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Impulse oscillometry versus spirometry in a long-term study of controller therapy for pediatric asthma.

ABSTRACT: Determination of the benefits and limitations of specific physiologic tests has not been well studied in long-term clinical pediatric trials.We sought to determine the utility of impulse oscillometry in a long-term comparison of 3 controller regimens in children with persistent asthma.Children 6 to 14 years of age with mild-to-moderate persistent asthma were characterized with oscillometry and spirometry before entry into a clinical trial and then serially during 48 weeks of therapy with either an inhaled corticosteroid, a combination inhaled corticosteroid with a long-acting beta-agonist, or a leukotriene receptor antagonist.The FEV(1)/forced vital capacity ratio, as well as the forced expiratory flow from 25% to 75% of forced vital capacity in terms of spirometric parameters and the reactance area (XA) from impulse oscillometry, appeared to complement information provided by FEV(1) when comparing the tests and factors that appeared to predict a response to treatment. XA was unique in that it, as distinct from spirometric variables, reflected ongoing improvement during the latter part of the trial. In general, improvements in XA during the latter part of the study occurred independently of indices of atopy and the level of airway responsiveness.Assessment of respiratory mechanics over time with oscillometry might offer additional insights into the response of asthmatic patients to therapy. In particular, the pattern of improvement seen in XA over the course of therapy suggests this test might detect alterations in airway mechanics not reflected by spirometry. The possibility that changes in XA reflect ongoing improvement in small airway function deserves additional study.

SUBMITTER: Larsen GL

PROVIDER: S-EPMC4291457 | biostudies-other | 2009 Apr

REPOSITORIES: biostudies-other

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Impulse oscillometry versus spirometry in a long-term study of controller therapy for pediatric asthma.

Larsen Gary L GL Morgan Wayne W Heldt Gregory P GP Mauger David T DT Boehmer Susan J SJ Chinchilli Vernon M VM Lemanske Robert F RF Martinez Fernando F Strunk Robert C RC Szefler Stanley J SJ Zeiger Robert S RS Taussig Lynn M LM Bacharier Leonard B LB Guilbert Theresa W TW Radford Shelley S Sorkness Christine A CA

The Journal of allergy and clinical immunology 20081212 4

<h4>Background</h4>Determination of the benefits and limitations of specific physiologic tests has not been well studied in long-term clinical pediatric trials.<h4>Objective</h4>We sought to determine the utility of impulse oscillometry in a long-term comparison of 3 controller regimens in children with persistent asthma.<h4>Methods</h4>Children 6 to 14 years of age with mild-to-moderate persistent asthma were characterized with oscillometry and spirometry before entry into a clinical trial and ...[more]

PMID: 19070356

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Project description:BackgroundAsthma management guidelines recommend a stepwise approach to instituting and adjusting anti-inflammatory controller therapy for children with asthma. The objective of this retrospective observational study was to describe prescribing patterns of asthma controller therapies for children in a primary care setting.MethodsData from the UK General Practice Research Database were examined for children with recorded asthma or recurrent wheezing who, from September 2006 through February 2007, were < or = 14 years old at the time of a first asthma controller prescription after > or = 6 months without a controller prescription. We evaluated demographic characteristics, asthma duration, comorbidities, asthma-related health care resource use, and prescribed daily dose of controller medication. In addition, physicians for 635 randomly selected patients completed a survey retrospectively classifying asthma severity at the prescription date and describing therapy and health care utilization for 6 prior months.ResultsWe identified 10,004 children, 5942 (59.4%) of them boys, of mean (SD) age of 8.0 (3.8) years. Asthma controller prescriptions were for inhaled corticosteroid (ICS) monotherapy for 9059 (90.6%) children; ICS plus long-acting beta2-agonist (LABA) for 698 (7.0%); leukotriene antagonist monotherapy for 91 (0.9%); ICS plus leukotriene antagonist for 55 (0.6%); and other therapy for 101 (1.0%), including 45 (0.45%) children who were prescribed LABA as monotherapy. High doses of ICS (> 400 microg) were prescribed for 44/2140 (2.1%) children < 5 years old and for 420/7452 (5.6%) children > or = 5 years. Physicians reported asthma severity as intermittent for 346/635 (55%) patients and as mild, moderate, and severe persistent for 159 (25%), 71 (11%), and 11 (2%), respectively (severity data missing for 48 [8%]). The baseline characteristics and controller therapy prescriptions of the survey cohort were similar to those of the full cohort.ConclusionsPhysician classifications of asthma severity did not always correspond to guideline recommendations, as leukotriene receptor antagonists were rarely used and high-dose ICS or add-on LABA was prescribed even in intermittent and mild disease. In UK primary care, monotherapy with ICS is the most common controller therapy at all levels of asthma severity.

