The evolution of scientific knowledge in childhood asthma over time
Clinical Snapshot
PICO Framework
| P — Population | Children with asthma across historical periods (early 20th century to present) |
| I — Intervention | Evolution of diagnostic and therapeutic approaches including inhaled corticosteroids, biomarkers, omics technologies, and AI-assisted tools |
| C — Comparator | Historical comparison of management approaches across different time periods |
| O — Outcomes | Diagnostic accuracy, therapeutic effectiveness, disease monitoring capabilities, and personalised care delivery |
Bottom Line
This narrative review traces the remarkable evolution of paediatric asthma management from basic clinical observations to today's sophisticated, personalised approaches. Key milestones include the introduction of inhaled corticosteroids for targeted inflammation control, development of non-invasive monitoring tools like fractional exhaled nitric oxide, and integration of omics technologies for phenotype-specific treatment. The review highlights the emerging role of digital health and machine learning in predicting exacerbations and optimising care. However, significant challenges remain in standardising new technologies, ensuring equitable access, and validating AI algorithms in paediatric populations. While this historical perspective provides valuable educational context, clinicians should note that as a narrative review, it lacks the systematic methodology required for evidence-based practice recommendations. The transition toward precision medicine represents a promising direction, but implementation requires careful consideration of local resources, regulatory approval, and cost-effectiveness in routine clinical practice.
Key Findings
P Value: Not applicable - narrative review
Effect Size: Not applicable - narrative synthesis
Primary Outcome: Evolution from empirical treatment to personalised, biomarker-driven asthma management strategies
Nnt Or Sensitivity: Historical transformation: introduction of inhaled corticosteroids, fractional exhaled nitric oxide monitoring, and AI-assisted prediction tools
Confidence Interval: Not applicable - narrative review
Clinical Application
Variable - depends on healthcare system resources and access to advanced diagnostic technologies Highly relevant to Australian practice; aligns with RACGP asthma guidelines and PBS-subsidised inhaled therapies; emerging technologies may require TGA evaluation and PBS consideration All children with asthma in contemporary healthcare settings
Abstract
Paediatric asthma management has undergone a significant transformation from rudimentary assessments in the early 20th century to sophisticated diagnostic and therapeutic approaches today. Early clinical observations lacked paediatric specificity, but mid-20th-century studies introduced functional assessments, spirometry and recognition of asthma as a chronic inflammatory condition. The introduction of inhaled corticosteroids transformed long-term management, offering targeted control with reduced systemic risks. Advances in noninvasive diagnostics, such as fractional exhaled nitric oxide, induced sputum analysis, exhaled breath condensate and electronic nose technology, have improved inflammation monitoring, phenotype classification and therapeutic responsiveness. The integration of omics technologies, i.e. genomics, proteomics and metabolomics, has enabled deeper insights into disease mechanisms and facilitated early, individualised interventions. Concurrently, artificial intelligence (AI) and machine learning are emerging as tools for predicting exacerbations, identifying clinical subtypes and enhancing decision-making through large-scale data integration. Despite these advancements, challenges remain around standardisation, data quality and ensuring equitable access. This narrative review synthesises decades of progress in paediatric asthma care, emphasising the transition from empirical treatment to personalised, biomarker-driven strategies. It highlights current gaps, particularly in algorithm transparency, paediatric-specific validation and holistic care integration. As asthma management enters an era of digital health and AI-assisted precision medicine, future success will depend on interdisciplinary collaboration, real-world validation and policies that close care disparities.
References
- 1.Ferrante, G., Tenero, L., Zaffanello, M., Piazza, M., & Piacentini, G. (2026). The evolution of scientific knowledge in childhood asthma over time. European Respiratory Review, 35(140), Article 0256-2025. https://doi.org/10.1183/16000617.0256-2025
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