Development and Multi-center Validation of a Breathomics-Based Triage Tool for Lung Cancer: A Prospective Study of 5,214 Participants.
A breath test successfully identified lung cancer with 93% sensitivity in nearly 550 patients, suggesting a simple, non-invasive screening tool may soon help catch disease earlier.
An ML-integrated exhaled volatile organic compound (VOC) breathomics model achieved AUC 0.85 (sensitivity 93.1%, NPV 71.0%) for lung cancer triage in an independent external validation cohort of 545 patients, representing the largest prospective multicenter breath test validation study to date for lung cancer. This record was retained from the prior triage attempt for PubMed pipeline handoff.
What the study was
- Study design
- prospective multicenter diagnostic accuracy study (n=5,214)
- Category
- ai_ml_clinical_diagnostics
- Maturity
- Potentially Practice-Changing
- Journal
- Chest
Why it surfaced
Largest prospective breathomics validation study to date for lung cancer triage (n=5,214); AUC 0.85 in geographically independent external cohort with prospective locked design. Chest publication addresses a major gap in non-invasive CT follow-up triage. High translational readiness score for AI/ML diagnostics watchlist.
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