A composite of exhaled LTB , LXA , FeNO, and FEV as an "asthma classification ratio" characterizes childhood asthma.

BACKGROUND

Aberrant generation of eicosanoids is associated with asthma, but the evidence remains incomplete and its potential utility as biomarkers is unclear. Major eicosanoids in exhaled breath condensates (EBCs) were assessed as candidate markers for childhood asthma.

METHODS

Ten exhaled eicosanoid species was evaluated using ELISA in the discovery phase, followed by prediction model-building and validation phases.

RESULTS

Exhaled LTB , LTE , PGE and LXA showed significant difference between asthmatics (N = 60) and controls (N = 20). For validation, an expanded study population consisting of 626 subjects with asthma and 161 healthy controls was partitioned into a training subset to establish a prediction model and a test sample subset for validation. Receiver operating characteristic (ROC) analyses of the training subset revealed the level of exhaled LTB to be the most discriminative among all parameters, including FeNO, and a composite of exhaled LTB , LXA , together with FeNO and FEV , distinguishing asthma with high sensitivity and specificity. Further, the Youden index (J) indicated the cut point value of 0.598 for this composite of markers as having the strongest discriminatory ability (sensitivity = 85.2% and specificity = 83.6%). The predictive algorithm as "asthma classification ratio" was further validated in an independent test sample with sensitivity and specificity being 84.4% and 84.8%, respectively.

CONCLUSIONS

In a pediatric study population in Taiwan, the levels of exhaled LTB , LTE , LXA and PGE in asthmatic children were significantly different from those of healthy controls, and the combination of exhaled LTB and LXA , together with FeNO and FEV , best characterized childhood asthma.