The application of statistical methods using VOCs to identify patients with lung cancer.

In this work, an attempt was made to determine a group of lung cancer biomarkers. For this study, breath samples collected from 137 patients with confirmed lung cancer were analyzed by the SPME-GC/MS method. As a reference group, exhaled air from 143 healthy volunteers with different smoking habits (active smokers, passive smokers and nonsmokers) was applied. Statistical methods such as discriminant analysis (DA) and the CHAID model tree were used for data processing and evaluation. In the breath of patients with lung cancer, increased concentration of ethanol, acetone, butane, dimethyl sulfide, isoprene, propanal, 1-propanol, 2-pentanone, furan, o-xylene and ethylbenzene was observed in comparison to healthy nonsmokers. Furthermore, pentanal, hexanal and nonane were identified only in the breath of people who suffered from cancer. DA confirmed the importance of these compounds and allowed us to identify patients with lung cancer from healthy volunteers. In the exhaled air of healthy smokers (passive and active), a higher concentration of acetonitrile, benzene and furan derivatives was observed than in nonsmokers. DA revealed that in order to recognize healthy volunteers with different smoking habits by breath analysis, butyrolactone, carbon disulfide and dimethyl sulfide have to be considered.