Project description:RationalePediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based on the relationship between treatment and clinical outcome has not been performed, and machine learning approaches for long-term outcome prediction in pediatric asthma have not been studied in depth.ObjectivesOur objectives were to use our novel machine learning algorithm, predictor pursuit (PP), to discover pediatric asthma phenotypes on the basis of asthma control in response to controller medications, to predict longitudinal asthma control among children with asthma, and to identify features associated with asthma control within each discovered pediatric phenotype.MethodsWe applied PP to the Childhood Asthma Management Program study data (n = 1,019) to discover phenotypes on the basis of asthma control between assigned controller therapy groups (budesonide vs. nedocromil). We confirmed PP's ability to discover phenotypes using the Asthma Clinical Research Network/Childhood Asthma Research and Education network data. We next predicted children's asthma control over time and compared PP's performance with that of traditional prediction methods. Last, we identified clinical features most correlated with asthma control in the discovered phenotypes.ResultsFour phenotypes were discovered in both datasets: allergic not obese (A+/O-), obese not allergic (A-/O+), allergic and obese (A+/O+), and not allergic not obese (A-/O-). Of the children with well-controlled asthma in the Childhood Asthma Management Program dataset, we found more nonobese children treated with budesonide than with nedocromil (P = 0.015) and more obese children treated with nedocromil than with budesonide (P = 0.008). Within the obese group, more A+/O+ children's asthma was well controlled with nedocromil than with budesonide (P = 0.022) or with placebo (P = 0.011). The PP algorithm performed significantly better (P < 0.001) than traditional machine learning algorithms for both short- and long-term asthma control prediction. Asthma control and bronchodilator response were the features most predictive of short-term asthma control, regardless of type of controller medication or phenotype. Bronchodilator response and serum eosinophils were the most predictive features of asthma control, regardless of type of controller medication or phenotype.ConclusionsAdvanced statistical machine learning approaches can be powerful tools for discovery of phenotypes based on treatment response and can aid in asthma control prediction in complex medical conditions such as asthma.

Project description:ObjectivesElite controllers (ECs), viraemic controllers (VCs), and long-term nonprogressors (LTNPs) control HIV viral replication or maintain CD4 T-cell counts without antiretroviral therapy, but may have increased cardiovascular disease (CVD) risk compared to HIV-uninfected persons. We evaluated subclinical carotid and coronary atherosclerosis and inflammatory biomarker levels among HIV controllers, LTNPs and noncontrollers and HIV-uninfected individuals in the Multicenter AIDS Cohort Study (MACS) and the Women's Interagency HIV Study (WIHS).MethodsWe measured carotid plaque presence and common carotid artery intima-media thickness (IMT) in 1729 women and 1308 men, and the presence of coronary artery calcium and plaque in a subgroup of men. Associations between HIV control category and carotid and coronary plaque prevalences were assessed by multivariable regression analyses adjusting for demographics and CVD risk factors. Serum inflammatory biomarker concentrations [soluble CD163 (sCD163), soluble CD14 (sCD14), galectin-3 (Gal-3), galectin-3 binding protein (Gal-3BP) and interleukin (IL)-6] were measured and associations with HIV control category assessed.ResultsWe included 135 HIV controllers (30 ECs) and 135 LTNPs in the study. Carotid plaque prevalence and carotid IMT were similar in HIV controllers, LTNPs and HIV-uninfected individuals. HIV controllers and LTNPs had lower prevalences of carotid plaque compared to viraemic HIV-infected individuals. The prevalence of coronary atherosclerosis was similar in HIV controllers/LTNPs compared to HIV-uninfected and viraemic HIV-infected men. Controllers and LTNPs had higher concentrations of sCD163 and sCD14 compared to HIV-uninfected persons.ConclusionsSubclinical CVD was similar in HIV controllers, LTNPs and HIV-uninfected individuals despite elevated levels of some inflammatory biomarkers. Future studies of HIV controllers and LTNPs are needed to characterize the risk of CVD among HIV-infected persons.

Dataset Information

Impulse oscillometry versus spirometry in a long-term study of controller therapy for pediatric asthma.

Publications

Impulse oscillometry versus spirometry in a long-term study of controller therapy for pediatric asthma.

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