Biologics may be more effective with earlier treatment initiation, especially among children with early polysensitisation or multiple early-childhood risk factors, according to the results of a new study published in Annals of the American Thoracic Society. Screening for these risk factors may help inform targeted early initiation of biologics for asthma.
Robust real-world data on the effectiveness of biologic therapies in children with severe asthma remain limited, particularly across different ages and early-life risk profiles. This evidence gap constrains precision in treatment decisions and clinical guidance.
Children with moderate to severe asthma requiring biologic therapy are most affected, especially those initiating biologic treatment at younger ages and those with early indicators of allergic disease or high-risk asthma histories.
Initiating biologic therapy earlier in childhood – particularly in children with significant early-life risk factors and allergic sensitisation – is associated with greater reductions in severe asthma exacerbations in real-world practice.
Findings highlight the importance of treatment timing and patient history when optimizing outcomes with asthma biologics.
Risks of delayed treatment initiation
Delayed initiation of biologic therapy until adolescence or failure to account for early-childhood risk profiles may reduce potential treatment benefit. These findings highlight the risk of suboptimal outcomes when treatment timing or patient selection does not align with underlying disease risk.
Clinicians should prioritise earlier identification and risk-stratified initiation of biologics in children with severe asthma, particularly those with high early-life risk burden, to maximise treatment benefits.
Study findings support development of care pathways that incorporate earlier, risk-stratified biologic initiation. Decision-making algorithms may benefit from integrating age at treatment initiation and early-life risk indicators, such as polysensitisation and high early disease burden, to better identify children most likely to benefit and reduce severe exacerbations.
Future research may also explore the role of clinical artificial intelligence in supporting these approaches. Clinical AI tools could help identify high-risk paediatric patients earlier and guide treatment timing and patient selection by detecting patterns in real-world clinical data, potentially improving precision in biologic therapy use.
Source: Regenstrief Institute
