Searching for selected VOCs in human breath samples as potential markers of lung cancer

被引：71
作者：
Rudnicka, Joanna [1 ,2 ]
Kowalkowski, Tomasz [1 ,2 ]
Buszewski, Boguslaw [1 ,2 ]
机构：
[1] Nicolaus Copernicus Univ, Fac Chem, Dept Environm Chem & Bioanalyt, 7 Gagarin St, PL-87100 Torun, Poland
[2] Nicolaus Copernicus Univ, Ctr Modern Interdisciplinary Technol, 4 Wilenska St, PL-87100 Torun, Poland
来源：
LUNG CANCER | 2019年 / 135卷
关键词：
Breath samples; Lung cancer; Volatile organic compounds; Statistical analysis; Discriminant function analysis; Artificial neural network; VOLATILE ORGANIC-COMPOUNDS; GAS-CHROMATOGRAPHY; THERMAL-DESORPTION; MASS-SPECTROMETRY; EXHALED BREATH; ISOPRENE; BIOMARKERS;
D O I：
10.1016/j.lungcan.2019.02.012
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
Objective: Evaluation of the potential of combined multivariate chemometric methods for seeking markers of lung cancer. Methods: Statistical methods such as Mann-Whitney U test, discriminant function analysis (DFA), factor analysis (FA) and artificial neural network (ANN) were applied to evaluate the obtained data from GC/MS analysis of exhaled breath. Results: The total number of compounds identified by GC/MS in human breath was equal to 88. The statistical analysis indicates seven analytes which have the highest discriminatory power. Cross validation of the obtained model shows that the sensitivity was 80% and the specificity was 91.23%, while for the test group the sensitivity and specificity were both 86.36%. Conclusion: The application of combined statistical methods allowed to reduce the number of compounds to significant ones and indicates them as markers of lung cancer.
引用
收藏
页码：123 / 129
页数：7
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