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eNose analysis for early immunotherapy response monitoring in non-small cell lung cancer.
Buma, Alessandra I G; Muller, Mirte; de Vries, Rianne; Sterk, Peter J; van der Noort, Vincent; Wolf-Lansdorf, Marguerite; Farzan, Niloufar; Baas, Paul; van den Heuvel, Michel M.
Affiliation
  • Buma AIG; Radboud University Medical Centre, Nijmegen, the Netherlands.
  • Muller M; Netherlands Cancer Institute, Amsterdam, the Netherlands.
  • de Vries R; Amsterdam University Medical Center, Amsterdam, the Netherlands; Breathomix B.V. (www.breathomix.com), Leiden, the Netherlands.
  • Sterk PJ; Amsterdam University Medical Center, Amsterdam, the Netherlands.
  • van der Noort V; Netherlands Cancer Institute, Amsterdam, the Netherlands.
  • Wolf-Lansdorf M; Netherlands Cancer Institute, Amsterdam, the Netherlands.
  • Farzan N; Breathomix B.V. (www.breathomix.com), Leiden, the Netherlands.
  • Baas P; Netherlands Cancer Institute, Amsterdam, the Netherlands.
  • van den Heuvel MM; Radboud University Medical Centre, Nijmegen, the Netherlands. Electronic address: michel.vandenheuvel@radboudumc.nl.
Lung Cancer ; 160: 36-43, 2021 10.
Article in En | MEDLINE | ID: mdl-34399166
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.
Subject(s)
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carcinoma, Non-Small-Cell Lung / Lung Neoplasms Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Humans Language: En Journal: Lung Cancer Journal subject: NEOPLASIAS Year: 2021 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carcinoma, Non-Small-Cell Lung / Lung Neoplasms Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Humans Language: En Journal: Lung Cancer Journal subject: NEOPLASIAS Year: 2021 Document type: Article Affiliation country: