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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Allergy Clin Immunol. Author manuscript; available in PMC Aug 1, 2010.
Published in final edited form as:
PMCID: PMC2757267
NIHMSID: NIHMS133047
Asthma morbidity among inner-city adolescents receiving guidelines-based therapy: Role of predictors in the setting of high adherence
Rebecca S. Gruchalla, MD, PhD, Hugh A. Sampson, MD, Elizabeth Matsui, MD, Gloria David, PhD, MHSc, Peter J. Gergen, MD, MPH, Agustin Calatroni, MA, MS, Mark Brown, MD, Andrew H. Liu, MD, Gordon R. Bloomberg, MD, James F. Chmiel, MD, Rajesh Kumar, MD, Carin Lamm, MD, Ernestine Smartt, RN, Christine A. Sorkness, PharmD, Suzanne F. Steinbach, MD, Kelly D. Stone, MD, PhD, Stanley J. Szefler, MD, and William W. Busse, MD
Rebecca S. Gruchalla, University of Texas Southwestern Medical Center, Dallas, TX;
Corresponding author Rebecca S. Gruchalla, MD, PhD University of Texas Southwestern Medical Center 5323 Harry Hines Blvd. Dallas, TX 75390-8859 Phone: (214) 648-6370 Fax: (214) 648-9100 ; Rebecca.Gruchalla/at/utsouthwestern.edu
Background
With the expanding effort to provide guidelines-based therapy to adolescents with asthma, attention must be directed to evaluating which factors predict future asthma control when guidelines-based management is applied.
Objective
We evaluated the role of FeNO, markers of allergic sensitization, airway inflammation and measures of asthma severity in determining future risk of asthma symptoms and exacerbations in adolescents and young adults participating in the Asthma Control Evaluation (ACE) study.
Methods
Five hundred forty-six inner-city residents, ages 12 through 20 years, with persistent asthma were extensively evaluated at study entry for predictors of future symptoms and exacerbations over the subsequent 46-weeks during which guidelines-based, optimal asthma management was offered. Baseline measurements included: FeNO, total IgE, allergen-specific IgE, allergen skin test reactivity, asthma symptoms, lung function, peripheral blood eosinophils, and, for a subset, airway hyperresponsiveness and sputum eosinophils.
Results
The baseline characteristics we examined accounted for only a small portion of the variance for future maximum symptom days and exacerbations, 11.4% and 12.6%, respectively. Future exacerbations were somewhat predicted by asthma symptoms, albuterol use, previous exacerbations and lung function while maximum symptom days were predicted , also to a modest extent, by symptoms, albuterol use and previous exacerbations but not lung function.
Conclusion
Our findings demonstrate that the usual predictors of future disease activity have little predictive power when applied to a highly-adherent, persistent asthma population that is receiving guidelines-based care. Thus, new predictors need to be identified that will be able to measure the continued fluctuation of disease that persists in highly adherent, well-treated populations such as the one studied.
Keywords: asthma, exhaled nitric oxide, inner-city, allergic sensitization, airway inflammation, asthma severity
Asthma is a complex disease of the airways that is characterized by variable and recurring symptoms, airflow obstruction, bronchial hyperresponsiveness and underlying inflammation. The interrelationships between these various features determine the clinical manifestations, influence the severity of the disease processes, and serve as a target for treatment in asthma.
The most recent Expert Panel Report 3 (EPR 3): Guidelines for the Diagnosis and Management of Asthma 1 recommend assessing asthma severity and achieving control as key components to effective asthma care. Assessments of asthma severity and control incorporate two important domains, which are distinct but likely interrelated: 1) current impairment, i.e. the frequency and intensity of symptoms and functional limitations; and 2) future risk, i.e. the likelihood of asthma exacerbations or progressive loss of lung function. 2 An unresolved question is whether baseline asthma assessments, atopic status and airway inflammation can predict future asthma control i.e., the level of impairment and exacerbation frequency in the face of guidelines-based management.
The above question constitutes the focus of this report. More specifically, we first sought to examine what participant characteristics best predict future asthma symptoms and exacerbations among asthma patients receiving guidelines-directed treatment and who are adherent to this treatment. To answer this question, we evaluated, not only baseline measurements of current impairment (asthma symptoms), but also, a number of additional objective measurements that reflect airway inflammation (FeNO, sputum and blood eosinophilia), atopic status (total IgE, number of positive skin tests, specific IgE against common aeroallergens) and lung function (FEV1 percent predicted, FEV1/FVC, and post-bronchodilator percent change in FEV1). In addition, we analyzed the relationship among FeNO, asthma symptoms, other markers of inflammation, atopy and lung function.
The aims of this study were secondary aims of the Asthma Control Evaluation (ACE) study, which was implemented to determine whether guidelines-directed treatment, supplemented by FeNO as a biomarker, would improve asthma outcomes compared to a guidelines-based approach alone in a high risk inner-city population. 3
Study Population and Design
In brief, 546 participants, aged 12 to 20 years, with physician-diagnosed asthma were enrolled at 10 urban locations across the United States. Eligibility was limited to residents of census tracts in which at least 20% of households had incomes below the federal poverty threshold. In addition, individuals had to have evidence of moderate to severe persistent disease. Those receiving long-term control therapy were required to have symptoms of persistent disease or uncontrolled asthma while those who were not on long term control therapy had to have symptoms of persistent asthma and evidence of uncontrolled disease 1, 3. Participants had to sleep at least 4 nights per week in one home (to ensure consistent exposure to the same household environment) and had to be a non-smoker for 1 year prior to recruitment with a urinary cotinine level < 100 ng/mL at enrollment. All appropriate institutional review boards approved this study. Written informed consent was obtained from each participant or their parent or legal guardian. Adolescents ages 12 to 17 provided assent.
