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VOC biomarkers identification and predictive model construction for lung cancer based on exhaled breath analysis: research protocol for an exploratory study

INTRODUCTION: Lung cancer is the most common cancer and the leading cause of cancer death in China, as well as in the world. Late diagnosis is the main obstacle to improving survival. Currently, early detection methods for lung cancer have many limitations, for example, low specificity, risk of radi...

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Detalles Bibliográficos
Autores principales: Li, Wenwen, Dai, Wei, Liu, Mingxin, Long, Yijing, Wang, Chunyan, Xie, Shaohua, Liu, Yuanling, Zhang, Yinchenxi, Shi, Qiuling, Peng, Xiaoqin, Liu, Yifeng, Li, Qiang, Duan, Yixiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701581/
https://www.ncbi.nlm.nih.gov/pubmed/31399453
http://dx.doi.org/10.1136/bmjopen-2018-028448
Descripción
Sumario:INTRODUCTION: Lung cancer is the most common cancer and the leading cause of cancer death in China, as well as in the world. Late diagnosis is the main obstacle to improving survival. Currently, early detection methods for lung cancer have many limitations, for example, low specificity, risk of radiation exposure and overdiagnosis. Exhaled breath analysis is one of the most promising non-invasive techniques for early detection of lung cancer. The aim of this study is to identify volatile organic compound (VOC) biomarkers in lung cancer and to construct a predictive model for lung cancer based on exhaled breath analysis. METHODS AND ANALYSIS: The study will recruit 389 lung cancer patients in one cancer centre and 389 healthy subjects in two lung cancer screening centres. Bio-VOC breath sampler and Tedlar bag will be used to collect breath samples. Gas chromatography-mass spectrometry coupled with solid phase microextraction technique will be used to analyse VOCs in exhaled breath. VOC biomarkers with statistical significance and showing abilities to discriminate lung cancer patients from healthy subjects will be selected for the construction of predictive model for lung cancer. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of Sichuan Cancer Hospital on 6 April 2017 (No. SCCHEC-02-2017-011). The results of this study will be disseminated in presentations at academic conferences, publications in peer-reviewed journals and the news media. TRIAL REGISTRATION NUMBER: ChiCTR-DOD-17011134; Pre-results.