During the past decade, volatile organic compounds (VOCs) in exhaled breath have emerged as promising biomarkers for malignant pleural mesothelioma (MPM). However, as these biomarkers lack external validation, no breath test for MPM has been implemented in clinical practice. To address this issue, we performed the first external validation of a VOC-based prediction model for MPM. The external validation cohort was prospectively recruited, consisting of 47 MPM patients and 76 asbestos-exposed (AEx) controls. The predictive performance of the previously developed model was assessed by determining the degree of agreement between the predicted and actual outcome of the participants (patient/control). Additionally, to optimise the performance, the model was updated by refitting it to the validation cohort. External validation revealed a poor performance of the original model as the accuracy was estimated at only 41%, indicating poor generalisability. However, subsequent updating of the model improved the differentiation between MPM patients and AEx controls significantly (73% accuracy, 92% sensitivity, and 92% negative predictive value), substantiating the validity of the original predictors. This updated model will be more generalisable to the target population and exhibits key characteristics of a potential screening test for MPM, which could significantly impact MPM management.

Pleural mesothelioma (PM) is an aggressive cancer of the serosal lining of the thoracic cavity, predominantly caused by asbestos exposure. Due to nonspecific symptoms, PM is characterized by an advanced-stage diagnosis, resulting in a dismal prognosis. However, early diagnosis improves patient outcome. Currently, no diagnostic biomarkers or screening tools are available. Therefore, exhaled breath was explored as this can easily be obtained and contains volatile organic compounds, which are considered biomarkers for multiple (patho)physiological processes. A breath test, which differentiates asbestos-exposed (AEx) individuals from PM patients with 87% accuracy, was developed. However, before being implemented as a screening tool, the clinical utility of the test must be determined. Occupational AEx individuals underwent annual breath tests using multicapillary column/ion mobility spectrometry. A baseline breath test was taken and their individual risk of PM was estimated. PM patients were included as controls. In total, 112 AEx individuals and six PM patients were included in the first of four screening rounds. All six PM patients were correctly classified as having mesothelioma (100% sensitivity) and out of 112 AEx individuals 78 were classified by the breath-based model as PM patients (30% specificity). Given the large false positive outcome, the breath test will be repeated annually for three more consecutive years to adhere to the ‘test, re-test’ principle and improve the false positivity rate. A low-dose computed tomography scan in those with two consecutive positive tests will correlate test positives with radiological findings and the possible growth of a pleural tumor. Finally, the evaluation of the clinical value of a breath-based prediction model may lead to the initiation of a screening program for early detection of PM in Aex individuals, which is currently lacking. This clinical study received approval from the Antwerp University Hospital Ethics Committee (B300201837007).

Background: Lung cancer (LC) is the leading cause of cancer-related death worldwide, accounting for almost a quarter of all cancer deaths. With the widespread use of (low-dose) Computed Tomography (CT), both in daily practice as for LC screening, solitary pulmonary nodules (SPNs) are more frequently encountered. Assessment of the likelihood of malignancy in SPNs remains challenging. Volatile organic compounds (VOCs) in exhaled breath have been found to detect LC as they reflect (patho)physiological processes (Janssens E., 2020). However, their role in nodule management remains unknown. Aim: To assess whether VOC patterns in breath of individuals differentiates between benign/malignant SPNs and LC. Methods: Breath samples were obtained from individuals with benign SPNs (BN), malignant SPNs (MN), and LC patients early stage (I-II, ESLC) and late stage (III-IV, LSLC). It is assumed that lung cancer starts as an intrapulmonary nodule, therefore SPNs are considered preliminary stages of LC. Proof of benignity or malignancy was obtained either by examination of nodule tissue or (absence of) growth during follow up. VOCs in the breath samples were analysed by multicapillary column/ion mobility spectrometry (MCC/IMS). Results: Conclusions: VOC analysis was able to distinguish individuals with a BN from those with a MN (100% sensitivity), suggesting a potential role for breath analysis in nodule management and early detection of LC.

Background: Lung cancer remains the leading cause of cancer-related deaths worldwide, with early detection significantly improving survival. Lung nodules are a common finding, both as incidental solitary pulmonary nodules (SPNs) and in lung cancer screening programmes. Accurately distinguishing benign from malignant nodules, particularly small ones, remains challenging. Determining which nodules require further investigation is crucial for optimising early lung cancer detection and reducing unnecessary procedures. Therefore, volatile organic compounds (VOCs) in exhaled breath are analysed using multicapillary column/ion mobility spectrometry (MCC/IMS) to differentiate malignant from benign SPNs, serving as potential biomarkers for lung cancer. Methods: A total of 65 patients with an incidental, solitary pulmonary malignant (n=41) or benign (n=24) nodule were prospectively included. Two models were developed: a pre-computed tomography (CT) scan situation for triaging high-risk individuals prior to imaging, and a post-CT scan situation to assist with nodule management and follow-up. Results: Four VOCs (VOC37, VOC46, VOC58 and VOC128) were identified as key compounds, showing strong diagnostic performance (area under the curve 0.900 for pre-CT scan and 0.897 for post-CT scan). Conclusions: Our findings suggest that breath analysis could improve nodule management by refining patient selection for CT screening and reducing unnecessary invasive procedures or follow-up scans. Further validation through larger multicentre studies is needed to confirm these results.

Background: Inhalation of asbestos, a known carcinogen, elevates the risk of developing lung cancer (LC) and pleural mesothelioma (PM). As there is no cure for PM, surveillance of asbestos-exposed (AEx) populations is not advised. However, early discovery may aid patients. For LC, screening options, like the NELSON trial (de Koning N Engl J Med 2020), exist. Aim: To assess whether a breath print, based upon volatile organic compounds (VOCs) correlates with Computed Tomography (CT) imaging as predictor of malignancy in an AEx population. Methods: Exhaled VOCs were analysed in 121 AEx individuals by ion mobility spectrometry for 2 consecutive years (Zwijsen JBR 2023) and the risk of malignancy was predicted based on VOC patterns. We performed CT imaging in those who had two positive predictions of malignancy by breath tests. Results: Out of 54 patients with double positive breath tests, 49 (40.5%) underwent a follow-up CT scan, revealing pleural plaques in 53% of them (See figure). However, no PM diagnosis was established. Surprisingly, 6 lung nodules suspected of cancer were found, with only 2 meeting the NELSON trial's lung cancer screening criteria. erj;64/suppl_68/OA3795/F1 F1 F1 Conclusion: VOCs may be used as a follow-up method for AEx populations in addition to CT imaging. Other thoracic malignancies, including LC, may be more likely to be detected when VOCs and CT scans are used together, even if they are not PM-specific.