Introduction: 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. Methods: 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; moderate-risk, ≥0.2 to 0.7; high-risk, ≥0.7). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models. Results: 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). Conclusions: 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.

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

Pennazza, Giorgio;Santonico, Marco;Crucitti, Pierfilippo;Incalzi, Raffaele Antonelli;Zompanti, Alessandro;Merone, Mario;
2024-01-01

Abstract

Introduction: 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. Methods: 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; moderate-risk, ≥0.2 to 0.7; high-risk, ≥0.7). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models. Results: 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). Conclusions: 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.
2024
Biopsy; Diagnosis; E-nose; Lung cancer; Stage I
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/77643
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