Canine Olfaction Combined With Bayesian Modeling for Multicancer Detection From Breath Samples: A Phase II Study in India
Trained dogs paired with AI can detect multiple cancers from breath with high accuracy in early stages, offering a low-cost screening option for resource-limited settings.
This Phase II study in 1,502 participants across 6 Indian hospitals showed that trained detection dogs combined with a Bayesian fusion algorithm can detect multiple cancer types from breath samples with over 90% sensitivity and specificity. Notably, sensitivity was equally high for early-stage disease (stages I-II), supporting potential use as a low-cost triage screen in low- and middle-income country settings.
What the study was
- Study design
- Phase II multicenter assessor-masked case-control study
- Population
- Treatment-naïve biopsy-confirmed cancer patients (7 major cancer types) and controls in India; 6 hospitals in Karnataka
- Sample size
- 1502
- Category
- Early Detection
- Maturity
- Validated
- Journal
- Journal of Clinical Oncology
Why it surfaced
Novel multicancer breath triage system achieving >90% sensitivity across 7 cancer types including stage I-II in a Phase II study, with direct relevance to LMIC screening where low-cost approaches are essential. Journal: JCO. Multicenter design with 1,502 test participants.
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