarized and compared.
Results
Asthma subjects in NYUBAR (n = 471) were predominantly women (70%) and Hispanic (57%), which were demographically different from the SARP population. The clinical phenotypes of the five groups generated by the simplified SARP algorithm were distinct across groups and distributed similarly to those described for the SARP population. Groups 1 and 2 (6 and 63%, respectively) had predominantly childhood onset atopic asthma. Groups 4 and 5 (20%) were older, with the longest duration of asthma, increased symptoms and exacerbations. Group 4 subjects were the most atopic and had the highest peripheral eosinophils. Group 3 (10%) had the least atopy, but included older obese women with adult-onset asthma, and increased exacerbations.
Conclusions
Application of the simplified SARP algorithm to the NYUBAR yielded groups that were phenotypically distinct and useful to characterize disease heterogeneity. Differences across NYUBAR groups support phenotypic variation and support the use of the simplified SARP algorithm for classification of asthma phenotypes in future prospective studies to investigate treatment and outcome differences between these distinct groups.
Trial Registration
Clinicaltrials.gov NCT00212537
Citation: Patrawalla P, Kazeros A, Rogers L, Shao Y, Liu M, et al. (2012) Application of the Asthma Phenotype Algorithm from the Severe Asthma Research Program to an Urban Population. PLoS ONE 7(9): e44540. doi:10.1371/journal.pone.0044540
Editor: Christian Taube, Leiden University Medical Center, The Netherlands
Received: May 1, 2012; Accepted: August 3, 2012; Published: September 13, 2012
Copyright: © 2012 Patrawalla et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the Colton Family Foundation, and the National Institutes of Health (Grants T32 ES007267, M01RR00096). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: joan.reibman@nyumc.org
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