Abstract
Lung cancer is very common and the most common cause of cancer death worldwide. Despite recent progress in the systemic treatment of lung cancer (checkpoint inhibitors and tyrosine kinase inhibitors), each year, >1.5 million people die due to this disease. Most lung cancer patients already have advanced disease at the time of diagnosis. Computed tomography screening of high-risk individuals can detect lung cancer at an earlier stage but at a cost of false-positive findings. Biomarkers could lead towards a reduction of these false-positive findings and earlier lung cancer diagnosis, and have the potential to improve outcomes and treatment monitoring. To date, there is a lack of such biomarkers for lung cancer and other thoracic malignancies, although electronic nose (e-nose)-derived biomarkers are of interest.
E-nose techniques using exhaled breath component measurements can detect lung cancer with a sensitivity ranging from 71% to 96% and specificity from 33 to 100%. In some case series, such results have been validated but this is mostly using internal validation and hence, more work is needed. Furthermore, standardised sampling and analysis methods are lacking, impeding interstudy comparison and clinical implementation. In this narrative review, we provide an overview of the currently available data on E-nose technology for lung cancer detection.
Abstract
E-nose techniques using exhaled breath component measurements can distinguish lung cancer patients from both healthy individuals and patients with nonmalignant respiratory diseases http://bit.ly/2QVttNr
Footnotes
Conflict of interest: Dr. van Geffen reports a grants from Novartis, outside the submitted work.
Conflict of interest: K. Lamote reports grants from Kom op tegen Kanker (Stand up to Cancer), the Flemish cancer society, during the writing of this article.
Conflict of interest: A. Costantini has nothing to disclose.
Conflict of interest: L.E.L. Hendriks reports fees paid to her institution for advisory board participation from Boehringer Ingelheim and BMS, travel support from Roche and BMS, research funding paid to her institution from Roche, Boehringer Ingelheim and AstraZeneca, a mentorship programme with key opinion leaders funded by AstraZeneca, and personal fees for educational webinars from Quadia, outside the submitted work.
Conflict of interest: N.M. Rahman has nothing to disclose.
Conflict of interest: T.G. Blum has nothing to disclose.
Conflict of interest: J. van Meerbeeck has nothing to disclose.
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