ArticleERJ open research2025
The electronic nose in lung cancer diagnostics: a systematic review and meta-analysis.
Article in ERJ open research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Few Labels, Many Breaths: Adapting Electronic Noses for Lung Cancer Detection.Respirology (Carlton, Vic.) · 2026Article
- Few-Shot Lung Cancer Classification via Electronic Nose Using Large Language Models: A Multicentre Prospective Study.Respirology (Carlton, Vic.) · 2026Article
- Real-Time Breath Diagnostics: Linking Molecular Pathways, Measurement Technologies, and Clinical Translation.International journal of molecular sciences · 2026Review
- Diagnostic performance of eNose technology in detecting colorectal cancer recurrence: A prospective evaluation.PloS one · 2026Article
- Exhaled Aldehydes and Ketones as Biomarkers of Lung Cancer and Diabetes: Review of Sensor Technologies for Early Disease Diagnosis.Biosensors · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung cancer remains a leading cause of cancer-related deaths. Early-stage detection is pivotal for curative interventions, yet most cases are diagnosed at advanced stages. Noninvasive point-of-care diagnostic strategies are needed to reduce lung cancer mortality rates. We assess the potential of electronic nose (eNose) devices as a tool for lung cancer detection. Study design and methods: All online available databases were searched. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we reviewed studies using eNose for Results: We included 35 studies, comprising 4483 patients. Pooled sensitivity and specificity were 0.90 (95% CI 0.87-0.93) and 0.89 (95% CI 0.85-0.93), respectively. The median negative predictive value was 0.93 and the median area under the curve was 0.91. Both the likelihood of bias and concerns regarding applicability were minimal. Interpretation: eNose devices hold promise as noninvasive, point-of-care tools for lung cancer diagnosis. Owing to the high sensitivity and negative predictive values and great ease of use, they could be valuable additions to the diagnostic toolbox. Further research and validation efforts are critical to maximise their impact on early lung cancer detection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.