The ACE study was a randomized, double-blind, parallel-group trial with a 3-week run-in to characterize participants, establish asthma treatment, and evaluate adherence. After run-in, participants were randomized to either a Reference Group (guidelines-based care) or FeNO Group (exhaled nitric oxide (eNO) added to guidelines-based care) for a 46-week treatment period. Follow-up visits were conducted every 6 to 8 weeks during the treatment period. Findings presented in the current manuscript relate to data collected at the enrollment visit (Week 0), 3 weeks later at the randomization visit (Week 3), and during the follow-up period (Weeks 9 [visit 3] through 49 [visit 8]). From Week 0 to week 49, study participants received guidelines-directed asthma treatment using algorithms prepared by the study investigators. 3 Treatment of all participants included inhaled corticosteroids (fluticasone) at various doses with or without long-acting beta adrenergic agonists (salmeterol). More difficult-to-control participants also received cysteinyl leukotriene receptor antagonists (montelukast).
Measurement of FeNO
FeNO was measured for all study participants at the randomization visit employing a technique modified after Silkoff et al 4 and following American Thoracic Society guidelines. 5 FeNO was measured (flow rate 50 ml/s) with a rapid-response chemiluminescent analyzer (NIOX™ System, Aerocrine; Sweden). 6
Total and Allergen-specific Serum IgE
At the randomization visit, a venous blood sample was obtained from all study participants for measurement of serum total IgE and allergen-specific IgE to cockroach (Blatella germanica), house dust mites (Dermatophagoides farinae and Dermatophagoides pteronyssinus), cats (cat epithelium and dander), and mold (Alternaria alternata). Serum IgE was measured with the UniCap System (Phadia; Uppsala, Sweden).
Skin Tests
Skin testing was performed during the randomization visit by the puncture method on the volar surface of the forearm using a Multi-Test II device (Lincoln Diagnostics; Decatur, IL). Allergen extracts were obtained from Greer Laboratories (Lenoir, NC). The online repository lists the 14 extracts, concentrations, and positive and negative controls, and describes the test methods andassessment of results.
Blood eosinophils
At the randomization visit, a venous blood sample was obtained from all study participants for determination of total serum eosinophil count by local clinical laboratories.
Sputum Induction and Processing
A subset of participants from four research sites (Dallas, Denver, New York, and Tucson) underwent sputum induction at the randomization visit. Sputum was induced by inhalation of hypertonic saline solution (3%) as previously described by Fahy et al7using a DeVilbiss Ultra-Sonic Pico #3207 nebulizer (Nouvag; Lake Hughes, CA). Participants with pre-albuterol FEV1 ≥ 70% of predicted (206 of 213, 97%; 1 of 206 refused) underwent sputum induction following pre-treatment with albuterol. Slides were prepared and stained at the local laboratories. Differential cell counts were performed centrally by a blinded technician. Refer to online repository for specific details regarding sputum analysis.
Spirometry
Spirometry was performed by certified technicians, according to American Thoracic Society standards,8 using a Jaeger Masterscreen (VIASYS Healthcare GmbH; Hoechberg, FRG). Spirometry was performed pre- and post-bronchodilator treatment at baseline, using 4 puffs of albuterol MDI administered via Aerochamber®. All pulmonary function tests were centrally overread for quality control purposes; the overreading failures, which account for slightly over 3% (171/5169) of all procedures performed, have been excluded from analysis.
Methacholine Challenge
At the randomization visit, a subset of participants from four research sites (Dallas, Denver, New York, and Tucson) underwent methacholine challenge testing as previously described by Strunk et al. 9 Airway responsiveness was measured by determining the concentration of methacholine required to produce a drop in FEV1 of 20% compared to a control (post-diluent) level (PC20) after the administration of increasing concentrations of methacholine using the small volume nebulizer-tidal breathing technique. Refer to online repository for specific details regarding the methacholine challenge procedure. Individuals who did not reach PC20 (37 of 144, 26%) were assigned an upper limit of detection of 26 mg/ml. All methacholine challenge procedures and interpretations were overread for purposes of quality assurance; the overreading failures (37 of 181, 20%) have been excluded from analysis.
Asthma Impairment and Risk Outcomes
The primary outcomes were maximum symptom days and exacerbations. Maximum symptom days per two-week recall and exacerbations were assessed at each visit during the 46-week treatment period. Maximum symptom days, as used in previous inner-city asthma studies, 10, 11 were defined as the largest value among the following variables reported over the prior 2 weeks: (1) number of days with wheezing, chest tightness or cough; (2) number of nights of sleep disturbance; and (3) number of days when activities were affected. This measure allows asthma symptoms to be correctly gauged whether the study participant expresses their asthma as reduction in play, sleep disturbance, or wheeze. An asthma exacerbation was defined as a hospitalization, unscheduled visit (including emergency department visits), or prednisone course for asthma.
Statistical Analyses
Partial Pearson's correlations were calculated for the entire study population to measure the strength of relationships between two variables, while controlling the effect of site, race, age and study group. The primary objective of these analyses was the identification of predictors of future asthma control while receiving guidelines-based therapy. Symptoms and FeNO at randomization, not baseline, were used since only at randomization, after the 3-week run-in, were the participants receiving well-characterized standardized asthma medical management. Similar analyses were also performed for the Reference Group (guidelines-based care) only (n=270) and no significant differences were apparent (data not shown).
Multivariate analyses were carried out on the average maximum symptom days and exacerbations during follow-up. Longitudinal analyses were not possible because post-randomization exacerbation values were sparse. The order in which the variables were entered into the analyses was set a priori based on ease and cost of obtaining the clinical measurements. To maximize the sample size for these analyses (N=477), we excluded variables obtained only on a subset of participants (methacholine PC20 and sputum eosinophils).
