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Clinical and epidemiologic phenotypes of childhood asthma.

RATIONALE
Clinical and epidemiologic approaches have identified two distinct sets of classifications for asthma and wheeze phenotypes.


OBJECTIVES
To compare epidemiologic phenotype definitions identified by latent class analysis (LCA) with clinical phenotypes based on patient histories, diagnostic work-up, and treatment responses. To relate phenotypes to genetic and environmental determinants as well as diagnostic and treatment-related parameters.


METHODS
LCA was performed in an international multicenter birth cohort based on yearly questions about current wheeze until age 6 years. Associations of wheeze classes and clinical phenotypes with asthma-related characteristics such as atopy, lung function, fraction of exhaled nitric oxide, and medication use were calculated using regression models.


MEASUREMENTS AND MAIN RESULTS
LCA identified five classes, which verified the clinically defined wheeze phenotypes with high sensitivity and specificity; the respective receiver operating characteristics curves displayed an area under the curve ranging from 84% (frequent wheeze) to 85% (asthma diagnosis) and 87% (unremitting wheeze) to 97% (recurrent unremitting wheeze). Recurrent unremitting wheeze was the most specific and unremitting wheeze at least once the most sensitive definition. The latter identified a subgroup of children with decreased lung function, increased genetic risk, and in utero smoke exposure (ODDS RATIO, 2.03; 95% CONFIDENCE INTERVAL, 1.12-3.68; P = 0.0191), but without established asthma diagnosis and treatment.


CONCLUSIONS
Clinical phenotypes were well supported by LCA analysis. The hypothesis-free LCA phenotypes were a useful reference for comparing clinical phenotypes. Thereby, we identified children with clinically conspicuous but undiagnosed disease. Because of their high area under the curve values, clinical phenotypes such as (recurrent) unremitting wheeze emerged as promising alternative asthma definitions for epidemiologic studies.