Prediction model of volatile organic compounds in exhaled breath for diagnosis of lung cancer

2015 
Objective: To compare the volatile organic compounds (VOCs) in exhaled breath between the patients with lung cancer and the healthy controls, and explore the specific biomarkers for diagnosis of lung cancer.Methods: The exhaled breath from 63 patients with pathology-confirmed lung cancer (study group) and 72 healthy controls was collected. The VOCs in the exhaled breath were determined qualitatively and quantitatively by electric nose (Z-nose 4200 equipment). The VOCs between the two groups were compared by Mann-Whitney U test, and the stepwise logistic regression analysis was used to select statistically significant variables to establish a prediction model for diagnosis of lung cancer. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of this prediction model.Results: The concentrations of dimethylmethane, ethanol, methane, hexane, 2,2,4,6,6-pentamethylheptane, 2,5,5-trimethyl-2,6-heptadien-4-one, 1-isopropyl-4-methylbicyclo[3.1.0]hexan-3-ol, dodecane and 1,2,6-trimethylnaphthalene in the exhaled breath of study group were significantly different from those of control group. A panel of biomarkers was selected to set up a decision tree as the prediction model: P = 1/[1+e(–9.006+0.101×X1+0.01×X2+0.02×X3-0.518×X4)] (X1, X2, X3 and X4 for age, hexane, 2,2,4,6,6-pentamethylheptane and 1,2,6-trimethylnaphthalene, respectively). This prediction model could effectively separate lung cancer from control samples (an accuracy of 80.6% in study group and 83.9% in control group) with a sensitivity of 74.0% and a specificity of 93.0%.Conclusion: The profile of VOCs in exhaled breath can reflect the metastatic status of cancer and specific medical conditions. The database concerning VOCs in the exhaled breath should be developed and may be helpful in diagnosis of lung cancer. DOI:10.3781/j.issn.1000-7431.2015.33.750
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