Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 493

The DOI matches its Crossref record.

Diagnostic Accuracy of Canine Scent Detection in Early- and Late-Stage Lung and Breast Cancers

Open access
McCulloch, Michael, Jezierski, Tadeusz, Broffman, Michael, Hubbard, Alan, Turner, Kirk, Janecki, Teresa·2006·Integrative Cancer Therapies

Abstract

Background: Lung and breast cancers are leading causes of cancer death worldwide. Prior exploratory work has shown that patterns of biochemical markers have been found in the exhaled breath of patients with lung and breast cancers that are distinguishable from those of controls. However, chemical analysis of exhaled breath has not shown suitability for individual clinical diagnosis. Methods: The authors used a food reward-based method of training 5 ordinary household dogs to distinguish, by scent alone, exhaled breath samples of 55 lung and 31 breast cancer patients from those of 83 healthy controls. A correct indication of cancer samples by the dogs was sitting/lying in front of the sample. A correct response to control samples was to ignore the sample. The authors first trained the dogs in a 3-phase sequential process with gradually increasing levels of challenge. Once trained, the dogs’ ability to distinguish cancer patients from controls was then tested using breath samples from subjects not previously encountered by the dogs. The researchers blinded both dog handlers and experimental observers to the identity of breath samples. The diagnostic accuracy data reported were obtained solely from the dogs’ sniffing, in double-blinded conditions, of these breath samples obtained from subjects not previously encountered by the dogs during the training period. Results: Among lung cancer patients and controls, overall sensitivity of canine scent detection compared to biopsy-confirmed conventional diagnosis was 0.99 (95% confidence interval [CI], 0.99, 1.00) and overall specificity 0.99 (95% CI, 0.96, 1.00). Among breast cancer patients and controls, sensitivity was 0.88 (95% CI, 0.75, 1.00) and specificity 0.98 (95% CI, 0.90, 0.99). Sensitivity and specificity were remarkably similar across all 4 stages of both diseases. Conclusion: Training was efficient and cancer identification was accurate; in a matter of weeks, ordinary household dogs with only basic behavioral “puppy training” were trained to accurately distinguish breath samples of lung and breast cancer patients from those of controls. This pilot work using canine scent detection demonstrates the validity of using a biological system to examine exhaled breath in the diagnostic identification of lung and breast cancers. Future work should closely examine the chemistry of exhaledbreath to identify which chemical compounds can most accurately identify the presence of cancer.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/1534735405285096

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 493

Metadata

Authors
McCulloch, M., Jezierski, T., Broffman, M., Hubbard, A., Turner, K., & Janecki, T.
Venue
Integrative Cancer Therapies
Published
2006-03
Volume
5
Issue
1
Pages
30-39
ISSN
  • 1534-7354 (ISSN-L)
  • 1552-695X
OpenAlex
W2119514457
Cited by
493
References
0
FWCI
12.19
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Diagnostic Accuracy of Canine Scent Detection in Early- and Late-Stage Lung and Breast Cancers. https://app.cochat.ai/papers/10.1177/1534735405285096
The paper
McCulloch, M., Jezierski, T., Broffman, M., Hubbard, A., Turner, K., & Janecki, T. (2006). Diagnostic Accuracy of Canine Scent Detection in Early- and Late-Stage Lung and Breast Cancers. Integrative Cancer Therapies. https://doi.org/10.1177/1534735405285096

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.