Stability of Asthma Symptom Control in a Longitudinal Study of Mild-Moderate Asthmatics

Pharmacovigilance study of the association between dipeptidyl peptidase-4 inhibitors and angioedema using the FDA Adverse Event Reporting System (FAERS)

Dipeptidyl peptidase-4 (DPP-4) plays a minor role in degrading vasoactive peptides that cause angioedema when angiotensin-converting enzyme (ACE) is present and fully functional. This study investigated the association between DPP-4 inhibitors (DPP-4Is) and angioedema, including cases where the concomitant use of ACE inhibitors (ACEIs) was absent. We obtained data from the US Food and Drug Administration Adverse Event Reporting System and performed a disproportionality analysis, using the reporting odds ratio (ROR) and information component (IC) for signal detection in patients aged ≥ 40 years, stratified by age group and sex. No signal was detected for DPP-4Is when the entire dataset was analyzed. However, a signal was detected for the entire female subset group, the three stratified female groups aged ≥ 60 years, and males in their 40 s. After excluding the data of concomitant ACEI users, most ROR and IC values were lower and significant only for females in their 60 s and males aged ≥ 80 years. Regarding individual DPP-4Is signals, those detected for saxagliptin and sitagliptin in some age groups disappeared after excluding the data of ACEI users. Notably, linagliptin was the only DPP-4I where signals were detected in most female groups, regardless of age and without concomitant ACEI use. Our findings suggest that some DPP-4Is were associated with a higher reporting of angioedema as per age and sex, even in the absence of concomitant ACEI use.

Patient characteristics associated with improvements in asthma control and reduction in emergency department visits for older adults with asthma

OBJECTIVE

To identify patient characteristics associated with improvements in asthma control among older adults with asthma.

METHODS

Secondary analysis of data from a randomized controlled trial of an asthma self-management support intervention for adults ages 60 and older with moderate-severe persistent asthma (n = 391). We tested the association of baseline patient characteristics with reduced emergency department (ED) visits and improvement in asthma control equal to or exceeding the minimal clinically important difference (MCID) in asthma control test (ACT) scores (3.0) 12 months.

RESULTS

At baseline, the mean age was 68 years, 15.0% were male, 30.3% were black, and 56.5% were Hispanic. Patients with a history of ED visits in the 12 months preceding study enrollment were significantly more likely to experience an ED visit during the study period (adjusted odds ratio [AOR] 6.92, 95% confidence interval [CI] 2.18-21.9, p < .0001). Similarly, those with poorer asthma control (baseline ACT scores <13) had greater odds of achieving improved asthma control (AOR 13.7, 95% CI 5.32-35.1, p < .0001). No other variables had statistically significant associations with the outcomes.

CONCLUSIONS

Low scores on the asthma control test and prior ED visits for asthma are strong correlates of later clinically meaningful changes in asthma control among older adults. Health systems preparing for population management of patients with asthma ought to consider incorporating serial collection of data on the ACT into the monitoring and management of older asthmatics, a high-risk patient population.

Does adherence to inhaled corticosteroids predict asthma-related outcomes over time? A cohort study

Inhaled corticosteroids (ICS) adherence is important for asthma management. Current evidence on the impact of ICS adherence on outcomes is mostly based on correlational analyses of between-person data. Although it is widely acknowledged that asthma outcomes fluctuate over time, evidence on predictors of within-person change is scarce. We aimed to quantify these fluctuations and the longitudinal relationships between ICS adherence and outcomes at both between- and within-person levels.A prospective cohort of persistent asthma patients in France and the UK (n=847, age 6-40 years) provided 3756 reports over up to 2 years via computer-assisted telephone interviews and text messages on ICS adherence, asthma control, reliever medication use and exacerbations. We examined adherence-outcome relationships via longitudinal models, controlling for confounders, including severity.Considerable within-person variability was found for exacerbations (91%), asthma control (59%) and reliever use (52%); 431 (11.5%) reports signalled exacerbations and 2046 (54.5%) poor control. At between-person level, patients with higher average adherence were more likely to report asthma control (OR 1.25, 95% CI 1.06-1.47), but not asthma exacerbations (OR 0.99, 95% CI 0.87-1.12) or lower reliever use (b -0.0004, 95% CI -0.089-0.088). At within-person level, higher-than-usual adherence was associated with higher concomitant reliever use (b 0.092, 95% CI 0.053-0.131) and lower subsequent reliever use (b -0.047, 95% CI -0.005- -0.088); it was unrelated to asthma control (OR 0.93, 95% CI 0.84-1.02) or exacerbations (OR 1.04, 95% CI 0.94-1.16).Patients maintaining high ICS adherence over time have better asthma control. Temporarily increasing ICS adherence tends to be simultaneous to higher reliever use and reduces reliever use later on. Causes of within-person variation in outcomes require more investigation.

Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning

RATIONALE

Pediatric 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.

OBJECTIVES

Our 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.

METHODS

We 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.

RESULTS

Four 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.

CONCLUSIONS

Advanced 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.

Continuous positive airway pressure for obstructive sleep apnoea does not improve asthma control

BACKGROUND AND OBJECTIVE

Unrecognized obstructive sleep apnoea syndrome (OSAS) may lead to poor asthma control despite optimal therapy. We assessed asthma control, airway responsiveness, daytime sleepiness and health status at baseline and 3 months after continuous positive airway pressure (CPAP) treatment among asthma patients with nocturnal symptoms and OSAS.

METHODS

Patients with nocturnal asthma symptoms despite receiving at least moderate-dose inhaled corticosteroid and long-acting bronchodilators underwent a home sleep study using 'Embletta' portable diagnostic system. Patients with significant OSAS (apnoea-hypopnoea index (AHI) ≥10/h) were randomized to receive either CPAP or conservative treatment for 3 months.

RESULTS

Among 145 patients recruited, 122 underwent sleep study with 41 (33.6%) having AHI ≥10/h. Patients with significant OSAS had higher BMI (27.4 (5.1) vs 25.1 (4.5) kg/m² , P = 0.016), bigger neck circumference (36.6 (3.1) vs 34.8 (3.6) cm, P = 0.006) and lower minimum SaO₂ (80.7 (6.6) vs 87.2 (3.9) %, P < 0.001). Using intention-to-treat analysis among 37 patients with AHI ≥10/h (CPAP group (n = 17) vs control group (n = 20)), there was no significant difference in Asthma Control Test score (CPAP 3.2 (2.7) vs control 2.4 (5.7), P = 0.568) but the CPAP group had a greater improvement in Epworth Sleepiness Scale (-3.0 (4.5) vs 0.5(3.8), P = 0.014), Asthma Quality of Life Questionnaire (0.6 (0.8) vs 0.02 (0.7), P = 0.022) and vitality domain in the SF-36 questionnaire (14.7 (16.8) vs 0.3 (16.2), P = 0.012) after 3 months. Data are presented as mean (SD) unless otherwise stated.

CONCLUSION

A high prevalence of OSAS was found among patients with asthma and snoring. CPAP therapy for 3 months did not enhance asthma control but improved daytime sleepiness, quality of life and vitality.

The Journal of Allergy and Clinical Immunology: In Practice 2017 Year in Review

An impressive number of clinically impactful studies and reviews were published in The Journal of Allergy and Clinical Immunology: In Practice in 2017. As a service to our readers, the editors provide this Year in Review article to highlight and contextualize the advances published over the past year. We include information from articles on asthma, allergic rhinitis, rhinosinusitis, immunotherapy, atopic dermatitis, contact dermatitis, food allergy, anaphylaxis, drug hypersensitivity, urticarial/angioedema, eosinophilic disorders, and immunodeficiency. Within each topic, epidemiologic findings are presented, relevant aspects of prevention are described, and diagnostic and therapeutic advances are enumerated. Treatments discussed include behavioral therapy, allergen avoidance therapy, positive and negative effects of pharmacologic therapy, and various forms of immunologic and desensitization management. We hope this review will help readers consolidate and use this extensive and practical knowledge for the benefit of patients.