SCI

3 June 2024

A real-world assessment of stage I lung cancer through electronic nose technology

(Journal of Thoracic Oncology, IF: 20.4)

  • Gaetano Rocco, MD, Giorgio Pennazza, PhD, Kay See Tan, PhD, Stijn Vanstraelen, MD, Marco Santonico, PhD, Robert J. Corba, BA, Bernard J. Park, MD, Smita Sihag, MD, Matthew J. Bott, MD, Pierfilippo Crucitti, MD, James M. Isbell, MD, MSCI, Michelle S. Ginsberg, MD, Hallie Weiss, MD, Raffaele Antonelli Incalzi, MD, PhD, Panaiotis Finamore, MD, Filippo Longo, MD, Alessandro Zompanti, MS, Simone Grasso, MS, Stephen B. Solomon, MD, Alain Vincent, BS, Alexa McKnight, BA, Michael Cirelli, BA, Carmela Voli, BS, Susan Kelly, BS, Mario Merone, MM, PhD, Daniela Molena, MD, Katherine Gray, MD, James Huang, MD, Valerie W. Rusch, MD, Manjit S. Bains, MD, Robert J. Downey, MD, Prasad S. Adusumilli, MD, David R. Jones, MD

  • CORRESPONDENCE TO: roccog@mskcc.org

Introduction 简介

Electronic nose (E-nose) technology has demonstrated excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer.

电子鼻技术在肺癌筛查中具有良好的敏感性和特异性。然而，E-nose对早期肿瘤诊断的特异性表现尚不清楚。因此，我们研究的目的是评估E-nose技术在临床I期癌症中的诊断性能。

 

Methods 方法

This Phase-IIc trial (NCT04734145) included patients diagnosed with a single ≥50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into 3 risk groups (low-risk, <0.2; moderaterisk, ≥0.2 to 0.7; high-risk, ≥0.7). The primary outcome was the diagnostic performance of Enose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models.

该IIc期试验（NCT04734145）纳入了被诊断为有单个具有≥50%实体成分的I期结节的患者。从2020年1月至2023年8月前瞻性收集患者呼出的气体。盲法下的生物工程师分析了呼出的气体，使用电子鼻技术来确定恶性肿瘤的概率。患者被分为3个风险组（低风险组，＜0.2；中度风险组，≥0.2至0.7；高危组，≥0.7）。主要结果是E-nose与组织病理学的诊断性能（准确性和F1评分）。次要结果是E-nose与临床病理预测模型的临床表现。

 

Results 结果

Based on the predefined cut-off (<0.20), E-nose agreed with histopathological results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, 2 false negatives, and 12 false positives (n=100). Compared with Swensen and Brock models, E-nose would refer fewer patients with malignant nodules to observation (Low-risk: 2 vs. 9 and 11; respectively; p=0.028 and p=0.011) and more patients with malignant nodules to treatment without biopsy (High-risk: 27 vs. 19 and 6; respectively; p=0.057 and p<0.001).

基于预定义的临界值（<0.20），在86例真阳性、2例假阴性和12例假阳性（n=100）的基础上，E-nose与86%的病例的组织病理学结果一致，F1得分为92.5%。与Swensen和Brock模型相比，E-nose将更少的患者定为恶性结节患者（低风险：2 vs.9和11；p值分别为：p=0.028和p=0.011），更多的恶性结节病例在不进行活检的情况下得以治疗（高风险：27 vs.19和6；p=0.057和p<0.001）。

 

Conclusions 结论

In the setting of clinical stage I lung cancer, E-nose has good agreement with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a “multiomics” platform.

在临床癌症I期的背景下，E-nose与组织病理学有良好的一致性。因此，E-nose技术可在成像之外作为“多组学”平台的一部分。