The purpose of relative importance is to quantify the relative contribution of an individual variable to the model's total explanatory value. 12 To control for the study design and possible confounders, we adjusted these analyses for study group, site, race and age. Assessment of relative importance in multivariate analysis is simple when all variables are uncorrelated. Each variable contribution is just the R2 from univariate regression, and all univariate R2 values add up to the full model R2. When variables are correlated, the order in which the variables are entered into the model affect their relative contribution. The effects of this ordering can be minimized by averaging sequential sums of squares over all possible orderings of variables, decomposing R2 into non-negative contributions. These are computer-intensive methods that have been achievable recently as a result of the advances in computational capabilities. To examine further the relation between the individual variables and FeNO, we combined them into a priori specific domains and determined 95% confidence intervals through bootstrap (5000 bootstrap samples) to assess the variability of the relative importance and investigate pairwise differences.
Log-transformations of skewed data (FeNO, methacholine PC20, total IgE, allergen-specific IgE, sum of the five allergen-specific IgEs, blood and sputum eosinophils) were used for partial correlations and multivariate analyses. A p-value of < 0.05 was considered statistically significant. All statistical analyses were performed using SAS statistical software version 9.1 (SAS Institute Inc; Cary, NC) and the R system for statistical computing version 2.7.0. 13 The calculation of relative importance was conducted using the R add-on package relaimpo. 14
Participant Characteristics at Randomization (Table 1)
Of the 546 participants enrolled, 53% were male and 64% were African American. Table 1 describes additional demographic characteristics of the population as well as asthma-related symptoms, lung function, atopic status and degree of allergic inflammation at randomization. The mean number of maximum symptom days over a 2-week period decreased significantly from 5.6 ± 4.6 at enrollment to 2.3 ± 2.9 after the 3-week run-in period at randomization (mean within participant reduction: 3.4 days/2 weeks, p<0.001). Mean FEV1 (% of predicted value) at randomization was 95.8% ± 15.7. Despite the decrease in maximum symptom days between enrollment and randomization, half of the participants (274 of 546) had FeNO levels ≥ 20 ppb and 75% (401 of 534) had serum IgE levels ≥ 100 kU/L at randomization. Moreover, twenty-six percent (40 of 157) had sputum eosinophilia defined as an eosinophil % of sputum white blood cells ≥ 2%. 15 Marked airway hyperresponsiveness also existed with 62% (89 of 144) having a PC20 < 8 mg/ml. Finally, the majority of participants had one or more positive skin tests (88%) with the median number of positive tests being 5 of 14 total tests placed (interquartile range 2-7). Allergic sensitization was most prevalent to cockroach (61.2%), cat (58.2%), molds (51.6%), and dust mites (46.9%). In addition to skin testing, allergen-specific IgE levels were measured for five allergens (Alternaria alternata, cat, D. pteronyssinus, D. farinae, and German cockroach), (Table 1). For each of the allergens tested, between 40 and 50% of the participants had allergen-specific IgE levels greater than 0.35 kUA/L.
Adherence to treatment was 88.6% at randomization and averaged 86.6% during follow-up (Visits 3-8). Despite these high level of adherence, 388 of 539 (72%) ACE participants with follow-up data had at least one visit with poor asthma control (more than 3 days of symptoms or 1 night of symptoms in 2 weeks or FEV1 < 80% of personal best) of which 137 (25%) had even more severe morbidity (14 days of symptoms or more than 4 nights of symptoms in the last 2 weeks or FEV1 < 70% of personal best).
Table 1
Table 1
Participant Characteristics at Randomization* (N=546)
Importance of different variables (asthma-related symptoms, lung function, allergic biomarkers, and inflammatory biomarkers) in predicting future symptoms and exacerbations
We sought to determine which clinical variables measured at randomization were best associated with future risk of asthma exacerbations and maximum symptom days (both measures of risk were assessed during the follow-up period, i.e. study weeks 9 through 49). As shown in Table 2, modest but significant correlations were demonstrated between several asthma-related symptom variables and future maximum symptom days and exacerbations. Maximum symptom days (r=0.25, p<0.001), days of albuterol use (r=0.27, p<0.001), and nights of albuterol use (r=0.19, p<0.001), measured at randomization, all predicted future maximum symptom days. The latter two variables (days of albuterol use [r=0.13, p=0.003] and nights of albuterol use [r=0.21, p<0.001]) also correlated with future exacerbations as did post-bronchodilator percent change in FEV1 at enrollment (r=0.19, p<0.001), and FEV1/FVC ratio (r=−0.10, p=0.026) and FeNO (r=0.11, p=0.010) measured at the randomization visit. Neither methacholine sensitivity nor any of the allergic or inflammatory biomarkers (except FeNO as noted) were associated with maximum symptom days or exacerbations measured during the 46 weeks of follow-up.
Table 2
Table 2
Pearson correlations of baseline participant characteristics with follow-up symptoms and exacerbations (Visits 3 – 8).*
When using relative importance measures, asthma symptom variables, especially albuterol use, independently explained most of the variability in future maximum symptom days (R2=6.2%) and exacerbations (R2=5.8%) (Figure 1). Post-bronchodilator percent change in FEV1 also was found to play a role in explaining future exacerbations. Table 3 presents three different models that evaluate the additional contribution of FeNO to various combinations of conventionally-measured parameters in predicting future maximum symptom days and asthma exacerbations. For model 1, symptoms, which are a composite of four variables and FeNO were the only predictors considered; for model 2, symptoms, lung function measurements, and FeNO were considered; and for model 3, symptoms, lung function measurements, inflammatory and allergic biomarkers, and FeNO were considered. As shown, asthma-related symptoms alone (days with symptoms, days and nights of albuterol use in the 2 weeks prior to randomization, and exacerbations in the year prior to enrollment) explained future maximum symptom days and exacerbations variance significantly (R2 =9.9% [p<0.05] for maximum symptom days; R2= 8.6% [p<0.001] for exacerbations). The addition of lung function measurements to asthma-related symptoms significantly increased the percent of variation explained for future exacerbations (models 2 and 3) (R2=3.3% [p<0.001]) but not for maximum symptom days. None of the other variables (inflammatory markers, atopic markers, or FeNO) further contributed to the prediction of either future maximum symptom days or exacerbations.
Figure 1
Figure 1
Relative importance of baseline characteristics for predicting maximum symptom days (Panel A) and exacerbations (Panel B) during follow-up (Visits 3 to 8). Combined these baseline characteristics explain 11.4 and 12.6 percent of the variation for maximum (more ...)
Table 3
Table 3
Percent of variation in follow-up asthma outcomes explained by symptoms, lung function, biomarkers and FeNO as measured at randomization*
Correlations between FeNO and asthma-related symptoms, lung function, and allergic and winflammatory biomarkers measured at randomization
We found significant correlations between FeNO and all the parameters evaluated, except for most asthma-related symptom measurements (Table 4). The strongest correlation was between FeNO and PC20 (r=−0.49, p<0.001). Moderate correlations were seen between FeNO and other lung function parameters (post-bronchodilator percent change in FEV1 [r=0.31, p<0.001]; FEV1 % predicted [r=−0.16, p<0.001]; FEV1/FVC [r=−0.29, p<0.001]) as well as with allergic biomarkers (total IgE [r=0.37, p<0.001]; sum of the five allergen-specific IgEs [r=0.35, p<0.001]) and inflammatory biomarkers (blood eosinophils [r=0.39, p<0.001]; sputum eosinophils [r=0.38, p<0.001]). Amongst the symptom variables, maximum symptom days had a small, but significant correlation (r=0.09, p=0.044) with FeNO, but other variables such as school days missed and days and nights of albuterol use showed no significant correlation.
Table 4
Table 4
Pearson correlations of participant characteristics with FeNO at randomization*
Relative importance of different parameters for determining FeNO at randomization
Using multivariate analyses, we focused on the relative importance of various parameters in determining FeNO. As shown in Figure 2 Panel A, PC20 (R2=13.8%) and FEV1/FVC ratio (R2=8.5%) explained most of the variability of FeNO, followed by the number of positive skin tests and sputum/blood eosinophils. All parameters considered together accounted for 50.3% of the FeNO variance. In Figure 2 Panel B, the various parameters were grouped into specific domains: lung function (methacholine PC20, FEV1/FVC, FEV1 % of predicted, and post-bronchodilator percent change in FEV1, inflammation (blood and sputum eosinophils), atopy (number of positive skin tests, total IgE, and sum of the five allergen-specific IgEs) and symptoms (maximum symptom days, days of albuterol use, nights of albuterol use, and exacerbations). Once again, the lung function (R2=26.0%) domain explained most of the FeNO variability followed by the inflammation (R2=12.7%) and atopy (R2=8.5%) domains. There was minimal relationship between FeNO and the asthma symptom domain.
Figure 2
Figure 2
Relative importance of baseline characteristics for predicting baseline FENO. Panel A shows individual variables while panel B combines the variables into specific domains with 95% confidence interval. Domains are defined as lung function (methacholine (more ...)
Our study reveals that factors often used to predict future asthma risk in poorly- controlled populations, are of no clinical benefit in predicting future risk in a well-treated, highly adherent population of inner-city adolescents and young adults with persistent asthma. We did find that future maximum symptom days and exacerbations could be predicted, but only to a minor extent, using a combination of asthma-related symptoms and lung function measurements that included FEV1 % predicted, FEV1/FVC, and post-bronchodilator percent change in FEV1. However, these predictors explained only approximately 12.6% and 11.4% of the variance (Figure 1) for exacerbations and maximum symptom days, respectively. Moreover, the independent contributions of degree of inflammation (as measured by FeNO, sputum and blood eosinophils), and degree of atopy, all measured at randomization, were minimal.
The literature suggests that an increased risk of symptoms and exacerbations may be predicted by numerous factors including recent asthma exacerbations 16, poor asthma control17, 18, severe airway obstruction 19, 20, history of intensive care admissions or frequent emergency department visits 21, elevated FeNO levels 20, 22, allergen sensitivity and exposure 23-25, depression 26, and poor attitudes about the use of asthma medicines. 27 Moreover, numerous studies have examined baseline predictors of treatment response and loss of asthma control. Such predictor variables examined in these studies have included baseline levels of serum IgE and eosinophil cationic protein, FeNO, PC20, pulmonary function measurements and asthma symptoms. Sputum eosinophils too have been examined in longitudinal studies and have been found to be useful as a predictor of asthma deterioration after ICS reduction. 28-32
Indeed while predictors of future asthma symptoms and exacerbations have been extensively studied, no single study has evaluated all of these potential predictive factors together and none has examined these factors in a well-treated, highly adherent population. Thus, a unique attribute of our work is that, unlike previous studies, an attempt was made to identify predictors of future asthma risk in a highly adherent population of inner-city adolescents and young adults who were receiving optimal care (i.e., guidelines-based medical management) for the entire 46 weeks of follow-up. Interestingly, none of four major asthma-related factors (symptoms, lung function measurements, allergic biomarkers, and inflammatory biomarkers) measured at baseline were useful in predicting future risk of disease as measured by future asthma symptoms and exacerbations. It must be pointed out, however, that our inability to identify useful predictors was not due to resolution of disease since we found that disease activity was not completely eliminated.
Another unique aspect of our study was the type of analyses that were performed. Like Pharoah et al. 33 did in analyzing breast cancer outcomes, another polygenic disease, we applied a model that looked at predictor variables in combination, as opposed to applying a model that evaluated simple univariate correlations only. In applying this type of model, Pharoah et al. found that seven established common breast-cancer susceptibility alleles, in combination, explained only 5% of the genetic risk for this disease. In comparison, the factors we examined accounted for a little over 10% of the variance in maximum symptom days and exacerbations (11.4% and 12.6%, respectively). Importantly, we also showed that complex measurements such as methacholine sensitivity and sputum eosinophils, along with IgE measurements and blood eosinophils, did not explain any of the remaining variance of these outcomes.
In our analyses, we found that baseline FeNO levels at randomization were related to future asthma exacerbations (Table 2). However, this relationship did not hold up in our multivariate models (Figure 1, Table 3). Thus, while baseline FeNO levels were found to be correlated with a number of inflammatory or lung function measurements, this biomarker was not a good predictor of future asthma risk, as defined by future maximum symptom days and asthma exacerbations. Others too have demonstrated relationships between FeNO and allergen sensitivity 9, 34, methacholine PC20 9, 34, 35, and blood and/or sputum eosinophils. 9, 34-40 In the few studies that have found relationships between FeNO levels and future exacerbations 20, 22, 41, 42, the study designs and/or participant populations were quite different from those of our study. In particular, our study population had very high adherence to a guidelines-based treatment algorithm.
Previous inner-city studies have demonstrated that cockroach sensitivity and exposure are associated with increased asthma-associated morbidity.23, 24 In the current study, there was no relationship between atopy and future asthma risk, and allergen exposure was not considered in the analysis. Because the purpose of the current study was to identify predictive markers that could be readily measured by the practicing physician, allergen exposure was not analyzed.
In conclusion, we found that when well-treated, adherent populations of patients with persistent asthma are evaluated for determinants of future disease risk, asthma-related symptoms and lung function measurements are only somewhat predictive of future maximum symptoms days and exacerbations. Furthermore, more complex baseline measurements, such as FeNO levels, inflammatory markers and markers of atopy are not predictive of future disease risk. These findings highlight the need to identify better clinical predictors, perhaps including indices that are independent of inflammation, for asthma morbidity in treated populations.
1
Online Repository
Predicting asthma morbidity among inner-city adolescents receiving guidelines-based therapy: Role of exhaled nitric oxide
Authors: full name, highest degree, institution
Rebecca S. Gruchalla, MD, PhD; University of Texas Southwestern Medical Center, Dallas, TX Hugh A. Sampson, MD; Mount Sinai School of Medicine, New York, NY Elizabeth Matsui MD; Johns Hopkins University School of Medicine, Baltimore, MD Gloria David PhD, MHSc; Rho, Inc., Chapel Hill, NC Peter J. Gergen MD, MPH; DAIT, NIAID, NIH Agustin Calatroni MA, MS; Rho, Inc., Chapel Hill, NC Mark Brown MD; University of Arizona College of Medicine, Tucson, AZ Andrew H. Liu MD; National Jewish Health and University of Colorado Health Science Center, Denver, CO Gordon R. Bloomberg MD; Washington University, St. Louis, MO James F. Chmiel MD; Case Western Reserve University School of Medicine, Cleveland, OH Rajesh Kumar MD; Children's Memorial Hospital, Chicago, IL Carin Lamm MD; Columbia University School of Medicine, New York, NY Ernestine Smartt RN; DAIT, NIAID, NIH Christine A. Sorkness, PharmD; University of Wisconsin School of Medicine and Public Health, Madison, WI Suzanne F. Steinbach MD; Boston University School of Medicine, Boston, MA Kelly D. Stone MD, PhD; Children's National Medical Center, Washington DC Stanley J. Szefler MD; National Jewish Health and University of Colorado Health Science Center, Denver, CO William W. Busse MD; University of Wisconsin School of Medicine and Public Health, Madison, WI
Corresponding author Rebecca S. Gruchalla, MD, PhD University of Texas Southwestern Medical Center 5323 Harry Hines Blvd. Dallas, TX 75390-8859 Phone: (214) 648-6370 Fax: (214) 648-9100 Rebecca.Gruchalla/at/utsouthwestern.edu
Methods
Skin Tests
The following allergen extracts were used for skin testing: mouse epithelia, dog epithelia, Dermatophagoides farinae, Dermatophagoides pteronyssinus, cat hair, rat epithelia, American and German cockroach mix, German cockroach, Alternaria tenuis, Cladosporium herbarum, Aspergillus mix, Penicillium notatum, Ragweed mix, and Timothy grass. All extracts were 1:20 (wt/vol) except for D. farinae, D. pteronyssinus, Timothy grass, and cat, which were standardized extracts of 10,000 Biologic Allergy Units per ml. The resulting wheals were measured after 15 minutes. Wheal sizes were calculated as the average of the longest diameter and its orthogonal midpoint diameter. Skin tests were considered valid if the wheal size of the negative control (50% Glycerin, 50% Coca's solution) was 3 mm or smaller and the wheal size of the positive control (histamine) was at least 3 mm larger than the wheal size of the negative control. A skin test response was considered to be positive if the wheal size for the allergen was at least 3 mm larger than that for the negative control. For those analyses treating skin test wheal sizes as continuous data, the wheal size of the negative control was subtracted from the wheal size of each specific allergen.
Sputum Induction and Processing
Sputum was induced by inhalation of hypertonic saline solution (3%) using a DeVilbiss Ultra-Sonic Pico #3207 nebulizer (Nouvag; Lake Hughes, CA). Participants with pre-albuterol FEV1 ≥ 70% of predicted (206 of 213, 97%; 1 of 206 refused) underwent sputum induction following pre-treatment with albuterol. A 12 minute sputum induction was performed during which peak flow was monitored every 2 minutes with a Mini-Wright Standard peak flow meter (Alliance Tech Medical, Inc; Rockdale, TX). Slides were prepared and stained at the local laboratories. Differential cell counts were performed centrally by a blinded technician. A minimum of 400 cells was counted. Sputum samples with volume < 0.3 ml (21 of 205, 10%) were not processed. Slides with > 80% squamous cells, mucus plugs, or with poor distribution of cells were excluded (27 of 184, 15%).
Methacholine Challenge
Airway responsiveness was measured by determining the concentration of methacholine required to produce a drop in FEV1 of 20% compared to a control (post-diluent) level (PC20) after the administration of increasing concentrations of methacholine using the small volume nebulizertidal breathing technique. In brief, the participant performed tidal breathing for two minutes while inhaling from a nebulizer. After the two minute breathing exposure, spirometry was performed using a Jaeger Masterscreen (VIASYS Healthcare GmbH; Hoechberg, FRG). The procedure was repeated with increasing concentrations of methacholine until there was a 20% drop in FEV1 or the maximum concentration was administered. The following concentrations of methacholine were tested: 0 (diluent only), 0.098, 0.195, 0.391, 0.781, 1.563, 3.125, 6.25, 12.5, and 25.0 mg/ml. The PC20 was calculated by the Jaeger software by linear interpolation with log10 transformation between the last two concentrations administered.
Acknowledgments
The Asthma Control Evaluation was a collaboration of the following institutions and investigators (principal investigators are indicated by asterisks):
Johns Hopkins University, Baltimore, MD – P Eggleston*, E Matsui, R Wood, K Callahan, M Mensa, L Campbell, R Merrill, P Huffman, D Bunce, H Bradly; Boston University School of Medicine, Boston, MA – G O'Connor*, S Steinbach, N Kozlowski; Children's Memorial Hospital, Chicago, IL – J Pongracic*, R Kumar, J Kim, R Story, A Donnell, S Desai, A Murthy, S Boudreau-Romano, K Koridek, T Kearney, S Pohlman, J Milam, H Negron, I Flexas; Case Western Reserve University School of Medicine, Cleveland, OH – C Kercsmar*, J Chmiel, M Hart, T Myers, Tracy Dillard, Jackie Juricka, C Kane, V Lockhart-Blue, M Rogers, K Ross, P Vavrek; UT Southwestern Medical Center at Dallas, TX – R Gruchalla*, V Gan, W Neaville, N Gorham, J Teeple, I Dougherty, T George; National Jewish Health, Denver, CO – S Szefler*, A Liu*, J Henley, M Anderson (Denver Health Medical Center), C Campos, P Pinedo, L Soto, M Gleason, R Covar, J Spahn, K Breese, K Patterson, M White, D Sundstrom, H Leo, N Jain, B Song, K Carel, L Stewart, B Macomber, C Mjaanes, A Schiltz, R Harbeck; Mount Sinai School of Medicine, New York, NY – M Kattan*, H Sampson, C Lamm, M Pierce, A Ting, E Sembrano, L Peters, A Valones, M Duarte, Y Fernandez-Pau, P Yaniv, R Castro, M Mishoe, Y Kucuk; Washington University School of Medicine, St Louis, MO – G Bloomberg*, R Strunk, L Bacharier, T Oliver-Welker; The University of Arizona College of Medicine, Tucson, AZ – W Morgan*, M Brown, T Guilbert, F Martinez, E Morales, K Otsuka, M Celaya, D Castellanos, S Ehteshami, M Fierro, G Garcia, J Goodwin, W Hall, Y Meza, J Priefert, J Rennspies, G Terrazas, M Vasquez, R Weese; Children's National Medical Center, Washington, DC – S Teach*, K Stone, D Quint, A. Newcomer, S. Staples, J. Schmidt, E. Dunbar, R. Chirumamilla; Statistical and Clinical Coordinating Center, Rho, Inc, Chapel Hill, NC – H Mitchell*, G David, A Calatroni, M Curry, M Walter, J Wildfire, A Hodges, R Budrevich, B Shaw, R Bailey, G Allen; Scientific Coordination and Administrative Center, Madison, WI – W Busse*, C Sorkness, R Kelley, P Heinritz, G Crisafi; National Institute of Allergy and Infectious Diseases, Bethesda, MD – P Gergen, A Togias, E Smartt, M Smolskis, M Fenton.
The study also gratefully acknowledges receiving donated product from GlaxoSmithKline (study drugs) and Lincoln Diagnostics, Inc. (skin testing materials).
Funding
This project has been funded in whole or in part with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, under Contracts number NO1-AI-25496 and NO1-AI-25482, and from the National Center for Research Resources, National Institutes of Health, under grant RR00052, M01 RR00533, M01RR0071, 5UL1RR024992-02, and 5M01RR020359-04.
Abbreviations
ACEAsthma Control Evaluation
FENOFraction of exhaled nitric oxide in parts per billion
(ppb)FEV1Forced expiratory volume in one second
FEV1/FVCRatio of FEV1 and forced vital capacity
ICSInhaled corticosteroid
IgEImmunoglobulin E
kU/LKilo units/liter
kUA/LKilo units (allergen-specific)/liter
MgMilligram
mLMilliliter
mmMillimeter
ngNanogram
PC20Provocative concentration of methacholine causing a 20% fall in FEV1
WBCWhite blood cells
wt/volWeight/volume

Footnotes
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Capsule Summary
Among 546 inner-city adolescents with asthma receiving guidelines-based therapy, future asthma symptoms and exacerbations were somewhat predicted by baseline symptoms and lung function measurements. Neither exhaled nitric oxide nor other markers of inflammation or atopy predicted future disease activity.
Clinical Implications
Markers of allergic sensitization, airway hyperresponsiveness, and airway inflammation do not predict future asthma exacerbations in inner city adolescents who are receiving guidelines-based therapy and who are adherent to their treatment regimens.
Contributor Information
Rebecca S. Gruchalla, University of Texas Southwestern Medical Center, Dallas, TX.
Hugh A. Sampson, Mount Sinai School of Medicine, New York, NY.
Elizabeth Matsui, Johns Hopkins University School of Medicine, Baltimore, MD.
Gloria David, Rho, Inc., Chapel Hill, NC.
Peter J. Gergen, DAIT, NIAID, NIH.
Agustin Calatroni, Rho, Inc., Chapel Hill, NC.
Mark Brown, University of Arizona College of Medicine, Tucson, AZ.
Andrew H. Liu, National Jewish Health and University of Colorado Health Science Center, Denver, CO.
Gordon R. Bloomberg, Washington University, St. Louis, MO.
James F. Chmiel, Case Western Reserve University School of Medicine, Cleveland, OH.
Rajesh Kumar, Children's Memorial Hospital, Chicago, IL.
Carin Lamm, Columbia University College of Physicians and Surgeons, New York, NY.
Ernestine Smartt, DAIT, NIAID, NIH.
Christine A. Sorkness, University of Wisconsin School of Medicine and Public Health, Madison, WI.
Suzanne F. Steinbach, Boston University School of Medicine, Boston, MA.
Kelly D. Stone, Children's National Medical Center, Washington DC.
Stanley J. Szefler, National Jewish Health and University of Colorado Denver School of Medicine, Denver, CO.
William W. Busse, University of Wisconsin School of Medicine and Public Health Madison, WI.
1. Expert Panel Report 3 (EPR-3): Guidelines for the Diagnosis and Management of Asthma-Summary. Aug 28, 2007. www.nhlbi.nih.gov/guidelines/asthma/asthdln.pdf 2007.
2. Busse WW, Lemanske RF., Jr Expert Panel Report 3: Moving forward to improve asthma care. J Allergy Clin Immunol. 2007;120:1012–4. [PubMed]
3. Szefler SJ, Mitchell H, Sorkness CA, Gergen PJ, O'Connor GT, Morgan WJ, et al. Management of asthma based on exhaled nitric oxide in addition to guideline-based treatment for inner-city adolescents and young adults: a randomised controlled trial. Lancet. 2008;372:1065–72. [PMC free article] [PubMed]
4. Silkoff PE, McClean PA, Slutsky AS, Furlott HG, Hoffstein E, Wakita S, et al. Marked flow-dependence of exhaled nitric oxide using a new technique to exclude nasal nitric oxide. Am J Respir Crit Care Med. 1997;155:260–7. [PubMed]
5. Recommendations for standardized procedures for the on-line and off-line measurement of exhaled lower respiratory nitric oxide and nasal nitric oxide in adults and children-1999. This official statement of the American Thoracic Society was adopted by the ATS Board of Directors, July 1999. Am J Respir Crit Care Med. 1999;160:2104–17. [PubMed]
6. Silkoff PE, Carlson M, Bourke T, Katial R, Ogren E, Szefler SJ. The Aerocrine exhaled nitric oxide monitoring system NIOX is cleared by the US Food and Drug Administration for monitoring therapy in asthma. J Allergy Clin Immunol. 2004;114:1241–56. [PubMed]
7. Fahy J, Boushey H, Lazarus S, Mauger E, Reuben M, Cherniak R, et al. Safety and reproducibility of sputum induction iin asthmatic subjects in a multicenter study. Am J Resp Crit Care Med. 2001;163:1470–5. [PubMed]
8. Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. Standardisation of spirometry. Eur Respir J. 2005;26:319–38. [PubMed]
9. Strunk RC, Szefler SJ, Phillips BR, Zeiger RS, Chinchilli VM, Larsen G, et al. Relationship of exhaled nitric oxide to clinical and inflammatory markers of persistent asthma in children. J Allergy Clin Immunol. 2003;112:883–92. [PubMed]
10. Evans R, 3rd, Gergen PJ, Mitchell H, Kattan M, Kercsmar C, Crain E, et al. A randomized clinical trial to reduce asthma morbidity among inner-city children: results of the National Cooperative Inner-City Asthma Study. J Pediatr. 1999;135:332–8. [PubMed]
11. Morgan WJ, Crain EF, Gruchalla RS, O'Connor GT, Kattan M, Evans R, 3rd, et al. Results of a home-based environmental intervention among urban children with asthma. N Engl J Med. 2004;351:1068–80. [PubMed]
12. Gromping U. Estimators of Relative Importance in Linear Regression Based on Variance Decomposition. The American Statistician. 2007;61:139–47.
13. R. Development Core Team R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; Vienna, Austria: 2007.
14. Gromping U. Relative Importance for Linear Regression in R: The Package relaimpo. Journal of Statistical Software. 2006;17:1–27.
