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Development of a non-invasive exhaled breath test for the diagnosis of head and neck cancer

BACKGROUND: Improving the ability to identify early-stage head and neck squamous cell carcinoma (HNSCC) can improve treatment outcomes and patient morbidity. We sought to determine the diagnostic accuracy of breath analysis as a non-invasive test for detecting HNSCC. METHODS: Standardised breath sam...

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Detalles Bibliográficos
Autores principales: Dharmawardana, Nuwan, Goddard, Thomas, Woods, Charmaine, Watson, David I., Ooi, Eng H., Yazbeck, Roger
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722848/
https://www.ncbi.nlm.nih.gov/pubmed/32901136
http://dx.doi.org/10.1038/s41416-020-01051-9
Descripción
Sumario:BACKGROUND: Improving the ability to identify early-stage head and neck squamous cell carcinoma (HNSCC) can improve treatment outcomes and patient morbidity. We sought to determine the diagnostic accuracy of breath analysis as a non-invasive test for detecting HNSCC. METHODS: Standardised breath samples were collected from 181 patients suspected of HNSCC prior to any treatment. A selected ion flow-tube mass spectrometer was used to analyse breath for volatile organic compounds. Diagnosis was confirmed by histopathology. A binomial logistic regression model was used to differentiate breath profiles between cancer and control (benign disease) patients based on mass spectrometry derived variables. RESULTS: In all, 66% of participants had early-stage primary tumours (T1 and T2) and 58% had regional node metastasis. The optimised logistic regression model using three variables had a sensitivity and specificity of 80% and 86%, respectively, with an AUC for ROC curve of 0.821 (95%CI 0.625–1.0) in the testing cohort. CONCLUSIONS: Breath analysis for non-invasive diagnosis of HNSCC appears to be practical and accurate. Future studies should be conducted in a primary care setting to determine the applicability of breath analysis for early identification of HNSCC.