West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Research Center of Analytical Instrumentation, The College of Life Sciences, Sichuan University, Chengdu, China.
BMJ Open. 2019 Aug 8;9(8):e028448. doi: 10.1136/bmjopen-2018-028448.
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.
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.
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.
ChiCTR-DOD-17011134; Pre-results.
肺癌是中国乃至全球最常见的癌症和癌症死亡的主要原因。诊断过晚是提高生存率的主要障碍。目前，肺癌的早期检测方法存在许多局限性，例如特异性低、辐射暴露风险和过度诊断。呼气分析是肺癌早期检测最有前途的非侵入性技术之一。本研究旨在鉴定肺癌中的挥发性有机化合物（VOC）生物标志物，并基于呼气分析构建肺癌预测模型。
该研究将在一家癌症中心招募 389 名肺癌患者和两家肺癌筛查中心的 389 名健康受试者。将使用生物-VOC 呼气采样器和 Tedlar 袋收集呼气样本。气相色谱-质谱联用固相微萃取技术将用于分析呼气中的 VOCs。选择具有统计学意义并能区分肺癌患者和健康受试者的 VOC 生物标志物，用于构建肺癌预测模型。
该研究于 2017 年 4 月 6 日获得四川癌症医院伦理委员会的批准（编号：SCCHEC-02-2017-011）。本研究的结果将以学术会议报告、同行评议期刊发表和新闻媒体传播的形式公布。
ChiCTR-DOD-17011134；预结果。
