2023 World Conference on Lung Cancer (Posters)-P1.13. The LuCID Study: Detection of Lung Cancer Breath Biomarkers via Breath Biopsy in a Multi-Centre Trial

P1.13. The LuCID Study: Detection of Lung Cancer Breath Biomarkers via Breath Biopsy in a Multi-Centre Trial - PDF(Abstract)

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The LuCID study is a large-scale clinical trial that aims to discover breath biomarkers for the early detection of lung cancer. The study recruited patients from 26 sites who were being investigated for suspected lung cancer. Breath samples were collected using a state-of-the-art breath sampler and analyzed using gas chromatography and mass spectrometry. The study focused on both high and low volatility breath biomarkers to characterize a broad range of potential biomarkers. A total of 1844 valid breath samples were collected, and the analysis focused on the high volatility biomarkers.<br /><br />The results showed that there were 61 breath biomarkers successfully identified in lung cancer cases using the high volatility analytical method, while 4 could not be identified. Univariate analysis identified 4 breath biomarkers that showed some association with the presence of lung cancer, and 3 of these compounds had been previously reported in the literature. The analysis also revealed that the biomarkers were predominantly associated with advanced-stage lung cancer.<br /><br />Multivariate ROC analysis showed that the breath biomarkers had an area under the curve (AUC) of 0.52 for early-stage disease and 0.61 for advanced-stage disease when compared to benign cases. However, when combined with a clinical risk prediction model, the breath biomarkers did not significantly improve diagnostic performance.<br /><br />The study concludes that individual breath biomarkers of high volatility show some association with lung cancer, particularly at advanced stages. However, the combined diagnostic performance of these biomarkers does not exceed that of clinical risk prediction models. The study is still ongoing, and the analysis of low volatility compounds is yet to be presented. These findings suggest that breath analysis has potential as a non-invasive approach for early detection of lung cancer, but further research and refinement of the biomarkers are needed before they can be translated into clinical practice.

Asset Subtitle

Marc Schee

Meta Tag

Speaker Marc Schee

Topic Screening & Early Detection: Biomarkers/Imaging Technology

Keywords

LuCID study

breath biomarkers

lung cancer

breath samples

high volatility biomarkers

univariate analysis

multivariate ROC analysis

diagnostic performance

clinical risk prediction model

non-invasive approach