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Acem, I.; Praag, V.M. van; Mostert, C.Q.B.; Wal, R.J.P. van der; Neijenhuis, R.M.L.; Verhoef, C.; ... ; Sande, M.A.J. van de (2023)

Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study

Article / Letter to editor
Plain language summary:  Diagnosing soft tissue sarcoma (STS) among the large number of benign soft tissue tumors is challenging. There is a serious need for a novel and easy tool that could accurately detect patients with STS. This study aimed to assess how well an easy-to-use electronic nose could differentiate between patients with STS and those without STS based on their exhaled breath. This is the first pilot study to reveal that an electronic nose could serve as a diagnostic tool for the detection of STS with a good performance. Future studies are needed to validate the findings in larger cohorts. Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques...Show morePlain language summary:  Diagnosing soft tissue sarcoma (STS) among the large number of benign soft tissue tumors is challenging. There is a serious need for a novel and easy tool that could accurately detect patients with STS. This study aimed to assess how well an easy-to-use electronic nose could differentiate between patients with STS and those without STS based on their exhaled breath. This is the first pilot study to reveal that an electronic nose could serve as a diagnostic tool for the detection of STS with a good performance. Future studies are needed to validate the findings in larger cohorts. Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques were used to develop the best-fitting model. Results: Fifty-nine breath samples were collected (29 STS and 30 control) from March 2018 to March 2022. The final model yielded a c-statistic of 0.85 with a sensitivity of 83% and specificity of 60%. Conclusion: This study suggests that exhaled volatile organic compound analysis could serve as a noninvasive diagnostic biomarker for the detection of STS with a good performance.Show less
breath analysis
diagnostic test
electronic nose
soft tissue sarcoma
volatile organic compounds
All authors
Acem, I.; Praag, V.M. van; Mostert, C.Q.B.; Wal, R.J.P. van der; Neijenhuis, R.M.L.; Verhoef, C.; Grunhagen, D.J.; Sande, M.A.J. van de
Date
2023-05-01
Journal
Future Oncology
Volume
19
Issue
10
DOI
doi:10.2217/fon-2022-1122