Patients with COPD are at high risk of developing lung cancer, 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 COPD patients.

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

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). 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 analysis, linear discriminant analysis and receiver operating characteristic analysis.

Exhaled breath data of 682 COPD patients and 211 lung cancer patients were available. 37 COPD patients (5.4%) developed clinically manifest lung cancer within 2 years after inclusion. Principal component 1, 2 and 3 were significantly different between patients with COPD and lung cancer in both training and validation sets with ROC-AUCs of 0.89 (CI:0.83-0.95) and 0.86 (CI:0.81-0.89). The same three principal components showed significant differences (p<0.01) at baseline between COPD patients who did and did not subsequently develop lung cancer within 2 years, with a cross-validation value of 87% and ROC-AUC of 0.90 (CI:0.84-0.95).

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