Combining Tablets with Smartphones for Data Analytics

International audienc

Aeroallergen Sensitization, Serum IgE, and Eosinophilia as Predictors of Response to Omalizumab Therapy during the Fall Season among Children with Persistent Asthma

BACKGROUND: Perennial aeroallergen sensitization is associated with greater asthma morbidity and is required for treatment with omalizumab. OBJECTIVE: To investigate the predictive relationship between the number of aeroallergen sensitizations, total serum IgE, and serum eosinophil count, and response to omalizumab in children and adolescents with asthma treated during the fall season. METHODS: This analysis includes inner-city patients with persistent asthma and recent exacerbations aged 6-20 years comprising the placebo and omalizumab-treated groups in two completed randomized clinical trials, the Inner-City Anti-IgE Therapy for Asthma (ICATA) study and the Preventative Omalizumab or Step-Up Therapy for Fall Exacerbations (PROSE) study. Logistic regression modeled the relationship between greater degrees of markers of allergic inflammation and the primary outcome of fall season asthma exacerbations. RESULTS: The analysis included 761 participants who were 62% male and 59% African American with a median age of 10 years. Fall asthma exacerbations were significantly higher in children with greater numbers of aeroallergen-specific sensitizations in the placebo group (OR 1.33, 95% CI 1.11-1.60, p CONCLUSIONS: In preventing fall season asthma exacerbations, treatment with omalizumab was most beneficial in children with a greater degree of allergic inflammation

Distinguishing characteristics of difficult-to-control asthma in inner-city children and adolescents.

BACKGROUND: Treatment levels required to control asthma vary greatly across a population with asthma. The factors that contribute to variability in treatment requirements of inner-city children have not been fully elucidated. OBJECTIVE: To identify the clinical characteristics which distinguish difficult-to-control asthma. METHODS: Children with asthma aged 6-17 underwent baseline assessment and bimonthly guidelines-based management visits over one year. Difficult- versus easy-to-control asthma were defined as daily therapy with fluticasone ≥500mcg +/-LABA versus ≤100mcg assigned on at least 4 visits. Forty-four baseline variables were used to compare the 2 groups using univariate analyses and identify the most relevant features of difficult-to-control asthma using a variable selection algorithm. Nonlinear seasonal variation in longitudinal measures (symptoms, pulmonary physiology and exacerbations) was examined using generalized additive mixed-effects models. RESULTS: Among 619 recruited participants, 40.9% had difficult-to-control asthma, 37.5% had easy-to-control asthma and 21.6% fell into neither group. At baseline, FEV(1) bronchodilator responsiveness was the most important characteristic distinguishing difficult- from easy-to-control asthma. Markers of rhinitis severity and atopy were among the other major discriminating features. Over time, difficult-to-control asthma was characterized by high exacerbation rates, particularly in spring and fall, greater day and night symptoms, especially in fall and winter, and compromised pulmonary physiology despite ongoing high dose controller therapy. CONCLUSIONS: Despite good adherence, difficult-to-control asthma showed little improvement in symptoms, exacerbations or pulmonary physiology over the year. Besides pulmonary physiology measures, rhinitis severity and atopy were associated with high dose asthma controller therapy requirement. CLINICAL IMPLICATIONS: Clinical baseline characteristics related to pulmonary physiology, rhinitis severity, and atopy prospectively distinguish difficult- from easy-to-control asthma

Distinguishing characteristics of difficult-to-control asthma in inner-city children and adolescents

BACKGROUND: Treatment levels required to control asthma vary greatly across a population with asthma. The factors that contribute to variability in treatment requirements of inner-city children have not been fully elucidated. OBJECTIVE: We sought to identify the clinical characteristics that distinguish difficult-to-control asthma from easy-to-control asthma. METHODS: Asthmatic children aged 6 to 17 years underwent baseline assessment and bimonthly guideline-based management visits over 1 year. Difficult-to-control and easy-to-control asthma were defined as daily therapy with 500 μg of fluticasone or greater with or without a long-acting β-agonist versus 100 μg or less assigned on at least 4 visits. Forty-four baseline variables were used to compare the 2 groups by using univariate analyses and to identify the most relevant features of difficult-to-control asthma by using a variable selection algorithm. Nonlinear seasonal variation in longitudinal measures (symptoms, pulmonary physiology, and exacerbations) was examined by using generalized additive mixed-effects models. RESULTS: Among 619 recruited participants, 40.9% had difficult-to-control asthma, 37.5% had easy-to-control asthma, and 21.6% fell into neither group. At baseline, FEV1 bronchodilator responsiveness was the most important characteristic distinguishing difficult-to-control asthma from easy-to-control asthma. Markers of rhinitis severity and atopy were among the other major discriminating features. Over time, difficult-to-control asthma was characterized by high exacerbation rates, particularly in spring and fall; greater daytime and nighttime symptoms, especially in fall and winter; and compromised pulmonary physiology despite ongoing high-dose controller therapy. CONCLUSIONS: Despite good adherence, difficult-to-control asthma showed little improvement in symptoms, exacerbations, or pulmonary physiology over the year. In addition to pulmonary physiology measures, rhinitis severity and atopy were associated with high-dose asthma controller therapy requirement

