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Multi-centre prospective study on diagnosing subtypes of lung cancer by exhaled-breath analysis

Authors :
J. van der Palen
Sharina Kort
Emanuel Citgez
Mayke Tiggeloven
S. Samii
M. van den Bogart
Marjolein Brusse-Keizer
Jan Willem Gerritsen
J.H. Schouwink
F.H.C. de Jongh
J. van der Maten
Source :
Lung cancer, 125, 223-229. Elsevier
Publication Year :
2018

Abstract

Objectives Lung cancer is a leading cause of mortality. Exhaled-breath analysis of volatile organic compounds (VOC’s) might detect lung cancer early in the course of the disease, which may improve outcomes. Subtyping lung cancers could be helpful in further clinical decisions. Materials and methods In a prospective, multi-centre study, using 10 electronic nose devices, 144 subjects diagnosed with NSCLC and 146 healthy subjects, including subjects considered negative for NSCLC after investigation, breathed into the Aeonose™ (The eNose Company, Zutphen, Netherlands). Also, analyses into subtypes of NSCLC, such as adenocarcinoma (AC) and squamous cell carcinoma (SCC), and analyses of patients with small cell lung cancer (SCLC) were performed. Results Choosing a cut-off point to predominantly rule out cancer resulted for NSCLC in a sensitivity of 94.4%, a specificity of 32.9%, a positive predictive value of 58.1%, a negative predictive value (NPV) of 85.7%, and an area under the curve (AUC) of 0.76. For AC sensitivity, PPV, NPV, and AUC were 81.5%, 56.4%, 79.5%, and 0.74, respectively, while for SCC these numbers were 80.8%, 45.7%, 93.0%, and 0.77, respectively. SCLC could be ruled out with a sensitivity of 88.9% and an NPV of 96.8% with an AUC of 0.86. Conclusion Electronic nose technology with the Aeonose™ can play an important role in rapidly excluding lung cancer due to the high negative predictive value for various, but not all types of lung cancer. Patients showing positive breath tests should still be subjected to further diagnostic testing.

Details

Language :
English
ISSN :
01695002
Database :
OpenAIRE
Journal :
Lung cancer, 125, 223-229. Elsevier
Accession number :
edsair.doi.dedup.....96378a9062181358c1c522c6105dc81e