15. Djukanovic R, Wilson SJ, Kraft M, Jarjour NN, Steel M, Chung KF, et al. Effects of treatment with anti-immunoglobulin E antibody omalizumab on airway inflammation in allergic asthma. Am J Respir Crit Care Med. 2004;170:583–93. [PubMed]
16. Miller MK, Lee JH, Miller DP, Wenzel SE. Recent asthma exacerbations: a key predictor of future exacerbations. Respir Med. 2007;101:481–9. [PubMed]
17. Kwong KYC, Morphew T, Scott L, Guterman J, Jones CA. Asthma control and future asthma-related morbidity in inner city asthmatic children. Ann Allergy Asthma Immunol. 2008;101:144–52. [PubMed]
18. Sullivan SD, Wenzel SE, Bresnahan BW, Zheng B, Lee JH, Pritchard M, et al. Association of control and risk of severe asthma-related events in severe or difficult-to-treat asthma patients. Allergy. 2007;62:655–60. [PubMed]
19. Connolly CK, Mamun M, Alcock SM, Prescott RJ. The Darlington and Northallerton Prospective Asthma Study: best function predicts mortality during the first 10 years. Respir Med. 1998;92:1274–80. [PubMed]
20. Gelb AF, Flynn Taylor C, Shinar CM, Gutierrez C, Zamel N. Role of spirometry and exhaled nitric oxide to predict exacerbations in treated asthmatics. Chest. 2006;129:1492–9. [PubMed]
21. Belessis Y, Dixon S, Thomsen A, Duffy B, Rawlinson W, Henry R, et al. Risk factors for an intensive care unit admission in children with asthma. Pediatr Pulmonol. 2004;37:201–9. [PubMed]
22. Harkins MS, Fiato KL, Iwamoto GK. Exhaled nitric oxide predicts asthma exacerbation. J Asthma. 2004;41:471–6. [PubMed]
23. Gruchalla RS, Pongracic J, Plaut M, Evans R, 3rd, Visness CM, Walter M, et al. Inner City Asthma Study: relationships among sensitivity, allergen exposure, and asthma morbidity. J Allergy Clin Immunol. 2005;115:478–85. [PubMed]
24. Rosenstreich D, Eggleston P, Kattan M, Baker D, Slavin R, Gergen P, et al. The role of cockroach allergy and exposure to cockroach allergen in causing morbidity among inner-city children with asthma. N Engl J Med. 1997;336:1356–63. [PubMed]
25. Sporik R, Platts-Mills TA. Cogswell JJ. Exposure to house dust mite allergen of children admitted to hospital with asthma. Clin Exp Allergy. 1993;23:740–6. [PubMed]
26. Eisner MD, Katz PP, Lactao G, Iribarren C. Impact of depressive symptoms on adult asthma outcomes. Ann Allergy Asthma Immunol. 2005;94:566–74. [PubMed]
27. Adams RJ, Smith BJ, Ruffin RE. Factors associated with hospital admissions and repeat emergency department visits for adults with asthma. Thorax. 2000;55:566–73. [PMC free article] [PubMed]
28. Deykin A, Lazarus SC, Fahy JV, Wechsler ME, Boushey HA, Chinchilli VM, et al. Sputum eosinophil counts predict asthma control after discontinuation of inhaled corticosteroids. J Allergy Clin Immunol. 2005;115:720–7. [PubMed]
29. Green RH, Brightling CE, McKenna S, Hargadon B, Parker D, Bradding P, et al. Asthma exacerbations and sputum eosinophil counts: a randomised controlled trial. Lancet. 2002;360:1715–21. [PubMed]
30. Lex C, Jenkins G, Wilson NM, Zacharasiewicz A, Erin E, Hansel TT, et al. Does sputum eosinophilia predict the response to systemic corticosteroids in children with difficult asthma? Pediatr Pulmonol. 2007;42:298–303. [PubMed]
31. Lex C, Ferreira F, Zacharasiewicz A, Nicholson AG, Haslam PL, Wilson NM, et al. Airway eosinophilia in children with severe asthma: predictive values of noninvasive tests. Am J Respir Crit Care Med. 2006;174:1286–91. [PubMed]
32. Zacharasiewicz A, Wilson N, Lex C, Erin EM, Li AM, Hansel T, et al. Clinical use of noninvasive measurements of airway inflammation in steroid reduction in children. Am J Respir Crit Care Med. 2005;171:1077–82. [PubMed]
33. Pharoah PD, Antoniou AC, Easton DF, Ponder BA. Polygenes, risk prediction, and targeted prevention of breast cancer. N Engl J Med. 2008;358:2796–803. [PubMed]
34. Covar R, Szefler S, Martin R, Sundstrom D, Silkoff P, Murphy J, et al. Relations between exhaled nitric oxide and measures of disease activity among children with mild-to-moderate asthma. J Pediatr. 2003;142:469–75. [PubMed]
35. Jatakanon A, Lim S, Kharitonov S, Chung K, Barnes P. Correlation between exhaled nitric oxide, sputum eosinophils, and methacholine responsiveness in patients with mild asthma. Thorax. 1998;53:91–5. [PMC free article] [PubMed]
36. Berlyne GS, Parameswaran K, Kamada D, Efthimiadis A, Hargreave FE. A comparison of exhaled nitric oxide and induced sputum as markers of airway inflammation. J Allergy Clin Immunol. 2000;106:638–44. [PubMed]
37. Berry MA, Shaw DE, Green RH, Brightling CE, Wardlaw AJ, Pavord ID. The use of exhaled nitric oxide concentration to identify eosinophilic airway inflammation: an observational study in adults with asthma. Clin Exp Allergy. 2005;35:1175–9. [PubMed]
38. Chan-Yeung M, Obata H, Dittrick M, Chan H, Abboud R. Airway inflammation, exhaled nitric oxide, and severity of asthma in patients with western red cedar asthma. Am J Respir Crit Care Med. 1999;159:1434–8. [PubMed]
39. Mattes J, Storm van's Gravesande K, Reining U, Alving K, Ihorst G, Henschen M, et al. NO in exhaled air is correlated with markers of eosinophilic airway inflammation in corticosteroid-dependent childhood asthma. Eur Respir J. 1999;13:1391–5. [PubMed]
40. Payne DN, Adcock IM, Wilson NM, Oates T, Scallan M, Bush A. Relationship between exhaled nitric oxide and mucosal eosinophilic inflammation in children with difficult asthma, after treatment with oral prednisolone. Am J Respir Crit Care Med. 2001;164:1376–81. [PubMed]
41. Jones SL, Kittelson J, Cowan JO, Flannery EM, Hancox RJ, McLachlan CR, et al. The predictive value of exhaled nitric oxide measurements in assessing changes in asthma control. Am J Respir Crit Care Med. 2001;164:738–43. [PubMed]
42. Pijnenburg MW, Hofhuis W, Hop WC, De Jongste JC. Exhaled nitric oxide predicts asthma relapse in children with clinical asthma remission. Thorax. 2005;60:215–8. [PMC free article] [PubMed]