eNose analysis for early immunotherapy response monitoring in non-small cell lung cancer
| Autor: | Paul Baas, Vincent van der Noort, Rianne de Vries, Marguerite Wolf-Lansdorf, Michel M van den Heuvel, Peter J. Sterk, Alessandra I.G. Buma, Niloufar Farzan, Mirte Muller |
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| Přispěvatelé: | Graduate School, AII - Inflammatory diseases, ARD - Amsterdam Reproduction and Development, Pulmonology |
| Rok vydání: | 2021 |
| Předmět: |
Pulmonary and Respiratory Medicine
Oncology Cancer Research medicine.medical_specialty Lung Neoplasms Rare cancers Radboud Institute for Molecular Life Sciences [Radboudumc 9] Non-invasive biomarker All institutes and research themes of the Radboud University Medical Center Non-small cell lung cancer Carcinoma Non-Small-Cell Lung Internal medicine medicine Carcinoma Humans Stage (cooking) Lung cancer Receiver operating characteristic business.industry Area under the curve medicine.disease Breath Tests Breath gas analysis Exhalation Response Evaluation Criteria in Solid Tumors Exhaled breath analysis Observational study Immunotherapy business |
| Zdroj: | Lung Cancer, 160, pp. 36-43 Lung Cancer, 160, 36-43 Lung cancer (Amsterdam, Netherlands), 160, 36-43. Elsevier Ireland Ltd |
| ISSN: | 0169-5002 |
| DOI: | 10.1016/j.lungcan.2021.07.017 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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