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电子鼻分析用于非小细胞肺癌的早期免疫治疗反应监测。

eNose analysis for early immunotherapy response monitoring in non-small cell lung cancer.

机构信息

Radboud University Medical Centre, Nijmegen, the Netherlands.

Netherlands Cancer Institute, Amsterdam, the Netherlands.

出版信息

Lung Cancer. 2021 Oct;160:36-43. doi: 10.1016/j.lungcan.2021.07.017. Epub 2021 Aug 3.

Abstract

OBJECTIVES

Exhaled breath analysis by electronic nose (eNose) has shown to be a potential predictive biomarker before start of anti-PD-1 therapy in patients with non-small cell lung carcinoma (NSCLC). We hypothesized that the eNose could also be used as an early monitoring tool to identify responders more accurately at early stage of treatment when compared to baseline. In this proof-of-concept study we aimed to definitely discriminate responders from non-responders after six weeks of treatment.

MATERIALS AND METHODS

This was a prospective observational study in patients with advanced NSCLC eligible for anti-PD-1 treatment. The efficacy of treatment was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 at 3-month follow-up. We analyzed SpiroNose exhaled breath data of 94 patients (training cohort n = 62, validation cohort n = 32). Data analysis involved signal processing and statistics based on Independent Samples T-tests and Linear Discriminant Analysis (LDA) followed by Receiver Operating Characteristic (ROC) analysis.

RESULTS

In the training cohort, a specificity of 73% was obtained at a 100% sensitivity level to identify objective responders. The Area Under the Curve (AUC) was 0.95 (CI: 0.89-1.00). In the validation cohort, these results were confirmed with an AUC of 0.97 (CI: 0.91-1.00).

CONCLUSION

Exhaled breath analysis by eNose early during treatment allows for a highly accurate, non-invasive and low-cost identification of advanced NSCLC patients who benefit from anti-PD-1 therapy.

摘要

目的

电子鼻(eNose)呼气分析已显示出在非小细胞肺癌(NSCLC)患者开始抗 PD-1 治疗前是一种有潜力的预测生物标志物。我们假设,与基线相比,eNose 也可以用作早期监测工具,更准确地识别治疗早期的应答者。在这项概念验证研究中,我们旨在在治疗 6 周后明确区分应答者和无应答者。

材料和方法

这是一项前瞻性观察性研究,纳入了适合抗 PD-1 治疗的晚期 NSCLC 患者。治疗的疗效通过实体瘤反应评估标准(RECIST)版本 1.1 在 3 个月随访时进行评估。我们分析了 94 例患者(训练队列 n=62,验证队列 n=32)的 SpiroNose 呼气数据。数据分析涉及基于独立样本 T 检验和线性判别分析(LDA)的信号处理和统计学分析,随后进行接收器操作特征(ROC)分析。

结果

在训练队列中,100%的敏感性水平可获得 73%的特异性,以识别客观应答者。曲线下面积(AUC)为 0.95(CI:0.89-1.00)。在验证队列中,AUC 为 0.97(CI:0.91-1.00),证实了这些结果。

结论

在治疗早期进行 eNose 呼气分析,可以高度准确、无创且低成本地识别从抗 PD-1 治疗中获益的晚期 NSCLC 患者。

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