Kooistra, S.A. (Simone Anna) (2019) Detecting non-small cell lung cancer by electronic nose technology : a preliminary external validation study. thesis, Medicine.
Full text available on request.Abstract
Background Lung cancer is a leading cause of death worldwide due to late detection. Exhaled breath contains volatile organic compounds (VOC’s), reflecting pathological processes, which might be used to detect lung cancer earlier. The aim of this study is to externally validate the diagnostic performance of the previously obtained prediction model of the Aeonose™ to detect lung cancer. Materials and Methods: It concerns an intermediate analysis of a prospective, single-centre study to externally validate the diagnostic performance of the Aeonose™ to detect lung cancer, which was previously obtained in a training study. Besides, a new model was created using the same subjects included for validating the training model. 21 subjects with confirmed non-small cell lung cancer (NSCLC), 5 subjects with suspected lung cancer, but proven negative, and 56 healthy volunteers were included. Results Focusing on a high sensitivity and a high negative predictive value (NPV), the analyses showed a sensitivity of 85.7%, a specificity of 34.4%, an NPV of 87.5%, and an area under the curve (AUC) of 0.64 when validating the previous obtained model. The newly created model resulted in a sensitivity of 100%, a specificity of 72.1%, an NPV of 100%, and an AUC of 0.96. Conclusion This study has reaffirmed promising results by discriminating breath prints of NSCLC patients and healthy controls. Due to high sensitivity and high NPV, the Aeonose™ could be of additional value in screening programs for lung cancer. However, the pronounced difference in results in the two presented analyses suggest to perform more and larger external validation studies.
| Item Type: | Thesis (Thesis) |
|---|---|
| Supervisor name: | Faculty supervisor: and Palen, Prof. Dr. J. van der |
| Supervisor name: | Daily supervisor: and Kort, Drs. S. and Location: and Medisch Spectrum Twente (MST) Enschede Department: Pulmonolo |
| Faculty: | Medical Sciences |
| Date Deposited: | 25 Jun 2020 11:05 |
| Last Modified: | 25 Jun 2020 11:05 |
| URI: | https://umcg.studenttheses.ub.rug.nl/id/eprint/2535 |
Actions (login required)
 |
View Item |