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Detection of Cancer in Breath Samples by Trained Detection Dogs

Recruiting
Conditions
Lung Cancer
PROSTATE CANCER
Breast Cancer
Colorectal Cancer
Registration Number
NCT06255041
Lead Sponsor
SpotitEarly
Brief Summary

The goal of this study is to show that trained detection dogs can identify breast, lung, prostate or colorectal cancer by sniffing masks containing breath samples. In this study, individuals who will undergo cancer screening at an integrated cancer prevention center or biopsy for a suspected malignancy, will be asked to provide a breath sample by breathing into a surgical mask. The mask will then be sent to the laboratory, where trained detection dogs will determine if the person who provided the mask has breast, lung, prostate or colorectal cancer or if the person does not have these types of cancer. The results provided by the dogs will be compared to the actual cancer screening results or biopsy results in order to determine the accuracy of cancer detection by the trained dogs.

Detailed Description

Not available

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
1250
Inclusion Criteria
  1. Men and women aged 18 and over.
  2. Signing an informed consent prior to performing the test.
  3. Intended to undergo screening tests for cancer detection.
  4. Did not smoke 2 hours before providing the breath sample
  5. Did not drink coffee in the hour before providing the breath sample
  6. Did not drink an alcoholic beverage in the hour prior to providing the breath sample.
  7. Did not eat food in the hour before providing the breath sample.
Exclusion Criteria
  1. Was diagnosed with cancer or was treated for cancer in the seven years preceding the study, excluding non-metastatic skin tumors that were surgically removed.
  2. Undergoing chemotherapy for any purpose.
  3. Pregnant or breastfeeding
  4. Had a medical procedure in the chest cavity and/or airways in the two weeks prior to providing the breath sample that may interfere with the ability to correctly provide a breath sample.
  5. Has a Helicobacter pylori infection.
  6. Has a peptic ulcer disease.
  7. Has a flare-up of an inflammatory bowel disease (Crohn's disease/ulcerative colitis).
  8. has an active infection, such as COVID-19, abscess, bacterial/viral/fungal infection, pneumonia, laryngitis, intestinal inflammation, active tuberculosis infection.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Sensitivity of detection of any cancer (breast, lung, prostate or colorectal cancer) by the breath test.2 years

Sensitivity is defined as the number of participants who were identified by the breath sample test as positive for cancer divided by the number of participants who were identified by the gold standard test as being positive for cancer.

Specificity of detection of any cancer (breast, lung, prostate or colorectal cancer) by the breath test.2 years

Specificity is defined as the number of participants who were identified by the breath sample test as negative for cancer divided by the number of participants who were identified by the gold standard test as being negative for cancer.

Secondary Outcome Measures
NameTimeMethod
Specificity, sensitivity, negative predictive value, and positive predictive value of the breath test for detecting colorectal cancer2 years
The rate of early-stage cancer cases detected by the breath test2 years
Specificity, sensitivity, negative predictive value, and positive predictive value of the breath test for detecting breast cancer2 years
Specificity, sensitivity, negative predictive value, and positive predictive value of the breath test for detecting prostate cancer2 years
Inter-observer variability among the detection dogs2 years
Intra-observer variability among the detection dogs2 years
Specificity, sensitivity, negative predictive value, and positive predictive value of the breath test for detecting lung cancer2 years

Trial Locations

Locations (2)

Rambam Health Care Campus

🇮🇱

Haifa, Israel

Tel Aviv Sourasky Medical Center

🇮🇱

Tel Aviv, Israel

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