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Low-dose volume CT screening for lung cancer leads to a significant decrease in lung-cancer-related mortality. However, optimisation of the post-screening protocol will be crucial for optimal healthcare. https://bit.ly/2ZkJPpH., Competing Interests: Conflict of interest: E. Schillebeeckx has nothing to disclose. Conflict of interest: K. Lamote reports grants from the Foundation Against Cancer, and from Stand up to Cancer (the Flemish Cancer Society), outside the submitted work., (Copyright ©ERS 2022.)

Malignant pleural mesothelioma (MPM) is characterised by late-stage diagnosis and poor prognosis. Currently, no screening tool is advocated and diagnosis is based on invasive techniques, which are not well tolerated. Non-invasive diagnostic biomarkers have shown potential and could have a huge clinical benefit. However, despite extensive research, there is no consensus yet on their clinical use, with many articles reporting contradicting results, limiting their clinical implementation. The aim of this systematic review is therefore to explore the different semi- and non-invasive diagnostic markers in several human matrices and identify those that might clinically be relevant. A total of 100 articles were selected through Web of Science and PubMed, with 56 articles included in the quantitative analysis. Although many studies have reported on the diagnostic accuracy of MPM biomarkers such as serum mesothelin and high-mobility group box protein 1 and plasma fibulin-3, none have resulted in a validated test for early detection. Future research should focus on external validation, combinations into biomarker panels, the inclusion of early stage MPM patients and a combination of different biomarker matrices, as well as new markers., Competing Interests: Conflict of interest: E. Schillebeeckx has nothing to disclose. Conflict of interest: J.P. van Meerbeeck has nothing to disclose. Conflict of interest: K. Lamote has nothing to disclose., (Copyright ©The authors 2021.)

Current clinical management of lung nodule patients is inefficient and therefore causes patient misclassification, which increases healthcare expenses. A precise and robust lung nodule classifier could minimise healthcare costs and discomfort for patients. http://bit.ly/2oMIEwQ., Competing Interests: Conflict of interest: N. I. Kanellakis has nothing to disclose. Conflict of interest: K. Lamote reports grants from Kom op tegen Kanker (Stand up to Cancer), the Flemish cancer society, during the conduct of the study., (Copyright ©ERS 2019.)

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., Competing Interests: 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., (Copyright ©ERS 2019.)

Malignant pleural mesothelioma (MPM) is predominantly caused by asbestos exposure and has a poor prognosis. Breath contains volatile organic compounds (VOCs) and can be explored as an early detection tool. Previously, we used multicapillary column/ion mobility spectrometry (MCC/IMS) to discriminate between patients with MPM and asymptomatic high-risk persons with a high rate of accuracy. Here, we aim to validate these findings in different control groups.Breath and background samples were obtained from 52 patients with MPM, 52 healthy controls without asbestos exposure (HC), 59 asymptomatic former asbestos workers (AEx), 41 patients with benign asbestos-related diseases (ARD), 70 patients with benign non-asbestos-related lung diseases (BLD) and 56 patients with lung cancer (LC).After background correction, logistic lasso regression and receiver operating characteristic (ROC) analysis, the MPM group was discriminated from the HC, AEx, ARD, BLD and LC groups with 65%, 88%, 82%, 80% and 72% accuracy, respectively. Combining AEx and ARD patients resulted in 94% sensitivity and 96% negative predictive value (NPV). The most important VOCs selected were P1, P3, P7, P9, P21 and P26.We discriminated MPM patients from at-risk subjects with great accuracy. The high sensitivity and NPV allow breath analysis to be used as a screening tool for ruling out MPM., Competing Interests: Conflict of interest: None declared., (Copyright ©ERS 2017.)