Abstract
ObjectivesExhaled 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 MethodsThis 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. ResultsIn 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). ConclusionExhaled 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.
Highlights
This prospective observational study shows that SpiroNose exhaled breath analysis can be used to identify advanced non-small cell lung cancer (NSCLC) patients with an objective response to anti-progressive disease (PD)-1 therapy more accurately at early stage of treatment when compared to baseline as part of routine assessment during early treatment monitoring in daily clinical practice
Our study extends the work of De Vries et al, who investigated whether sensitivity to anti-PD-1 therapy in patients with advanced NSCLC might be re flected by a distinct exhaled breathprint
After six weeks of treatment, patients classified as partial response (PR) showed a distinct clustering of prediction scores towards higher probabilities of an objective response, while patients classified as PD showed a distinct clustering towards lower probabilities of an objective response when compared to baseline
Summary
The recent introduction of immune checkpoint inhibitors (ICIs) in daily clinical practice has significantly improved the 5-year survival rate in patients with metastatic non-small cell lung cancer (NSCLC) [1]. Results have shown that only a minority of patients ex periences a relevant clinical benefit [2]. Treatment continuation is currently based on tumor dynamics evaluated by radiological imaging. Since the only validated predictive biomarker tumor PD-L1 expression is fairly inaccurate, other, and preferably non-invasive, predictive biomarkers are being investi gated to avoid losing valuable time and undesirable immune-related adverse events (IRAEs), and to reduce unnecessary costs [2,5,6,7,8,9]
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