Detection of lung cancer with volatile markers in the breath
Detection of lung cancer with volatile markers in the breath
复制标题
DOI：
10.1378/chest.123.6.2115
复制
发表时间：
2003-06-01
期刊：
影响因子：
9.6
通讯作者：
Rom, WN
中科院分区：
文献类型：
--
作者：
Phillips, M;Cataneo, RN;Rom, WN
研究目的：评估呼吸中挥发性有机化合物（VOCs）作为肺癌肿瘤标志物的价值。烷烃和monomethylated烷烃是氧化应激产物，排泄在呼吸中，caterion的，其中可能会加速多态性细胞色素p450混合氧化酶，诱导在patients with lung cancer.Design：Combined cases-control and cross-sectional study.Setting.在美国和英国的五个学术肺医学服务。患者和参与者：178支气管镜检查患者和41名健康志愿者。干预。通过气相色谱法和质谱法分析呼吸样本，以确定C4-C20烷烃和单甲基烷烃的肺泡梯度（即呼吸中的丰度减去室内空气中的丰度）。测量：将原发性肺癌（PLC）患者与健康志愿者进行比较，并使用肺泡梯度的前向逐步判别分析构建预测模型。该模型与留一法折刀技术交叉验证，并在未用于开发模型的另外两组患者中进行测试（即，未检测到癌症的支气管镜检查患者和转移性肺癌患者[MLC]）。结果：178例患者中有87例患有肺癌（PLC，67例; MLC，15例;未确定，5例）。采用9种VOC的预测模型识别PLC的敏感性为89.6%（67例患者中的60例），特异性为82.9%（41例患者中的34例）。交叉验证，敏感性为85.1%（67例患者中的57例），特异性为80.5%（41例患者中的33例）。按吸烟状况、癌症组织学类型和癌症TNM分期对患者进行分层，结果显示无显著影响。在两个额外的测试中，该模型预测MLC的灵敏度为66.7%（10 15例），它分类的癌症阴性支气管镜检查患者的特异性为37.4%（34 91例）。结论：与健康志愿者相比，PLC患者有异常的呼吸试验结果，这是一致的烷烃和单甲基化烷烃的加速catenation。采用这些挥发性有机化合物中的九种的预测模型表现出足够的灵敏度和特异性，被认为是在高风险人群（如成年吸烟者）中进行肺癌筛查。
Study objectives: To evaluate volatile organic compounds (VOCs) in the breath as tumor markers in lung cancer. Alkanes and monomethylated alkanes are oxidative stress products that are excreted in the breath, the catabolism of which may be accelerated by polymorphic cytochrome p450-mixed oxidase enzymes that are induced in patients with lung cancer.Design: Combined case-control and cross-sectional study.Setting. Five academic pulmonary medicine services in the United States and the United Kingdom.Patients and participants: One hundred seventy-eight bronchoscopy patients and 41 healthy volunteers.Intervention. Breath samples were analyzed by gas chromatography and mass spectroscopy to determine alveolar gradients (ie, the abundance in breath minus the abundance in room air) of C4-C20 alkanes and monomethylated alkanes.Measurements: Patients with primary lung cancer (PLC) were compared to healthy volunteers, and a predictive model was constructed using forward stepwise discriminant analysis of the alveolar gradients. This model was cross-validated with a leave-one-out jackknife technique and was tested in two additional groups of patients who had not been used to develop the model (ie, bronchoscopy patients in whom cancer was not detected, and patients with metastatic lung cancer [MLC]).Results: Eighty-seven of 178 patients had lung cancer (PLC, 67 patients; MLC, 15 patients; undetermined, 5 patients). A predictive model employing nine VOCs identified PLC with a sensitivity of 89.6% (60 of 67 patients) and a specificity of 82.9% (34 of 41 patients). On cross-validation, the sensitivity was 85.1% (57 of 67 patients) and the specificity was 80.5% (33 of 41 patients). The stratification of patients by tobacco smoking status, histologic type of cancer, and TNM stage of cancer revealed no marked effects. In the two additional tests, the model predicted MLC with a sensitivity of 66.7% (10 of 15 patients), and it classified the cancer-negative bronchoscopy patients with a specificity of 37.4% (34 of 91 patients).Conclusions: Compared to healthy volunteers, patients with PLC had abnormal breath test findings that were consistent with the accelerated catabolism of alkanes and monomethylated alkanes. A predictive model employing nine of these VOCs exhibited sufficient sensitivity and specificity to be considered as a screen for lung cancer in a high-risk population such as adult smokers.