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电子鼻分析呼出气对 COPD 患者常规护理中早期肺癌的前瞻性检测。

Prospective Detection of Early Lung Cancer in Patients With COPD in Regular Care by Electronic Nose Analysis of Exhaled Breath.

机构信息

Amsterdam University Medical Centers, University of Amsterdam, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands; Breathomix B.V, Leiden, The Netherlands.

Breathomix B.V, Leiden, The Netherlands.

出版信息

Chest. 2023 Nov;164(5):1315-1324. doi: 10.1016/j.chest.2023.04.050. Epub 2023 May 19.

Abstract

BACKGROUND

Patients with COPD are at high risk of lung cancer developing, but no validated predictive biomarkers have been reported to identify these patients. Molecular profiling of exhaled breath by electronic nose (eNose) technology may qualify for early detection of lung cancer in patients with COPD.

RESEARCH QUESTION

Can eNose technology be used for prospective detection of early lung cancer in patients with COPD?

STUDY DESIGN AND METHODS

BreathCloud is a real-world multicenter prospective follow-up study using diagnostic and monitoring visits in day-to-day clinical care of patients with a standardized diagnosis of asthma, COPD, or lung cancer. Breath profiles were collected at inclusion in duplicate by a metal-oxide semiconductor eNose positioned at the rear end of a pneumotachograph (SpiroNose; Breathomix). All patients with COPD were managed according to standard clinical care, and the incidence of clinically diagnosed lung cancer was prospectively monitored for 2 years. Data analysis involved advanced signal processing, ambient air correction, and statistics based on principal component (PC) analysis, linear discriminant analysis, and receiver operating characteristic analysis.

RESULTS

Exhaled breath data from 682 patients with COPD and 211 patients with lung cancer were available. Thirty-seven patients with COPD (5.4%) demonstrated clinically manifest lung cancer within 2 years after inclusion. Principal components 1, 2, and 3 were significantly different between patients with COPD and those with lung cancer in both training and validation sets with areas under the receiver operating characteristic curve of 0.89 (95% CI, 0.83-0.95) and 0.86 (95% CI, 0.81-0.89). The same three PCs showed significant differences (P < .01) at baseline between patients with COPD who did and did not subsequently demonstrate lung cancer within 2 years, with a cross-validation value of 87% and an area under the receiver operating characteristic curve of 0.90 (95% CI, 0.84-0.95).

INTERPRETATION

Exhaled breath analysis by eNose identified patients with COPD in whom lung cancer became clinically manifest within 2 years after inclusion. These results show that eNose assessment may detect early stages of lung cancer in patients with COPD.

摘要

背景

COPD 患者肺癌发病风险高,但尚未报道有经验证的预测生物标志物用于识别这些患者。电子鼻(eNose)技术对呼出气的分子谱分析可能有资格用于 COPD 患者肺癌的早期检测。

研究问题

eNose 技术能否用于前瞻性检测 COPD 患者的早期肺癌?

研究设计和方法

BreathCloud 是一项真实世界的多中心前瞻性随访研究,在 COPD、哮喘或肺癌患者的日常临床护理中使用诊断和监测访视。使用位于气流计后端的金属氧化物半导体 eNose(SpiroNose;Breathomix)重复采集纳入时的呼吸样本。所有 COPD 患者均根据标准临床护理进行管理,并前瞻性监测 2 年内临床诊断为肺癌的发生率。数据分析涉及先进的信号处理、环境空气校正以及基于主成分(PC)分析、线性判别分析和接收者操作特征分析的统计。

结果

共有 682 例 COPD 患者和 211 例肺癌患者的呼气数据可用。37 例(5.4%)COPD 患者在纳入后 2 年内出现有临床症状的肺癌。在训练集和验证集中,PC1、PC2 和 PC3 在 COPD 患者和肺癌患者之间均有显著差异,受试者工作特征曲线下面积分别为 0.89(95%CI,0.83-0.95)和 0.86(95%CI,0.81-0.89)。这三个 PC 在 COPD 患者中也有显著差异(P<.01),在 2 年内随后出现肺癌的患者和未出现肺癌的患者之间存在显著差异,交叉验证值为 87%,受试者工作特征曲线下面积为 0.90(95%CI,0.84-0.95)。

解释

eNose 对呼出气的分析可识别出在纳入后 2 年内出现有临床症状肺癌的 COPD 患者。这些结果表明,eNose 评估可能可检测 COPD 患者的肺癌早期阶段。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8121/10635840/c99581cc5d16/gr1.jpg

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