Pathways through which asthma risk factors contribute to asthma severity in inner-city children.

BACKGROUND: Pathway analyses can be used to determine how host and environmental factors contribute to asthma severity. OBJECTIVE: Investigate pathways explaining asthma severity in inner-city children. METHODS: Based on medical evidence in the published literature, we developed a conceptual model to describe how eight risk-factor domains (allergen sensitization, allergic inflammation, pulmonary physiology, stress, obesity, vitamin D, environmental tobacco smoke (ETS) exposure and rhinitis severity) are linked to asthma severity. To estimate the relative magnitude and significance of hypothesized relationships among these domains and asthma severity, we applied a causal network analysis to test our model in an Inner-City Asthma Consortium study. Participants comprised 6–17 year old children (n=561) with asthma and rhinitis from 9 U.S. inner-cities who were evaluated every two months for one year. Asthma severity was measured by a longitudinal composite assessment of day and night symptoms, exacerbations, and controller usage. RESULTS: Our conceptual model explained 53.4% of the variance in asthma severity. An allergy pathway (linking allergen sensitization, allergic inflammation, pulmonary physiology, and rhinitis severity domains to asthma severity) and ETS exposure pathway (linking ETS exposure and pulmonary physiology domains to asthma severity) exerted significant effects on asthma severity. Among the domains, pulmonary physiology and rhinitis severity had the largest significant standardized total effects on asthma severity (−0.51 and 0.48 respectively), followed by ETS exposure (0.30) and allergic inflammation (0.22). While vitamin D had modest but significant indirect effects on asthma severity, its total effect was insignificant (0.01). CONCLUSIONS: The standardized effect sizes generated by a causal network analysis quantify the relative contributions of different domains and can be used to prioritize interventions to address asthma severity

Pathways through which asthma risk factors contribute to asthma severity in inner-city children

BACKGROUND: Pathway analyses can be used to determine how host and environmental factors contribute to asthma severity. OBJECTIVE: To investigate pathways explaining asthma severity in inner-city children. METHODS: On the basis of medical evidence in the published literature, we developed a conceptual model to describe how 8 risk-factor domains (allergen sensitization, allergic inflammation, pulmonary physiology, stress, obesity, vitamin D, environmental tobacco smoke [ETS] exposure, and rhinitis severity) are linked to asthma severity. To estimate the relative magnitude and significance of hypothesized relationships among these domains and asthma severity, we applied a causal network analysis to test our model in an Inner-City Asthma Consortium study. Participants comprised 6- to 17-year-old children (n = 561) with asthma and rhinitis from 9 US inner cities who were evaluated every 2 months for 1 year. Asthma severity was measured by a longitudinal composite assessment of day and night symptoms, exacerbations, and controller usage. RESULTS: Our conceptual model explained 53.4% of the variance in asthma severity. An allergy pathway (linking allergen sensitization, allergic inflammation, pulmonary physiology, and rhinitis severity domains to asthma severity) and the ETS exposure pathway (linking ETS exposure and pulmonary physiology domains to asthma severity) exerted significant effects on asthma severity. Among the domains, pulmonary physiology and rhinitis severity had the largest significant standardized total effects on asthma severity (-0.51 and 0.48, respectively), followed by ETS exposure (0.30) and allergic inflammation (0.22). Although vitamin D had modest but significant indirect effects on asthma severity, its total effect was insignificant (0.01). CONCLUSIONS: The standardized effect sizes generated by a causal network analysis quantify the relative contributions of different domains and can be used to prioritize interventions to address asthma severity