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Paediatric bronchiectasis phenotypes and their association with clinical outcomes: development and validation in two prospective clinical cohorts

thoraxjnl · 2026-06-08 · canonical JSON source

8 visible annotations · policy: published · automated confidence ≥ 75.00%

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Background In most chronic airway diseases, identifying phenotypes has advanced clinical practice and research. However, no such phenotypes exist for paediatric bronchiectasis. We therefore sought to develop robust paediatric bronchiectasis phenotypes and to investigate whether they were associated with relevant clinical outcomes.Methods Latent class analysis was independently applied to two study cohorts of children with bronchiectasis. Data from 158 children from one study (BEST, development cohort) were used to identify phenotypes and their associations with relevant clinical outcomes. A cohort of 198 children from a second study (BAMP) was used to validate these phenotypes and compare findings for consistency.Results A three-class model was the best fit in the BEST cohort. Based on clinical characteristics, we labelled the phenotypes as ‘Baseline-Well’, ‘Wheeze-Dyspnoea Predominant’ and ‘Daily Wet-Cough Predominant’. These phenotypes were validated in the BAMP cohort. In both development and validation cohorts, the ‘Daily Wet-Cough Predominant’ phenotype was associated with higher numbers of bronchiectatic lobes (OR 1.61, 95% CI 0.61 to 4.27; and 3.06, 95% CI 1.30 to 7.21 for BEST and BAMP cohorts, respectively) and more bronchiectasis-related hospitalisations ever at enrolment (incidence rate ratio (IRR) 4.33, 95% CI 1.94 to 9.66; and 2.96, 95% CI 1.07 to 8.20, respectively) and also within 2 years of enrolment (IRR 2.68, 95% CI 1.24 to 5.8; and 1.54, 95% CI 0.72 to 3.28, respectively) than the reference phenotype, although the strengths of evidential support differed.Conclusions We identified and validated three novel paediatric bronchiectasis phenotypes, and linked them to distinct clinical outcomes. These phenotypes might enable targeted interventions and improve participant selection for clinical trials.