Electronic noses effectively detect cancer with high accuracy using exhaled breath: JAMA

Written By :  Dr. Hiral patel
Medically Reviewed By :  Dr. Kamal Kant Kohli
Published On 2022-06-30 16:24 GMT   |   Update On 2022-07-01 08:52 GMT

Netherlands: Electronic noses (e-noses) have a relatively high diagnostic accuracy in the detection of cancer in exhaled breath, suggests a systematic review and meta-analysis results published in JAMA Network Open. However, the researchers add that there is a need for standardized external validation studies that investigate their diagnostic accuracy for establishing their role in the...

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Netherlands: Electronic noses (e-noses) have a relatively high diagnostic accuracy in the detection of cancer in exhaled breath, suggests a systematic review and meta-analysis results published in JAMA Network Open. However, the researchers add that there is a need for standardized external validation studies that investigate their diagnostic accuracy for establishing their role in the diagnostic workup of cancer. 

Cancer has become a major cause of global mortality, leading to the emerging recognition of cancer control as a global health priority. The composition of volatile organic compounds (VOCs) in exhaled breath changes because of pathological processes, such as cancer and can be used for noninvasive cancer diagnoses. Exhaled breath contains thousands of VOCs which vary in composition depending on health status.

Electronic noses (e-noses) are a relatively new, emerging technique for analyzing VOCs in exhaled breath. E-noses are portable, cheap, and easy-to-use diagnostic tests that produce rapid results. Several reviews have uniformly concluded that e-noses have the potential to become promising diagnostic tools in everyday clinical practice, but no e-nose is being used in clinical practice to detect malignant tumors.

Co-author Max H, Maastricht University, Netherlands, and his research team conducted a Systematic Review and Meta-analysis to provide an overview of the diagnostic accuracy and methodologic challenges of using e-noses for cancer detection.

Researchers performed an electronic search in the PubMed and Embase databases (2000-2021). Inclusion criteria were the use of e-nose technology, detection of cancer, and analysis of exhaled breath. Exclusion criteria were set as studies published before 2000; not performed in humans; not performed in adults; that only analyzed biofluids; and that exclusively used gas chromatography-mass spectrometry to analyze exhaled breath samples.52 articles with a total of 3677 patients with cancer were identified. The main outcomes were sensitivity, specificity, and mean area under the receiver operating characteristic curve. 

Key findings of the review,

• The sensitivity of e-noses ranged from 48.3% to 95.8% and the specificity from 10.0% to 100.0%

• The pooled analysis resulted in a mean (SE) area under the receiver operating characteristic curve of 94%, a sensitivity of 90%, and a specificity of 87%.

• The differences in the selection of patients, endogenous and exogenous factors, and collection of exhaled breath, resulted in considerable heterogeneity among the studies.

The authors conclude that the study results demonstrated high diagnostic accuracy of e-noses for the detection of cancer. Though, the existing studies generally consisted of feasibility studies with small sample sizes, a lack of standardization, and a high risk of bias.

Adequately powered, multicenter external validation studies are necessary to establish the potential of e-noses in the diagnostic workup of cancer. Future studies should investigate the type of cancer that would benefit most from the use of e-noses using exhaled breath. Also, before clinical implementation, the lack of standardization and reproducibility in the field of e-nose research must be addressed, the authors wrote.

Reference:

Scheepers MHMC, Al-Difaie Z, Brandts L, Peeters A, van Grinsven B, Bouvy ND. Diagnostic Performance of Electronic Noses in Cancer Diagnoses Using Exhaled Breath: A Systematic Review and Meta-analysis. JAMA Netw Open. 2022;5(6):e2219372. doi:10.1001/jamanetworkopen.2022.19372

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Article Source : JAMA Network Open

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