Adnan Custovic

Background: Achieving and maintaining pediatric asthma control depends on effective and regular monitoring. While a wide range of monitoring tools are available, how and why clinicians use these in routine practice has not been formally characterized. Here we describe distinct real‐world monitoring patterns among healthcare professionals ( HCPs ) caring for children with asthma in an international convenience survey, examining the geographic, professional, and institutional factors associated with them. Methods: Data from the international cross‐sectional Pediatric Asthma in Real Life ( PeARL ) HCP survey, administered to clinicians with expertise in childhood asthma, were analyzed. Monitoring patterns were derived by Ward agglomerative hierarchical clustering on four standardized domains: clinical evaluation, spirometry, fractional exhaled nitric oxide ( FeNO ), and home‐monitoring. Independent associations between cluster membership and region, specialty, sector, and level of care were estimated by multinomial logistic regression ( MLR ). Results: 951 HCPs from 78 countries were included. Four monitoring patterns emerged: Low‐intensity ( n = 88, 9.3%), lower overall monitoring intensity but moderate clinical assessment; Clinical ( n = 449, 47.2%), predominantly clinical assessment with moderate spirometry but infrequent FeNO and home monitoring; Clinical & Objective ( n = 308, 32.4%) with additional regular spirometry with moderate FeNO use and Comprehensive ( n = 106, 11.1%), also providing home monitoring. In MLR ( n = 933), region and care level were significantly associated with cluster membership ( p < .001), and specialty ( p = .012) and sector ( p = .039) also contributed independently. The most pronounced gradients involved objective in‐clinic testing: specialists were 3.5‐fold (95% CI 1.68–7.37) more likely than generalists, and tertiary‐care HCPs 3.3‐fold (95% CI 1.99–5.58) more likely than primary‐care HCPs, to belong to the Clinical & Objective pattern, with routine use of objective measures concentrated in Western and Northern European practices. Home monitoring showed no consistent gradient across the measured characteristics. Conclusion: Real‐world pediatric asthma monitoring follows recognizable patterns, distinguished by the use of objective in‐clinic testing and between‐visit home‐based practices. Nearly half of HCPs relied predominantly on clinical assessment with limited use of FeNO and home‐based monitoring, and only a minority integrated home‐monitoring tools. Objective in‐clinic testing concentrated in specialist services and Western/Northern European practices, while home‐monitoring adoption showed no consistent gradient. These findings identify factors associated with pediatric asthma monitoring and suggest system‐level factors that warrant direct evaluation in dedicated implementation studies. image

Asthma is a heterogeneous disease affecting nearly 300 million people around the world. It is the most common chronic respiratory disease of childhood. There are significant sex differences in asthma incidence, severity, and morbidity around the time of puberty. The reasons for these peripubertal changes are still not fully understood, but they are likely multifactorial. In this review, we will discuss several proposed contributing mechanisms, including sex differences in anatomy and development, the effects of sex hormones on airway inflammation and reactivity, the immunomodulatory effects of sex hormones, differences in mucociliary function, and sex differences in genetic and epigenetic factors.

Background: IgE‐mediated food allergy prevention guidelines are now established in many countries, but their implementation in routine clinical practice globally remains unclear. Methods: An anonymous online survey was distributed to healthcare professionals (HCPs) through the World Allergy Organization network between December 2024 and April 2025, collecting data on food allergy prevention recommendations in daily clinical practice. Results: The analysis included 731 healthcare professionals from 80 countries worldwide: Asia (36.7%), Europe (27.1%), North America (15.9%), and Rest of the World (20.0%; Russia, South America, Africa, Oceania). Unsupervised clustering revealed two distinct practice patterns—one favoring early allergen introduction and one favoring later introduction—with timing varying by allergen type. For peanuts, clusters diverged between early (median 6 months of age) and late (median 18 months of age) introduction recommendations for high‐risk infants. Allergen introduction timing was independently driven by region and specialty: North American HCPs recommend peanut introduction 6.7 months earlier than those in Asia (5.48 3.32 vs. 12.18 7.27 months; p < 0.001), and pediatric allergists globally advocate for introduction 2.37 months earlier than non‐allergists (8.72 5.85 vs. 11.09 7.14 months, p = 0.024). This disparity is more pronounced in high‐risk infants than in normal‐risk infants. Conclusions: The variability in allergen introduction practices, driven by geography and medical specialty, highlights a persistent gap in prevention guidelines adoption. This divergence likely reflects both suboptimal implementation of existing recommendations and regional differences in food allergy epidemiology. These findings underscore the need for population‐tailored allergen introduction strategies across diverse healthcare settings.

Asthma is a heterogeneous condition often studied through wheeze alone, yet the interplay between lung function and reported symptoms remains underexplored. To capture this heterogeneity, we applied Bayesian Profile Regression to data from school-age children in two prospective birth cohorts, integrating airway hyperresponsiveness, lung function, bronchodilator reversibility, allergic sensitisation, reported symptoms, and physician diagnosis. In the Manchester Allergy and Asthma Study (discovery cohort), five reproducible clusters were identified: HA-LLF (high asthma-low lung function), HA-NLF (high asthma normal lung function), LA-RLF (low asthma-reduced lung function), LA-NLF (low asthma normal lung function), and MA-NLF (moderate asthma normal lung function). The HA-LLF and HA-NLF clusters had very high asthma prevalence (80–100%), but differed markedly in lung function, airway responsiveness, bronchodilator reversibility, sensitisation, and symptom burden. The LA-RLF and LA-NLF clusters with low asthma prevalence (< 5%) displayed contrasting lung function profiles, while MA-NLF (~ 50% asthma prevalence) was largely defined by prominent symptoms such as chest tightness and shortness of breath. These subtypes were replicated in an independent cohort, Isle of Wight. Our findings demonstrate that integrating physiological, immunological, and symptom-based measures yields clinically meaningful asthma subtypes beyond wheeze-based definitions and may support more precise disease classification.

Early microbial colonization influences respiratory disease risk, yet mechanisms remain unclear. In a prospective birth cohort of 256 infants, we profiled bacterial, fungal, and viral communities in the upper airway and assessed local immune gene expression longitudinally and systemic gene expression at 1 year. Bacterial populations, not fungal or viral, correlated most strongly with immune development during the first 3 months, coinciding with composition shifts and immune-related gene expression changes, including interferon and adaptive immunity pathways. In contrast, the mycobiome and resident viruses showed no significant coevolution with host immunity. By 1 year, infants who previously wheezed displayed an upper airway microbiota enriched in Haemophilus influenzae and Moraxella , accompanied by a distinct local and systemic immune gene signature featuring elevated classical monocyte-related genes. These findings reveal a specific link between early-life bacterial dysbiosis, monocyte-related immunity, and wheezing onset, suggesting potential targets for early intervention in respiratory disease.