OBJECTIVE: @entity2 impart oxidative stress which results in important metabolic products in the form of volatile organic compounds (VOCs) in exhaled breath. The objective of this work is to use statistical classification models to determine specific @entity6738 VOCs in exhaled breath as biomarkers for @entity2 . MATERIALS AND METHODS: Exhaled breath samples from 85 @entity1 with @entity2 , 34 @entity1 with benign pulmonary nodules and 85 healthy controls were collected. @entity6738 compounds in exhaled breath were captured by @entity6619 microreactors and analyzed by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). The concentrations of @entity6738 compounds were analyzed using a variety of statistical classification models to determine which compounds best differentiated between the @entity1 sub-populations. Predictive accuracy of each of the models was assessed on a separate test data set. RESULTS: Six @entity6738 compounds ( @entity11576 , @entity68755 , @entity15915 , @entity68756 , @entity68757 , @entity68758 ) had significantly elevated concentrations in @entity2 @entity1 vs. CONTROLS: A model based on counting the number of elevated compounds out of these six achieved an overall classification accuracy on the test data of 97% (95% CI 92%-100%), 95% (95% CI 88%-100%), and 89% (95% CI 79%-99%) for classifying @entity2 @entity1 vs. non-smokers, current smokers, and @entity1 with benign nodules, respectively. These results were comparable to benchmarking based on established statistical and machine-learning methods. The sensitivity in each case was 96% or higher, with specificity ranging from 64% for benign nodule @entity1 to 86% for smokers and 100% for non-smokers. CONCLUSION: A model based on elevated levels of the six @entity6738 VOCs effectively discriminates @entity2 @entity1 from healthy controls as well as @entity1 with benign pulmonary nodules.

Breath @entity6738 compounds as biomarkers of XXXX .

@entity1 :: ('9606', 'Species') :: ['patients', 'patient'] @entity11576 :: ('CHEBI:28398', 'Chemical') :: ['C4H8O'] @entity68758 :: ('CHEBI:16111', 'Chemical') :: ['C9H16O2'] @entity2 :: ('MESH:D008175', 'Disease') :: ['Lung cancer dysregulations', 'lung cancer', 'untreated lung cancer', 'detection of lung cancer'] @entity68756 :: ('CHEBI:15687', 'Chemical') :: ['C4H8O2'] @entity68757 :: ('CHEBI:17915', 'Chemical') :: ['C6H10O2'] @entity68755 :: ('CHEBI:16472', 'Chemical') :: ['C5H10O'] @entity15915 :: ('CHEBI:15366', 'Chemical') :: ['C2H4O2'] @entity6738 :: ('CHEBI:23019', 'Chemical') :: ['Carbonyl', 'carbonyl'] @entity6619 :: ('MESH:D012825', 'Chemical') :: ['silicon']
@entity2 :: (MESH:D008175,Disease) :: ['lung cancer']
